test: build a failing example with LogicalPlanBuilder

Signed-off-by: discord9 <discord9@163.com>

.github/actions/setup-etcd-cluster/action.yml

@@ -12,7 +12,7 @@ runs:
   steps:
   - name: Install Etcd cluster
     shell: bash
-    run: |
+    run: | 
       helm upgrade \
         --install etcd oci://registry-1.docker.io/bitnamicharts/etcd \
         --set replicaCount=${{ inputs.etcd-replicas }} \
@@ -24,9 +24,4 @@ runs:
         --set auth.rbac.token.enabled=false \
         --set persistence.size=2Gi \
         --create-namespace \
-        --set global.security.allowInsecureImages=true \
-        --set image.registry=docker.io \
-        --set image.repository=greptime/etcd \
-        --set image.tag=3.6.1-debian-12-r3 \
-        --version 12.0.8 \
         -n ${{ inputs.namespace }}

.github/actions/setup-greptimedb-cluster/with-remote-wal.yaml

@@ -1,8 +1,3 @@
-logging:
-  level: "info"
-  format: "json"
-  filters:
-  - log_store=debug
 meta:
   configData: |-
     [runtime]

.github/actions/setup-kafka-cluster/action.yml

@@ -12,7 +12,7 @@ runs:
   steps:
   - name: Install Kafka cluster
     shell: bash
-    run: |
+    run: | 
       helm upgrade \
         --install kafka oci://registry-1.docker.io/bitnamicharts/kafka \
         --set controller.replicaCount=${{ inputs.controller-replicas }} \
@@ -23,8 +23,4 @@ runs:
         --set listeners.controller.protocol=PLAINTEXT \
         --set listeners.client.protocol=PLAINTEXT \
         --create-namespace \
-        --set image.registry=docker.io \
-        --set image.repository=greptime/kafka \
-        --set image.tag=3.9.0-debian-12-r1 \
-        --version 31.0.0 \
         -n ${{ inputs.namespace }}

.github/actions/setup-postgres-cluster/action.yml

@@ -6,7 +6,9 @@ inputs:
     description: "Number of PostgreSQL replicas"
   namespace:
     default: "postgres-namespace"
-    description: "The PostgreSQL namespace"
+  postgres-version:
+    default: "14.2"
+    description: "PostgreSQL version"
   storage-size:
     default: "1Gi"
     description: "Storage size for PostgreSQL"
@@ -20,11 +22,7 @@ runs:
       helm upgrade \
         --install postgresql oci://registry-1.docker.io/bitnamicharts/postgresql \
         --set replicaCount=${{ inputs.postgres-replicas }} \
-        --set global.security.allowInsecureImages=true \
+        --set image.tag=${{ inputs.postgres-version }} \
-        --set image.registry=docker.io \
-        --set image.repository=greptime/postgresql \
-        --set image.tag=17.5.0-debian-12-r3 \
-        --version 16.7.4 \
         --set persistence.size=${{ inputs.storage-size }} \
         --set postgresql.username=greptimedb \
         --set postgresql.password=admin \

.github/scripts/check-version.sh

@@ -35,8 +35,8 @@ HIGHER_VERSION=$(printf "%s\n%s" "$CLEAN_CURRENT" "$CLEAN_LATEST" | sort -V | ta
 
 if [ "$HIGHER_VERSION" = "$CLEAN_CURRENT" ]; then
   echo "Current version ($CLEAN_CURRENT) is NEWER than or EQUAL to latest ($CLEAN_LATEST)"
-  echo "is-current-version-latest=true" >> $GITHUB_OUTPUT
+  echo "should-push-latest-tag=true" >> $GITHUB_OUTPUT
 else
   echo "Current version ($CLEAN_CURRENT) is OLDER than latest ($CLEAN_LATEST)"
-  echo "is-current-version-latest=false" >> $GITHUB_OUTPUT
+  echo "should-push-latest-tag=false" >> $GITHUB_OUTPUT
 fi

.github/scripts/pull-test-deps-images.sh

@@ -1,34 +0,0 @@
-#!/bin/bash
-
-# This script is used to pull the test dependency images that are stored in public ECR one by one to avoid rate limiting.
-
-set -e
-
-MAX_RETRIES=3
-
-IMAGES=(
-  "greptime/zookeeper:3.7"
-  "greptime/kafka:3.9.0-debian-12-r1"
-  "greptime/etcd:3.6.1-debian-12-r3"
-  "greptime/minio:2024"
-  "greptime/mysql:5.7"
-)
-
-for image in "${IMAGES[@]}"; do
-  for ((attempt=1; attempt<=MAX_RETRIES; attempt++)); do
-    if docker pull "$image"; then
-      # Successfully pulled the image.
-      break
-    else
-      # Use some simple exponential backoff to avoid rate limiting.
-      if [ $attempt -lt $MAX_RETRIES ]; then
-        sleep_seconds=$((attempt * 5))
-        echo "Attempt $attempt failed for $image, waiting $sleep_seconds seconds"
-        sleep $sleep_seconds  # 5s, 10s delays
-      else
-        echo "Failed to pull $image after $MAX_RETRIES attempts"
-        exit 1
-      fi
-    fi
-  done
-done

.github/scripts/update-dev-builder-version.sh

@@ -21,7 +21,7 @@ update_dev_builder_version() {
 
   # Commit the changes.
   git add Makefile
-  git commit -s -m "ci: update dev-builder image tag"
+  git commit -m "ci: update dev-builder image tag"
   git push origin $BRANCH_NAME
 
   # Create a Pull Request.

.github/workflows/develop.yml

@@ -12,7 +12,6 @@ on:
       - 'docker/**'
       - '.gitignore'
       - 'grafana/**'
-      - 'Makefile'
   workflow_dispatch:
 
 name: CI
@@ -618,12 +617,10 @@ jobs:
       - uses: actions/checkout@v4
         with:
           persist-credentials: false
-
       - if: matrix.mode.kafka
         name: Setup kafka server
         working-directory: tests-integration/fixtures
-        run:  ../../.github/scripts/pull-test-deps-images.sh && docker compose up -d --wait kafka
+        run: docker compose up -d --wait kafka
-
       - name: Download pre-built binaries
         uses: actions/download-artifact@v4
         with:
@@ -685,30 +682,6 @@ jobs:
       - name: Run cargo clippy
         run: make clippy
 
-  check-udeps:
-    if: ${{ github.repository == 'GreptimeTeam/greptimedb' }}
-    name: Check Unused Dependencies
-    runs-on: ubuntu-latest
-    timeout-minutes: 60
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          persist-credentials: false
-      - uses: arduino/setup-protoc@v3
-        with:
-          repo-token: ${{ secrets.GITHUB_TOKEN }}
-      - uses: actions-rust-lang/setup-rust-toolchain@v1
-      - name: Rust Cache
-        uses: Swatinem/rust-cache@v2
-        with:
-          shared-key: "check-udeps"
-          cache-all-crates: "true"
-          save-if: ${{ github.ref == 'refs/heads/main' }}
-      - name: Install cargo-udeps
-        run: cargo install cargo-udeps --locked
-      - name: Check unused dependencies
-        run: make check-udeps
-
   conflict-check:
     if: ${{ github.repository == 'GreptimeTeam/greptimedb' }}
     name: Check for conflict
@@ -724,7 +697,7 @@ jobs:
     if: ${{ github.repository == 'GreptimeTeam/greptimedb' && github.event_name != 'merge_group' }}
     runs-on: ubuntu-22.04-arm
     timeout-minutes: 60
-    needs: [conflict-check, clippy, fmt, check-udeps]
+    needs:  [conflict-check, clippy, fmt]
     steps:
       - uses: actions/checkout@v4
         with:
@@ -736,7 +709,7 @@ jobs:
       - name: Install toolchain
         uses: actions-rust-lang/setup-rust-toolchain@v1
         with:
-          cache: false
+            cache: false
       - name: Rust Cache
         uses: Swatinem/rust-cache@v2
         with:
@@ -746,11 +719,9 @@ jobs:
           save-if: ${{ github.ref == 'refs/heads/main' }}
       - name: Install latest nextest release
         uses: taiki-e/install-action@nextest
-
       - name: Setup external services
         working-directory: tests-integration/fixtures
-        run: ../../.github/scripts/pull-test-deps-images.sh && docker compose up -d --wait
+        run: docker compose up -d --wait
-
       - name: Run nextest cases
         run: cargo nextest run --workspace -F dashboard -F pg_kvbackend -F mysql_kvbackend
         env:
@@ -767,11 +738,8 @@ jobs:
           GT_MINIO_ACCESS_KEY: superpower_password
           GT_MINIO_REGION: us-west-2
           GT_MINIO_ENDPOINT_URL: http://127.0.0.1:9000
-          GT_ETCD_TLS_ENDPOINTS: https://127.0.0.1:2378
           GT_ETCD_ENDPOINTS: http://127.0.0.1:2379
           GT_POSTGRES_ENDPOINTS: postgres://greptimedb:admin@127.0.0.1:5432/postgres
-          GT_POSTGRES15_ENDPOINTS: postgres://test_user:test_password@127.0.0.1:5433/postgres
-          GT_POSTGRES15_SCHEMA: test_schema
           GT_MYSQL_ENDPOINTS: mysql://greptimedb:admin@127.0.0.1:3306/mysql
           GT_KAFKA_ENDPOINTS: 127.0.0.1:9092
           GT_KAFKA_SASL_ENDPOINTS: 127.0.0.1:9093
@@ -804,11 +772,9 @@ jobs:
         uses: taiki-e/install-action@nextest
       - name: Install cargo-llvm-cov
         uses: taiki-e/install-action@cargo-llvm-cov
-
       - name: Setup external services
         working-directory: tests-integration/fixtures
-        run: ../../.github/scripts/pull-test-deps-images.sh && docker compose up -d --wait
+        run: docker compose up -d --wait
-        
       - name: Run nextest cases
         run: cargo llvm-cov nextest --workspace --lcov --output-path lcov.info -F dashboard -F pg_kvbackend -F mysql_kvbackend
         env:
@@ -824,11 +790,8 @@ jobs:
           GT_MINIO_ACCESS_KEY: superpower_password
           GT_MINIO_REGION: us-west-2
           GT_MINIO_ENDPOINT_URL: http://127.0.0.1:9000
-          GT_ETCD_TLS_ENDPOINTS: https://127.0.0.1:2378
           GT_ETCD_ENDPOINTS: http://127.0.0.1:2379
           GT_POSTGRES_ENDPOINTS: postgres://greptimedb:admin@127.0.0.1:5432/postgres
-          GT_POSTGRES15_ENDPOINTS: postgres://test_user:test_password@127.0.0.1:5433/postgres
-          GT_POSTGRES15_SCHEMA: test_schema
           GT_MYSQL_ENDPOINTS: mysql://greptimedb:admin@127.0.0.1:3306/mysql
           GT_KAFKA_ENDPOINTS: 127.0.0.1:9092
           GT_KAFKA_SASL_ENDPOINTS: 127.0.0.1:9093

.github/workflows/docs.yml

@@ -10,7 +10,6 @@ on:
       - 'docker/**'
       - '.gitignore'
       - 'grafana/**'
-      - 'Makefile'
   push:
     branches:
       - main
@@ -22,7 +21,6 @@ on:
       - 'docker/**'
       - '.gitignore'
       - 'grafana/**'
-      - 'Makefile'
   workflow_dispatch:
 
 name: CI
@@ -67,12 +65,6 @@ jobs:
     steps:
       - run: 'echo "No action required"'
 
-  check-udeps:
-    name: Unused Dependencies
-    runs-on: ubuntu-latest
-    steps:
-      - run: 'echo "No action required"'
-
   coverage:
     runs-on: ubuntu-latest
     steps:

.github/workflows/release.yml

@@ -111,8 +111,7 @@ jobs:
       # The 'version' use as the global tag name of the release workflow.
       version: ${{ steps.create-version.outputs.version }}
 
-      # The 'is-current-version-latest' determines whether to update 'latest' Docker tags and downstream repositories.
+      should-push-latest-tag: ${{ steps.check-version.outputs.should-push-latest-tag }}
-      is-current-version-latest: ${{ steps.check-version.outputs.is-current-version-latest }}
     steps:
       - name: Checkout
         uses: actions/checkout@v4
@@ -322,7 +321,7 @@ jobs:
           image-registry-username: ${{ secrets.DOCKERHUB_USERNAME }}
           image-registry-password: ${{ secrets.DOCKERHUB_TOKEN }}
           version: ${{ needs.allocate-runners.outputs.version }}
-          push-latest-tag: ${{ needs.allocate-runners.outputs.is-current-version-latest == 'true' && github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' }}
+          push-latest-tag: ${{ needs.allocate-runners.outputs.should-push-latest-tag == 'true' && github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' }}
 
       - name: Set build image result
         id: set-build-image-result
@@ -369,7 +368,7 @@ jobs:
           dev-mode: false
           upload-to-s3: true
           update-version-info: true
-          push-latest-tag: ${{ needs.allocate-runners.outputs.is-current-version-latest == 'true' && github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' }}
+          push-latest-tag: ${{ needs.allocate-runners.outputs.should-push-latest-tag == 'true' && github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' }}
 
   publish-github-release:
     name: Create GitHub release and upload artifacts
@@ -477,7 +476,7 @@ jobs:
 
   bump-helm-charts-version:
     name: Bump helm charts version
-    if: ${{ github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' && needs.allocate-runners.outputs.is-current-version-latest == 'true' }}
+    if: ${{ github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' }}
     needs: [allocate-runners, publish-github-release]
     runs-on: ubuntu-latest
     permissions:
@@ -498,7 +497,7 @@ jobs:
 
   bump-homebrew-greptime-version:
     name: Bump homebrew greptime version
-    if: ${{ github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' && needs.allocate-runners.outputs.is-current-version-latest == 'true' }}
+    if: ${{ github.ref_type == 'tag' && !contains(github.ref_name, 'nightly') && github.event_name != 'schedule' }}
     needs: [allocate-runners, publish-github-release]
     runs-on: ubuntu-latest
     permissions:

.gitignore

@@ -52,9 +52,6 @@ venv/
 tests-fuzz/artifacts/
 tests-fuzz/corpus/
 
-# cargo-udeps reports
-udeps-report.json
-
 # Nix
 .direnv
 .envrc

CONTRIBUTING.md

@@ -55,18 +55,14 @@ GreptimeDB uses the [Apache 2.0 license](https://github.com/GreptimeTeam/greptim
 - To ensure that community is free and confident in its ability to use your contributions, please sign the Contributor License Agreement (CLA) which will be incorporated in the pull request process.
 - Make sure all files have proper license header (running `docker run --rm -v $(pwd):/github/workspace ghcr.io/korandoru/hawkeye-native:v3 format` from the project root).
 - Make sure all your codes are formatted and follow the [coding style](https://pingcap.github.io/style-guide/rust/) and [style guide](docs/style-guide.md).
-- Make sure all unit tests are passed using [nextest](https://nexte.st/index.html) `cargo nextest run --workspace --features pg_kvbackend,mysql_kvbackend` or `make test`.
+- Make sure all unit tests are passed using [nextest](https://nexte.st/index.html) `cargo nextest run`.
-- Make sure all clippy warnings are fixed (you can check it locally by running `cargo clippy --workspace --all-targets -- -D warnings` or `make clippy`).
+- Make sure all clippy warnings are fixed (you can check it locally by running `cargo clippy --workspace --all-targets -- -D warnings`).
-- Ensure there are no unused dependencies by running `make check-udeps` (clean them up with `make fix-udeps` if reported).
-- If you must keep a target-specific dependency (e.g. under `[target.'cfg(...)'.dev-dependencies]`), add a cargo-udeps ignore entry in the same `Cargo.toml`, for example:
-  `[package.metadata.cargo-udeps.ignore]` with `development = ["rexpect"]` (or `dependencies`/`build` as appropriate).
-- When modifying sample configuration files in `config/`, run `make config-docs` (which requires Docker to be installed) to update the configuration documentation and include it in your commit.
 
 #### `pre-commit` Hooks
 
 You could setup the [`pre-commit`](https://pre-commit.com/#plugins) hooks to run these checks on every commit automatically.
 
-1.  Install `pre-commit`
+1. Install `pre-commit`
 
         pip install pre-commit
 
@@ -74,7 +70,7 @@ You could setup the [`pre-commit`](https://pre-commit.com/#plugins) hooks to run
 
         brew install pre-commit
 
-2.  Install the `pre-commit` hooks
+2. Install the `pre-commit` hooks
 
         $ pre-commit install
         pre-commit installed at .git/hooks/pre-commit

Cargo.toml

@@ -98,12 +98,11 @@ rust.unexpected_cfgs = { level = "warn", check-cfg = ['cfg(tokio_unstable)'] }
 # See for more detaiils: https://github.com/rust-lang/cargo/issues/11329
 ahash = { version = "0.8", features = ["compile-time-rng"] }
 aquamarine = "0.6"
-arrow = { version = "56.0", features = ["prettyprint"] }
+arrow = { version = "54.2", features = ["prettyprint"] }
-arrow-array = { version = "56.0", default-features = false, features = ["chrono-tz"] }
+arrow-array = { version = "54.2", default-features = false, features = ["chrono-tz"] }
-arrow-buffer = "56.0"
+arrow-flight = "54.2"
-arrow-flight = "56.0"
+arrow-ipc = { version = "54.2", default-features = false, features = ["lz4", "zstd"] }
-arrow-ipc = { version = "56.0", default-features = false, features = ["lz4", "zstd"] }
+arrow-schema = { version = "54.2", features = ["serde"] }
-arrow-schema = { version = "56.0", features = ["serde"] }
 async-stream = "0.3"
 async-trait = "0.1"
 # Remember to update axum-extra, axum-macros when updating axum
@@ -122,30 +121,26 @@ clap = { version = "4.4", features = ["derive"] }
 config = "0.13.0"
 crossbeam-utils = "0.8"
 dashmap = "6.1"
-datafusion = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-common = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-expr = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-expr = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-functions = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-functions = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-functions-aggregate-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-functions-aggregate-common = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-optimizer = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-optimizer = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-orc = { git = "https://github.com/GreptimeTeam/datafusion-orc", rev = "a0a5f902158f153119316eaeec868cff3fc8a99d" }
+datafusion-physical-expr = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-physical-expr = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-physical-plan = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-physical-plan = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-sql = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-sql = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
+datafusion-substrait = { git = "https://github.com/waynexia/arrow-datafusion.git", rev = "12c0381babd52c681043957e9d6ee083a03f7646" }
-datafusion-substrait = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7d5214512740b4dfb742b6b3d91ed9affcc2c9d0" }
 deadpool = "0.12"
 deadpool-postgres = "0.14"
 derive_builder = "0.20"
 dotenv = "0.15"
 either = "1.15"
-etcd-client = { git = "https://github.com/GreptimeTeam/etcd-client", rev = "f62df834f0cffda355eba96691fe1a9a332b75a7", features = [
+etcd-client = "0.14"
-    "tls",
-    "tls-roots",
-] }
 fst = "0.4.7"
 futures = "0.3"
 futures-util = "0.3"
-greptime-proto = { git = "https://github.com/GreptimeTeam/greptime-proto.git", rev = "66eb089afa6baaa3ddfafabd0a4abbe317d012c3" }
+greptime-proto = { git = "https://github.com/GreptimeTeam/greptime-proto.git", rev = "ccfd4da48bc0254ed865e479cd981a3581b02d84" }
 hex = "0.4"
 http = "1"
 humantime = "2.1"
@@ -156,7 +151,7 @@ itertools = "0.14"
 jsonb = { git = "https://github.com/databendlabs/jsonb.git", rev = "8c8d2fc294a39f3ff08909d60f718639cfba3875", default-features = false }
 lazy_static = "1.4"
 local-ip-address = "0.6"
-loki-proto = { git = "https://github.com/GreptimeTeam/loki-proto.git", rev = "3b7cd33234358b18ece977bf689dc6fb760f29ab" }
+loki-proto = { git = "https://github.com/GreptimeTeam/loki-proto.git", rev = "1434ecf23a2654025d86188fb5205e7a74b225d3" }
 meter-core = { git = "https://github.com/GreptimeTeam/greptime-meter.git", rev = "5618e779cf2bb4755b499c630fba4c35e91898cb" }
 mockall = "0.13"
 moka = "0.12"
@@ -164,9 +159,9 @@ nalgebra = "0.33"
 nix = { version = "0.30.1", default-features = false, features = ["event", "fs", "process"] }
 notify = "8.0"
 num_cpus = "1.16"
-object_store_opendal = "0.54"
+object_store_opendal = "0.50"
 once_cell = "1.18"
-opentelemetry-proto = { version = "0.30", features = [
+opentelemetry-proto = { version = "0.27", features = [
     "gen-tonic",
     "metrics",
     "trace",
@@ -175,14 +170,13 @@ opentelemetry-proto = { version = "0.30", features = [
 ] }
 ordered-float = { version = "4.3", features = ["serde"] }
 parking_lot = "0.12"
-parquet = { version = "56.0", default-features = false, features = ["arrow", "async", "object_store"] }
+parquet = { version = "54.2", default-features = false, features = ["arrow", "async", "object_store"] }
 paste = "1.0"
 pin-project = "1.0"
 pretty_assertions = "1.4.0"
 prometheus = { version = "0.13.3", features = ["process"] }
 promql-parser = { version = "0.6", features = ["ser"] }
 prost = { version = "0.13", features = ["no-recursion-limit"] }
-prost-types = "0.13"
 raft-engine = { version = "0.4.1", default-features = false }
 rand = "0.9"
 ratelimit = "0.10"
@@ -194,7 +188,7 @@ reqwest = { version = "0.12", default-features = false, features = [
     "stream",
     "multipart",
 ] }
-rskafka = { git = "https://github.com/WenyXu/rskafka.git", rev = "7b0f31ed39db049b4ee2e5f1e95b5a30be9baf76", features = [
+rskafka = { git = "https://github.com/influxdata/rskafka.git", rev = "8dbd01ed809f5a791833a594e85b144e36e45820", features = [
     "transport-tls",
 ] }
 rstest = "0.25"
@@ -207,14 +201,15 @@ sea-query = "0.32"
 serde = { version = "1.0", features = ["derive"] }
 serde_json = { version = "1.0", features = ["float_roundtrip"] }
 serde_with = "3"
+shadow-rs = "1.1"
 simd-json = "0.15"
 similar-asserts = "1.6.0"
 smallvec = { version = "1", features = ["serde"] }
 snafu = "0.8"
-sqlparser = { git = "https://github.com/GreptimeTeam/sqlparser-rs.git", rev = "39e4fc94c3c741981f77e9d63b5ce8c02e0a27ea", features = [
+sqlparser = { git = "https://github.com/GreptimeTeam/sqlparser-rs.git", rev = "df6fcca80ce903f5beef7002cd2c1b062e7024f8", features = [
     "visitor",
     "serde",
-] } # branch = "v0.55.x"
+] } # branch = "v0.54.x"
 sqlx = { version = "0.8", features = [
     "runtime-tokio-rustls",
     "mysql",
@@ -224,20 +219,20 @@ sqlx = { version = "0.8", features = [
 strum = { version = "0.27", features = ["derive"] }
 sysinfo = "0.33"
 tempfile = "3"
-tokio = { version = "1.47", features = ["full"] }
+tokio = { version = "1.40", features = ["full"] }
 tokio-postgres = "0.7"
 tokio-rustls = { version = "0.26.2", default-features = false }
 tokio-stream = "0.1"
 tokio-util = { version = "0.7", features = ["io-util", "compat"] }
 toml = "0.8.8"
-tonic = { version = "0.13", features = ["tls-ring", "gzip", "zstd"] }
+tonic = { version = "0.12", features = ["tls", "gzip", "zstd"] }
 tower = "0.5"
 tower-http = "0.6"
 tracing = "0.1"
 tracing-appender = "0.2"
 tracing-subscriber = { version = "0.3", features = ["env-filter", "json", "fmt"] }
 typetag = "0.2"
-uuid = { version = "1.17", features = ["serde", "v4", "fast-rng"] }
+uuid = { version = "1.7", features = ["serde", "v4", "fast-rng"] }
 vrl = "0.25"
 zstd = "0.13"
 # DO_NOT_REMOVE_THIS: END_OF_EXTERNAL_DEPENDENCIES
@@ -296,7 +291,7 @@ mito-codec = { path = "src/mito-codec" }
 mito2 = { path = "src/mito2" }
 object-store = { path = "src/object-store" }
 operator = { path = "src/operator" }
-otel-arrow-rust = { git = "https://github.com/GreptimeTeam/otel-arrow", rev = "2d64b7c0fa95642028a8205b36fe9ea0b023ec59", features = [
+otel-arrow-rust = { git = "https://github.com/open-telemetry/otel-arrow", rev = "5d551412d2a12e689cde4d84c14ef29e36784e51", features = [
     "server",
 ] }
 partition = { path = "src/partition" }

Makefile

@@ -8,7 +8,7 @@ CARGO_BUILD_OPTS := --locked
 IMAGE_REGISTRY ?= docker.io
 IMAGE_NAMESPACE ?= greptime
 IMAGE_TAG ?= latest
-DEV_BUILDER_IMAGE_TAG ?= 2025-05-19-f55023f3-20250829091211
+DEV_BUILDER_IMAGE_TAG ?= 2025-05-19-b2377d4b-20250520045554
 BUILDX_MULTI_PLATFORM_BUILD ?= false
 BUILDX_BUILDER_NAME ?= gtbuilder
 BASE_IMAGE ?= ubuntu
@@ -22,7 +22,7 @@ SQLNESS_OPTS ?=
 ETCD_VERSION ?= v3.5.9
 ETCD_IMAGE ?= quay.io/coreos/etcd:${ETCD_VERSION}
 RETRY_COUNT ?= 3
-NEXTEST_OPTS := --retries ${RETRY_COUNT} --features pg_kvbackend,mysql_kvbackend
+NEXTEST_OPTS := --retries ${RETRY_COUNT}
 BUILD_JOBS ?= $(shell which nproc 1>/dev/null && expr $$(nproc) / 2) # If nproc is not available, we don't set the build jobs.
 ifeq ($(BUILD_JOBS), 0) # If the number of cores is less than 2, set the build jobs to 1.
   BUILD_JOBS := 1
@@ -193,17 +193,6 @@ clippy: ## Check clippy rules.
 fix-clippy: ## Fix clippy violations.
 	cargo clippy --workspace --all-targets --all-features --fix
 
-.PHONY: check-udeps
-check-udeps: ## Check unused dependencies.
-	cargo udeps --workspace --all-targets
-
-.PHONY: fix-udeps
-fix-udeps: ## Remove unused dependencies automatically.
-	@echo "Running cargo-udeps to find unused dependencies..."
-	@cargo udeps --workspace --all-targets --output json > udeps-report.json || true
-	@echo "Removing unused dependencies..."
-	@python3 scripts/fix-udeps.py udeps-report.json
-	
 .PHONY: fmt-check
 fmt-check: ## Check code format.
 	cargo fmt --all -- --check

config/config.md

@@ -41,7 +41,6 @@
 | `mysql.addr` | String | `127.0.0.1:4002` | The addr to bind the MySQL server. |
 | `mysql.runtime_size` | Integer | `2` | The number of server worker threads. |
 | `mysql.keep_alive` | String | `0s` | Server-side keep-alive time.<br/>Set to 0 (default) to disable. |
-| `mysql.prepared_stmt_cache_size` | Integer | `10000` | Maximum entries in the MySQL prepared statement cache; default is 10,000. |
 | `mysql.tls` | -- | -- | -- |
 | `mysql.tls.mode` | String | `disable` | TLS mode, refer to https://www.postgresql.org/docs/current/libpq-ssl.html<br/>- `disable` (default value)<br/>- `prefer`<br/>- `require`<br/>- `verify-ca`<br/>- `verify-full` |
 | `mysql.tls.cert_path` | String | Unset | Certificate file path. |
@@ -148,7 +147,7 @@
 | `region_engine.mito.write_cache_ttl` | String | Unset | TTL for write cache. |
 | `region_engine.mito.sst_write_buffer_size` | String | `8MB` | Buffer size for SST writing. |
 | `region_engine.mito.parallel_scan_channel_size` | Integer | `32` | Capacity of the channel to send data from parallel scan tasks to the main task. |
-| `region_engine.mito.max_concurrent_scan_files` | Integer | `384` | Maximum number of SST files to scan concurrently. |
+| `region_engine.mito.max_concurrent_scan_files` | Integer | `128` | Maximum number of SST files to scan concurrently. |
 | `region_engine.mito.allow_stale_entries` | Bool | `false` | Whether to allow stale WAL entries read during replay. |
 | `region_engine.mito.min_compaction_interval` | String | `0m` | Minimum time interval between two compactions.<br/>To align with the old behavior, the default value is 0 (no restrictions). |
 | `region_engine.mito.index` | -- | -- | The options for index in Mito engine. |
@@ -187,13 +186,12 @@
 | `logging.dir` | String | `./greptimedb_data/logs` | The directory to store the log files. If set to empty, logs will not be written to files. |
 | `logging.level` | String | Unset | The log level. Can be `info`/`debug`/`warn`/`error`. |
 | `logging.enable_otlp_tracing` | Bool | `false` | Enable OTLP tracing. |
-| `logging.otlp_endpoint` | String | `http://localhost:4318/v1/traces` | The OTLP tracing endpoint. |
+| `logging.otlp_endpoint` | String | `http://localhost:4318` | The OTLP tracing endpoint. |
 | `logging.append_stdout` | Bool | `true` | Whether to append logs to stdout. |
 | `logging.log_format` | String | `text` | The log format. Can be `text`/`json`. |
 | `logging.max_log_files` | Integer | `720` | The maximum amount of log files. |
 | `logging.otlp_export_protocol` | String | `http` | The OTLP tracing export protocol. Can be `grpc`/`http`. |
-| `logging.otlp_headers` | -- | -- | Additional OTLP headers, only valid when using OTLP http |
+| `logging.tracing_sample_ratio` | -- | -- | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
-| `logging.tracing_sample_ratio` | -- | Unset | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
 | `logging.tracing_sample_ratio.default_ratio` | Float | `1.0` | -- |
 | `slow_query` | -- | -- | The slow query log options. |
 | `slow_query.enable` | Bool | `false` | Whether to enable slow query log. |
@@ -245,22 +243,11 @@
 | `grpc.tls.cert_path` | String | Unset | Certificate file path. |
 | `grpc.tls.key_path` | String | Unset | Private key file path. |
 | `grpc.tls.watch` | Bool | `false` | Watch for Certificate and key file change and auto reload.<br/>For now, gRPC tls config does not support auto reload. |
-| `internal_grpc` | -- | -- | The internal gRPC server options. Internal gRPC port for nodes inside cluster to access frontend. |
-| `internal_grpc.bind_addr` | String | `127.0.0.1:4010` | The address to bind the gRPC server. |
-| `internal_grpc.server_addr` | String | `127.0.0.1:4010` | The address advertised to the metasrv, and used for connections from outside the host.<br/>If left empty or unset, the server will automatically use the IP address of the first network interface<br/>on the host, with the same port number as the one specified in `grpc.bind_addr`. |
-| `internal_grpc.runtime_size` | Integer | `8` | The number of server worker threads. |
-| `internal_grpc.flight_compression` | String | `arrow_ipc` | Compression mode for frontend side Arrow IPC service. Available options:<br/>- `none`: disable all compression<br/>- `transport`: only enable gRPC transport compression (zstd)<br/>- `arrow_ipc`: only enable Arrow IPC compression (lz4)<br/>- `all`: enable all compression.<br/>Default to `none` |
-| `internal_grpc.tls` | -- | -- | internal gRPC server TLS options, see `mysql.tls` section. |
-| `internal_grpc.tls.mode` | String | `disable` | TLS mode. |
-| `internal_grpc.tls.cert_path` | String | Unset | Certificate file path. |
-| `internal_grpc.tls.key_path` | String | Unset | Private key file path. |
-| `internal_grpc.tls.watch` | Bool | `false` | Watch for Certificate and key file change and auto reload.<br/>For now, gRPC tls config does not support auto reload. |
 | `mysql` | -- | -- | MySQL server options. |
 | `mysql.enable` | Bool | `true` | Whether to enable. |
 | `mysql.addr` | String | `127.0.0.1:4002` | The addr to bind the MySQL server. |
 | `mysql.runtime_size` | Integer | `2` | The number of server worker threads. |
 | `mysql.keep_alive` | String | `0s` | Server-side keep-alive time.<br/>Set to 0 (default) to disable. |
-| `mysql.prepared_stmt_cache_size` | Integer | `10000` | Maximum entries in the MySQL prepared statement cache; default is 10,000. |
 | `mysql.tls` | -- | -- | -- |
 | `mysql.tls.mode` | String | `disable` | TLS mode, refer to https://www.postgresql.org/docs/current/libpq-ssl.html<br/>- `disable` (default value)<br/>- `prefer`<br/>- `require`<br/>- `verify-ca`<br/>- `verify-full` |
 | `mysql.tls.cert_path` | String | Unset | Certificate file path. |
@@ -306,20 +293,19 @@
 | `logging.dir` | String | `./greptimedb_data/logs` | The directory to store the log files. If set to empty, logs will not be written to files. |
 | `logging.level` | String | Unset | The log level. Can be `info`/`debug`/`warn`/`error`. |
 | `logging.enable_otlp_tracing` | Bool | `false` | Enable OTLP tracing. |
-| `logging.otlp_endpoint` | String | `http://localhost:4318/v1/traces` | The OTLP tracing endpoint. |
+| `logging.otlp_endpoint` | String | `http://localhost:4318` | The OTLP tracing endpoint. |
 | `logging.append_stdout` | Bool | `true` | Whether to append logs to stdout. |
 | `logging.log_format` | String | `text` | The log format. Can be `text`/`json`. |
 | `logging.max_log_files` | Integer | `720` | The maximum amount of log files. |
 | `logging.otlp_export_protocol` | String | `http` | The OTLP tracing export protocol. Can be `grpc`/`http`. |
-| `logging.otlp_headers` | -- | -- | Additional OTLP headers, only valid when using OTLP http |
+| `logging.tracing_sample_ratio` | -- | -- | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
-| `logging.tracing_sample_ratio` | -- | Unset | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
 | `logging.tracing_sample_ratio.default_ratio` | Float | `1.0` | -- |
 | `slow_query` | -- | -- | The slow query log options. |
 | `slow_query.enable` | Bool | `true` | Whether to enable slow query log. |
 | `slow_query.record_type` | String | `system_table` | The record type of slow queries. It can be `system_table` or `log`.<br/>If `system_table` is selected, the slow queries will be recorded in a system table `greptime_private.slow_queries`.<br/>If `log` is selected, the slow queries will be logged in a log file `greptimedb-slow-queries.*`. |
 | `slow_query.threshold` | String | `30s` | The threshold of slow query. It can be human readable time string, for example: `10s`, `100ms`, `1s`. |
 | `slow_query.sample_ratio` | Float | `1.0` | The sampling ratio of slow query log. The value should be in the range of (0, 1]. For example, `0.1` means 10% of the slow queries will be logged and `1.0` means all slow queries will be logged. |
-| `slow_query.ttl` | String | `90d` | The TTL of the `slow_queries` system table. Default is `90d` when `record_type` is `system_table`. |
+| `slow_query.ttl` | String | `30d` | The TTL of the `slow_queries` system table. Default is `30d` when `record_type` is `system_table`. |
 | `export_metrics` | -- | -- | The frontend can export its metrics and send to Prometheus compatible service (e.g. `greptimedb` itself) from remote-write API.<br/>This is only used for `greptimedb` to export its own metrics internally. It's different from prometheus scrape. |
 | `export_metrics.enable` | Bool | `false` | whether enable export metrics. |
 | `export_metrics.write_interval` | String | `30s` | The interval of export metrics. |
@@ -330,8 +316,6 @@
 | `tracing.tokio_console_addr` | String | Unset | The tokio console address. |
 | `memory` | -- | -- | The memory options. |
 | `memory.enable_heap_profiling` | Bool | `true` | Whether to enable heap profiling activation during startup.<br/>When enabled, heap profiling will be activated if the `MALLOC_CONF` environment variable<br/>is set to "prof:true,prof_active:false". The official image adds this env variable.<br/>Default is true. |
-| `event_recorder` | -- | -- | Configuration options for the event recorder. |
-| `event_recorder.ttl` | String | `90d` | TTL for the events table that will be used to store the events. Default is `90d`. |
 
 
 ### Metasrv
@@ -343,7 +327,6 @@
 | `store_key_prefix` | String | `""` | If it's not empty, the metasrv will store all data with this key prefix. |
 | `backend` | String | `etcd_store` | The datastore for meta server.<br/>Available values:<br/>- `etcd_store` (default value)<br/>- `memory_store`<br/>- `postgres_store`<br/>- `mysql_store` |
 | `meta_table_name` | String | `greptime_metakv` | Table name in RDS to store metadata. Effect when using a RDS kvbackend.<br/>**Only used when backend is `postgres_store`.** |
-| `meta_schema_name` | String | `greptime_schema` | Optional PostgreSQL schema for metadata table and election table name qualification.<br/>When PostgreSQL public schema is not writable (e.g., PostgreSQL 15+ with restricted public),<br/>set this to a writable schema. GreptimeDB will use `meta_schema_name`.`meta_table_name`.<br/>GreptimeDB will NOT create the schema automatically; please ensure it exists or the user has permission.<br/>**Only used when backend is `postgres_store`.** |
 | `meta_election_lock_id` | Integer | `1` | Advisory lock id in PostgreSQL for election. Effect when using PostgreSQL as kvbackend<br/>Only used when backend is `postgres_store`. |
 | `selector` | String | `round_robin` | Datanode selector type.<br/>- `round_robin` (default value)<br/>- `lease_based`<br/>- `load_based`<br/>For details, please see "https://docs.greptime.com/developer-guide/metasrv/selector". |
 | `use_memory_store` | Bool | `false` | Store data in memory. |
@@ -355,7 +338,7 @@
 | `runtime` | -- | -- | The runtime options. |
 | `runtime.global_rt_size` | Integer | `8` | The number of threads to execute the runtime for global read operations. |
 | `runtime.compact_rt_size` | Integer | `4` | The number of threads to execute the runtime for global write operations. |
-| `backend_tls` | -- | -- | TLS configuration for kv store backend (applicable for etcd, PostgreSQL, and MySQL backends)<br/>When using etcd, PostgreSQL, or MySQL as metadata store, you can configure TLS here |
+| `backend_tls` | -- | -- | TLS configuration for kv store backend (only applicable for PostgreSQL/MySQL backends)<br/>When using PostgreSQL or MySQL as metadata store, you can configure TLS here |
 | `backend_tls.mode` | String | `prefer` | TLS mode, refer to https://www.postgresql.org/docs/current/libpq-ssl.html<br/>- "disable" - No TLS<br/>- "prefer" (default) - Try TLS, fallback to plain<br/>- "require" - Require TLS<br/>- "verify_ca" - Require TLS and verify CA<br/>- "verify_full" - Require TLS and verify hostname |
 | `backend_tls.cert_path` | String | `""` | Path to client certificate file (for client authentication)<br/>Like "/path/to/client.crt" |
 | `backend_tls.key_path` | String | `""` | Path to client private key file (for client authentication)<br/>Like "/path/to/client.key" |
@@ -388,33 +371,28 @@
 | `datanode.client.tcp_nodelay` | Bool | `true` | `TCP_NODELAY` option for accepted connections. |
 | `wal` | -- | -- | -- |
 | `wal.provider` | String | `raft_engine` | -- |
-| `wal.broker_endpoints` | Array | -- | The broker endpoints of the Kafka cluster.<br/><br/>**It's only used when the provider is `kafka`**. |
+| `wal.broker_endpoints` | Array | -- | The broker endpoints of the Kafka cluster. |
-| `wal.auto_create_topics` | Bool | `true` | Automatically create topics for WAL.<br/>Set to `true` to automatically create topics for WAL.<br/>Otherwise, use topics named `topic_name_prefix_[0..num_topics)`<br/>**It's only used when the provider is `kafka`**. |
+| `wal.auto_create_topics` | Bool | `true` | Automatically create topics for WAL.<br/>Set to `true` to automatically create topics for WAL.<br/>Otherwise, use topics named `topic_name_prefix_[0..num_topics)` |
-| `wal.auto_prune_interval` | String | `30m` | Interval of automatically WAL pruning.<br/>Set to `0s` to disable automatically WAL pruning which delete unused remote WAL entries periodically.<br/>**It's only used when the provider is `kafka`**. |
+| `wal.auto_prune_interval` | String | `0s` | Interval of automatically WAL pruning.<br/>Set to `0s` to disable automatically WAL pruning which delete unused remote WAL entries periodically. |
-| `wal.flush_trigger_size` | String | `512MB` | Estimated size threshold to trigger a flush when using Kafka remote WAL.<br/>Since multiple regions may share a Kafka topic, the estimated size is calculated as:<br/>  (latest_entry_id - flushed_entry_id) * avg_record_size<br/>MetaSrv triggers a flush for a region when this estimated size exceeds `flush_trigger_size`.<br/>- `latest_entry_id`: The latest entry ID in the topic.<br/>- `flushed_entry_id`: The last flushed entry ID for the region.<br/>Set to "0" to let the system decide the flush trigger size.<br/>**It's only used when the provider is `kafka`**. |
+| `wal.trigger_flush_threshold` | Integer | `0` | The threshold to trigger a flush operation of a region in automatically WAL pruning.<br/>Metasrv will send a flush request to flush the region when:<br/>`trigger_flush_threshold` + `prunable_entry_id` < `max_prunable_entry_id`<br/>where:<br/>- `prunable_entry_id` is the maximum entry id that can be pruned of the region.<br/>- `max_prunable_entry_id` is the maximum prunable entry id among all regions in the same topic.<br/>Set to `0` to disable the flush operation. |
-| `wal.checkpoint_trigger_size` | String | `128MB` | Estimated size threshold to trigger a checkpoint when using Kafka remote WAL.<br/>The estimated size is calculated as:<br/>  (latest_entry_id - last_checkpoint_entry_id) * avg_record_size<br/>MetaSrv triggers a checkpoint for a region when this estimated size exceeds `checkpoint_trigger_size`.<br/>Set to "0" to let the system decide the checkpoint trigger size.<br/>**It's only used when the provider is `kafka`**. |
+| `wal.auto_prune_parallelism` | Integer | `10` | Concurrent task limit for automatically WAL pruning. |
-| `wal.auto_prune_parallelism` | Integer | `10` | Concurrent task limit for automatically WAL pruning.<br/>**It's only used when the provider is `kafka`**. |
+| `wal.num_topics` | Integer | `64` | Number of topics. |
-| `wal.num_topics` | Integer | `64` | Number of topics used for remote WAL.<br/>**It's only used when the provider is `kafka`**. |
+| `wal.selector_type` | String | `round_robin` | Topic selector type.<br/>Available selector types:<br/>- `round_robin` (default) |
-| `wal.selector_type` | String | `round_robin` | Topic selector type.<br/>Available selector types:<br/>- `round_robin` (default)<br/>**It's only used when the provider is `kafka`**. |
+| `wal.topic_name_prefix` | String | `greptimedb_wal_topic` | A Kafka topic is constructed by concatenating `topic_name_prefix` and `topic_id`.<br/>Only accepts strings that match the following regular expression pattern:<br/>[a-zA-Z_:-][a-zA-Z0-9_:\-\.@#]*<br/>i.g., greptimedb_wal_topic_0, greptimedb_wal_topic_1. |
-| `wal.topic_name_prefix` | String | `greptimedb_wal_topic` | A Kafka topic is constructed by concatenating `topic_name_prefix` and `topic_id`.<br/>Only accepts strings that match the following regular expression pattern:<br/>[a-zA-Z_:-][a-zA-Z0-9_:\-\.@#]*<br/>i.g., greptimedb_wal_topic_0, greptimedb_wal_topic_1.<br/>**It's only used when the provider is `kafka`**. |
+| `wal.replication_factor` | Integer | `1` | Expected number of replicas of each partition. |
-| `wal.replication_factor` | Integer | `1` | Expected number of replicas of each partition.<br/>**It's only used when the provider is `kafka`**. |
+| `wal.create_topic_timeout` | String | `30s` | Above which a topic creation operation will be cancelled. |
-| `wal.create_topic_timeout` | String | `30s` | The timeout for creating a Kafka topic.<br/>**It's only used when the provider is `kafka`**. |
 | `event_recorder` | -- | -- | Configuration options for the event recorder. |
-| `event_recorder.ttl` | String | `90d` | TTL for the events table that will be used to store the events. Default is `90d`. |
+| `event_recorder.ttl` | String | `30d` | TTL for the events table that will be used to store the events. |
-| `stats_persistence` | -- | -- | Configuration options for the stats persistence. |
-| `stats_persistence.ttl` | String | `0s` | TTL for the stats table that will be used to store the stats.<br/>Set to `0s` to disable stats persistence.<br/>Default is `0s`.<br/>If you want to enable stats persistence, set the TTL to a value greater than 0.<br/>It is recommended to set a small value, e.g., `3h`. |
-| `stats_persistence.interval` | String | `10m` | The interval to persist the stats. Default is `10m`.<br/>The minimum value is `10m`, if the value is less than `10m`, it will be overridden to `10m`. |
 | `logging` | -- | -- | The logging options. |
 | `logging.dir` | String | `./greptimedb_data/logs` | The directory to store the log files. If set to empty, logs will not be written to files. |
 | `logging.level` | String | Unset | The log level. Can be `info`/`debug`/`warn`/`error`. |
 | `logging.enable_otlp_tracing` | Bool | `false` | Enable OTLP tracing. |
-| `logging.otlp_endpoint` | String | `http://localhost:4318/v1/traces` | The OTLP tracing endpoint. |
+| `logging.otlp_endpoint` | String | `http://localhost:4318` | The OTLP tracing endpoint. |
 | `logging.append_stdout` | Bool | `true` | Whether to append logs to stdout. |
 | `logging.log_format` | String | `text` | The log format. Can be `text`/`json`. |
 | `logging.max_log_files` | Integer | `720` | The maximum amount of log files. |
 | `logging.otlp_export_protocol` | String | `http` | The OTLP tracing export protocol. Can be `grpc`/`http`. |
-| `logging.otlp_headers` | -- | -- | Additional OTLP headers, only valid when using OTLP http |
+| `logging.tracing_sample_ratio` | -- | -- | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
-| `logging.tracing_sample_ratio` | -- | Unset | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
 | `logging.tracing_sample_ratio.default_ratio` | Float | `1.0` | -- |
 | `export_metrics` | -- | -- | The metasrv can export its metrics and send to Prometheus compatible service (e.g. `greptimedb` itself) from remote-write API.<br/>This is only used for `greptimedb` to export its own metrics internally. It's different from prometheus scrape. |
 | `export_metrics.enable` | Bool | `false` | whether enable export metrics. |
@@ -521,8 +499,6 @@
 | `region_engine.mito.worker_channel_size` | Integer | `128` | Request channel size of each worker. |
 | `region_engine.mito.worker_request_batch_size` | Integer | `64` | Max batch size for a worker to handle requests. |
 | `region_engine.mito.manifest_checkpoint_distance` | Integer | `10` | Number of meta action updated to trigger a new checkpoint for the manifest. |
-| `region_engine.mito.experimental_manifest_keep_removed_file_count` | Integer | `256` | Number of removed files to keep in manifest's `removed_files` field before also<br/>remove them from `removed_files`. Mostly for debugging purpose.<br/>If set to 0, it will only use `keep_removed_file_ttl` to decide when to remove files<br/>from `removed_files` field. |
-| `region_engine.mito.experimental_manifest_keep_removed_file_ttl` | String | `1h` | How long to keep removed files in the `removed_files` field of manifest<br/>after they are removed from manifest.<br/>files will only be removed from `removed_files` field<br/>if both `keep_removed_file_count` and `keep_removed_file_ttl` is reached. |
 | `region_engine.mito.compress_manifest` | Bool | `false` | Whether to compress manifest and checkpoint file by gzip (default false). |
 | `region_engine.mito.max_background_flushes` | Integer | Auto | Max number of running background flush jobs (default: 1/2 of cpu cores). |
 | `region_engine.mito.max_background_compactions` | Integer | Auto | Max number of running background compaction jobs (default: 1/4 of cpu cores). |
@@ -540,7 +516,7 @@
 | `region_engine.mito.write_cache_ttl` | String | Unset | TTL for write cache. |
 | `region_engine.mito.sst_write_buffer_size` | String | `8MB` | Buffer size for SST writing. |
 | `region_engine.mito.parallel_scan_channel_size` | Integer | `32` | Capacity of the channel to send data from parallel scan tasks to the main task. |
-| `region_engine.mito.max_concurrent_scan_files` | Integer | `384` | Maximum number of SST files to scan concurrently. |
+| `region_engine.mito.max_concurrent_scan_files` | Integer | `128` | Maximum number of SST files to scan concurrently. |
 | `region_engine.mito.allow_stale_entries` | Bool | `false` | Whether to allow stale WAL entries read during replay. |
 | `region_engine.mito.min_compaction_interval` | String | `0m` | Minimum time interval between two compactions.<br/>To align with the old behavior, the default value is 0 (no restrictions). |
 | `region_engine.mito.index` | -- | -- | The options for index in Mito engine. |
@@ -579,13 +555,12 @@
 | `logging.dir` | String | `./greptimedb_data/logs` | The directory to store the log files. If set to empty, logs will not be written to files. |
 | `logging.level` | String | Unset | The log level. Can be `info`/`debug`/`warn`/`error`. |
 | `logging.enable_otlp_tracing` | Bool | `false` | Enable OTLP tracing. |
-| `logging.otlp_endpoint` | String | `http://localhost:4318/v1/traces` | The OTLP tracing endpoint. |
+| `logging.otlp_endpoint` | String | `http://localhost:4318` | The OTLP tracing endpoint. |
 | `logging.append_stdout` | Bool | `true` | Whether to append logs to stdout. |
 | `logging.log_format` | String | `text` | The log format. Can be `text`/`json`. |
 | `logging.max_log_files` | Integer | `720` | The maximum amount of log files. |
 | `logging.otlp_export_protocol` | String | `http` | The OTLP tracing export protocol. Can be `grpc`/`http`. |
-| `logging.otlp_headers` | -- | -- | Additional OTLP headers, only valid when using OTLP http |
+| `logging.tracing_sample_ratio` | -- | -- | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
-| `logging.tracing_sample_ratio` | -- | Unset | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
 | `logging.tracing_sample_ratio.default_ratio` | Float | `1.0` | -- |
 | `export_metrics` | -- | -- | The datanode can export its metrics and send to Prometheus compatible service (e.g. `greptimedb` itself) from remote-write API.<br/>This is only used for `greptimedb` to export its own metrics internally. It's different from prometheus scrape. |
 | `export_metrics.enable` | Bool | `false` | whether enable export metrics. |
@@ -616,12 +591,6 @@
 | `flow.batching_mode.experimental_frontend_activity_timeout` | String | `60s` | Frontend activity timeout<br/>if frontend is down(not sending heartbeat) for more than frontend_activity_timeout,<br/>it will be removed from the list that flownode use to connect |
 | `flow.batching_mode.experimental_max_filter_num_per_query` | Integer | `20` | Maximum number of filters allowed in a single query |
 | `flow.batching_mode.experimental_time_window_merge_threshold` | Integer | `3` | Time window merge distance |
-| `flow.batching_mode.read_preference` | String | `Leader` | Read preference of the Frontend client. |
-| `flow.batching_mode.frontend_tls` | -- | -- | -- |
-| `flow.batching_mode.frontend_tls.enabled` | Bool | `false` | Whether to enable TLS for client. |
-| `flow.batching_mode.frontend_tls.server_ca_cert_path` | String | Unset | Server Certificate file path. |
-| `flow.batching_mode.frontend_tls.client_cert_path` | String | Unset | Client Certificate file path. |
-| `flow.batching_mode.frontend_tls.client_key_path` | String | Unset | Client Private key file path. |
 | `grpc` | -- | -- | The gRPC server options. |
 | `grpc.bind_addr` | String | `127.0.0.1:6800` | The address to bind the gRPC server. |
 | `grpc.server_addr` | String | `127.0.0.1:6800` | The address advertised to the metasrv,<br/>and used for connections from outside the host |
@@ -649,13 +618,12 @@
 | `logging.dir` | String | `./greptimedb_data/logs` | The directory to store the log files. If set to empty, logs will not be written to files. |
 | `logging.level` | String | Unset | The log level. Can be `info`/`debug`/`warn`/`error`. |
 | `logging.enable_otlp_tracing` | Bool | `false` | Enable OTLP tracing. |
-| `logging.otlp_endpoint` | String | `http://localhost:4318/v1/traces` | The OTLP tracing endpoint. |
+| `logging.otlp_endpoint` | String | `http://localhost:4318` | The OTLP tracing endpoint. |
 | `logging.append_stdout` | Bool | `true` | Whether to append logs to stdout. |
 | `logging.log_format` | String | `text` | The log format. Can be `text`/`json`. |
 | `logging.max_log_files` | Integer | `720` | The maximum amount of log files. |
 | `logging.otlp_export_protocol` | String | `http` | The OTLP tracing export protocol. Can be `grpc`/`http`. |
-| `logging.otlp_headers` | -- | -- | Additional OTLP headers, only valid when using OTLP http |
+| `logging.tracing_sample_ratio` | -- | -- | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
-| `logging.tracing_sample_ratio` | -- | Unset | The percentage of tracing will be sampled and exported.<br/>Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.<br/>ratio > 1 are treated as 1. Fractions < 0 are treated as 0 |
 | `logging.tracing_sample_ratio.default_ratio` | Float | `1.0` | -- |
 | `tracing` | -- | -- | The tracing options. Only effect when compiled with `tokio-console` feature. |
 | `tracing.tokio_console_addr` | String | Unset | The tokio console address. |

config/datanode.example.toml

@@ -409,19 +409,6 @@ worker_request_batch_size = 64
 ## Number of meta action updated to trigger a new checkpoint for the manifest.
 manifest_checkpoint_distance = 10
 
-
-## Number of removed files to keep in manifest's `removed_files` field before also
-## remove them from `removed_files`. Mostly for debugging purpose.
-## If set to 0, it will only use `keep_removed_file_ttl` to decide when to remove files
-## from `removed_files` field.
-experimental_manifest_keep_removed_file_count = 256
-
-## How long to keep removed files in the `removed_files` field of manifest
-## after they are removed from manifest.
-## files will only be removed from `removed_files` field
-## if both `keep_removed_file_count` and `keep_removed_file_ttl` is reached.
-experimental_manifest_keep_removed_file_ttl = "1h"
-
 ## Whether to compress manifest and checkpoint file by gzip (default false).
 compress_manifest = false
 
@@ -488,7 +475,7 @@ sst_write_buffer_size = "8MB"
 parallel_scan_channel_size = 32
 
 ## Maximum number of SST files to scan concurrently.
-max_concurrent_scan_files = 384
+max_concurrent_scan_files = 128
 
 ## Whether to allow stale WAL entries read during replay.
 allow_stale_entries = false
@@ -645,7 +632,7 @@ level = "info"
 enable_otlp_tracing = false
 
 ## The OTLP tracing endpoint.
-otlp_endpoint = "http://localhost:4318/v1/traces"
+otlp_endpoint = "http://localhost:4318"
 
 ## Whether to append logs to stdout.
 append_stdout = true
@@ -659,13 +646,6 @@ max_log_files = 720
 ## The OTLP tracing export protocol. Can be `grpc`/`http`.
 otlp_export_protocol = "http"
 
-## Additional OTLP headers, only valid when using OTLP http
-[logging.otlp_headers]
-## @toml2docs:none-default
-#Authorization = "Bearer my-token"
-## @toml2docs:none-default
-#Database = "My database"
-
 ## The percentage of tracing will be sampled and exported.
 ## Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.
 ## ratio > 1 are treated as 1. Fractions < 0 are treated as 0

config/flownode.example.toml

@@ -30,20 +30,6 @@ node_id = 14
 #+experimental_max_filter_num_per_query=20
 ## Time window merge distance
 #+experimental_time_window_merge_threshold=3
-## Read preference of the Frontend client.
-#+read_preference="Leader"
-[flow.batching_mode.frontend_tls]
-## Whether to enable TLS for client.
-#+enabled=false
-## Server Certificate file path.
-## @toml2docs:none-default
-#+server_ca_cert_path=""
-## Client Certificate file path.
-## @toml2docs:none-default
-#+client_cert_path=""
-## Client Private key file path.
-## @toml2docs:none-default
-#+client_key_path=""
 
 ## The gRPC server options.
 [grpc]
@@ -120,7 +106,7 @@ level = "info"
 enable_otlp_tracing = false
 
 ## The OTLP tracing endpoint.
-otlp_endpoint = "http://localhost:4318/v1/traces"
+otlp_endpoint = "http://localhost:4318"
 
 ## Whether to append logs to stdout.
 append_stdout = true
@@ -134,13 +120,6 @@ max_log_files = 720
 ## The OTLP tracing export protocol. Can be `grpc`/`http`.
 otlp_export_protocol = "http"
 
-## Additional OTLP headers, only valid when using OTLP http
-[logging.otlp_headers]
-## @toml2docs:none-default
-#Authorization = "Bearer my-token"
-## @toml2docs:none-default
-#Database = "My database"
-
 ## The percentage of tracing will be sampled and exported.
 ## Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.
 ## ratio > 1 are treated as 1. Fractions < 0 are treated as 0

config/frontend.example.toml

@@ -79,42 +79,6 @@ key_path = ""
 ## For now, gRPC tls config does not support auto reload.
 watch = false
 
-## The internal gRPC server options. Internal gRPC port for nodes inside cluster to access frontend.
-[internal_grpc]
-## The address to bind the gRPC server.
-bind_addr = "127.0.0.1:4010"
-## The address advertised to the metasrv, and used for connections from outside the host.
-## If left empty or unset, the server will automatically use the IP address of the first network interface
-## on the host, with the same port number as the one specified in `grpc.bind_addr`.
-server_addr = "127.0.0.1:4010"
-## The number of server worker threads.
-runtime_size = 8
-## Compression mode for frontend side Arrow IPC service. Available options:
-## - `none`: disable all compression
-## - `transport`: only enable gRPC transport compression (zstd)
-## - `arrow_ipc`: only enable Arrow IPC compression (lz4)
-## - `all`: enable all compression.
-## Default to `none`
-flight_compression = "arrow_ipc"
-
-## internal gRPC server TLS options, see `mysql.tls` section.
-[internal_grpc.tls]
-## TLS mode.
-mode = "disable"
-
-## Certificate file path.
-## @toml2docs:none-default
-cert_path = ""
-
-## Private key file path.
-## @toml2docs:none-default
-key_path = ""
-
-## Watch for Certificate and key file change and auto reload.
-## For now, gRPC tls config does not support auto reload.
-watch = false
-
-
 ## MySQL server options.
 [mysql]
 ## Whether to enable.
@@ -126,8 +90,6 @@ runtime_size = 2
 ## Server-side keep-alive time.
 ## Set to 0 (default) to disable.
 keep_alive = "0s"
-## Maximum entries in the MySQL prepared statement cache; default is 10,000.
-prepared_stmt_cache_size = 10000
 
 # MySQL server TLS options.
 [mysql.tls]
@@ -259,7 +221,7 @@ level = "info"
 enable_otlp_tracing = false
 
 ## The OTLP tracing endpoint.
-otlp_endpoint = "http://localhost:4318/v1/traces"
+otlp_endpoint = "http://localhost:4318"
 
 ## Whether to append logs to stdout.
 append_stdout = true
@@ -273,13 +235,6 @@ max_log_files = 720
 ## The OTLP tracing export protocol. Can be `grpc`/`http`.
 otlp_export_protocol = "http"
 
-## Additional OTLP headers, only valid when using OTLP http
-[logging.otlp_headers]
-## @toml2docs:none-default
-#Authorization = "Bearer my-token"
-## @toml2docs:none-default
-#Database = "My database"
-
 ## The percentage of tracing will be sampled and exported.
 ## Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.
 ## ratio > 1 are treated as 1. Fractions < 0 are treated as 0
@@ -302,8 +257,8 @@ threshold = "30s"
 ## The sampling ratio of slow query log. The value should be in the range of (0, 1]. For example, `0.1` means 10% of the slow queries will be logged and `1.0` means all slow queries will be logged.
 sample_ratio = 1.0
 
-## The TTL of the `slow_queries` system table. Default is `90d` when `record_type` is `system_table`.
+## The TTL of the `slow_queries` system table. Default is `30d` when `record_type` is `system_table`.
-ttl = "90d"
+ttl = "30d"
 
 ## The frontend can export its metrics and send to Prometheus compatible service (e.g. `greptimedb` itself) from remote-write API.
 ## This is only used for `greptimedb` to export its own metrics internally. It's different from prometheus scrape.
@@ -333,8 +288,3 @@ headers = { }
 ## is set to "prof:true,prof_active:false". The official image adds this env variable.
 ## Default is true.
 enable_heap_profiling = true
-
-## Configuration options for the event recorder.
-[event_recorder]
-## TTL for the events table that will be used to store the events. Default is `90d`.
-ttl = "90d"

config/metasrv.example.toml

@@ -23,14 +23,6 @@ backend = "etcd_store"
 ## **Only used when backend is `postgres_store`.**
 meta_table_name = "greptime_metakv"
 
-## Optional PostgreSQL schema for metadata table and election table name qualification.
-## When PostgreSQL public schema is not writable (e.g., PostgreSQL 15+ with restricted public),
-## set this to a writable schema. GreptimeDB will use `meta_schema_name`.`meta_table_name`.
-## GreptimeDB will NOT create the schema automatically; please ensure it exists or the user has permission.
-## **Only used when backend is `postgres_store`.**
-
-meta_schema_name = "greptime_schema"
-
 ## Advisory lock id in PostgreSQL for election. Effect when using PostgreSQL as kvbackend
 ## Only used when backend is `postgres_store`.
 meta_election_lock_id = 1
@@ -73,8 +65,8 @@ node_max_idle_time = "24hours"
 ## The number of threads to execute the runtime for global write operations.
 #+ compact_rt_size = 4
 
-## TLS configuration for kv store backend (applicable for etcd, PostgreSQL, and MySQL backends)
+## TLS configuration for kv store backend (only applicable for PostgreSQL/MySQL backends)
-## When using etcd, PostgreSQL, or MySQL as metadata store, you can configure TLS here
+## When using PostgreSQL or MySQL as metadata store, you can configure TLS here
 [backend_tls]
 ## TLS mode, refer to https://www.postgresql.org/docs/current/libpq-ssl.html
 ## - "disable" - No TLS
@@ -184,69 +176,50 @@ tcp_nodelay = true
 # - `kafka`: metasrv **have to be** configured with kafka wal config when using kafka wal provider in datanode.
 provider = "raft_engine"
 
+# Kafka wal config.
+
 ## The broker endpoints of the Kafka cluster.
-##
-## **It's only used when the provider is `kafka`**.
 broker_endpoints = ["127.0.0.1:9092"]
 
 ## Automatically create topics for WAL.
 ## Set to `true` to automatically create topics for WAL.
 ## Otherwise, use topics named `topic_name_prefix_[0..num_topics)`
-## **It's only used when the provider is `kafka`**.
 auto_create_topics = true
 
 ## Interval of automatically WAL pruning.
 ## Set to `0s` to disable automatically WAL pruning which delete unused remote WAL entries periodically.
-## **It's only used when the provider is `kafka`**.
+auto_prune_interval = "0s"
-auto_prune_interval = "30m"
 
-
+## The threshold to trigger a flush operation of a region in automatically WAL pruning.
-## Estimated size threshold to trigger a flush when using Kafka remote WAL.
+## Metasrv will send a flush request to flush the region when:
-## Since multiple regions may share a Kafka topic, the estimated size is calculated as:
+## `trigger_flush_threshold` + `prunable_entry_id` < `max_prunable_entry_id`
-##   (latest_entry_id - flushed_entry_id) * avg_record_size
+## where:
-## MetaSrv triggers a flush for a region when this estimated size exceeds `flush_trigger_size`.
+## - `prunable_entry_id` is the maximum entry id that can be pruned of the region.
-## - `latest_entry_id`: The latest entry ID in the topic.
+## - `max_prunable_entry_id` is the maximum prunable entry id among all regions in the same topic.
-## - `flushed_entry_id`: The last flushed entry ID for the region.
+## Set to `0` to disable the flush operation.
-## Set to "0" to let the system decide the flush trigger size.
+trigger_flush_threshold = 0
-## **It's only used when the provider is `kafka`**.
-flush_trigger_size = "512MB"
-
-## Estimated size threshold to trigger a checkpoint when using Kafka remote WAL.
-## The estimated size is calculated as:
-##   (latest_entry_id - last_checkpoint_entry_id) * avg_record_size
-## MetaSrv triggers a checkpoint for a region when this estimated size exceeds `checkpoint_trigger_size`.
-## Set to "0" to let the system decide the checkpoint trigger size.
-## **It's only used when the provider is `kafka`**.
-checkpoint_trigger_size = "128MB"
 
 ## Concurrent task limit for automatically WAL pruning.
-## **It's only used when the provider is `kafka`**.
 auto_prune_parallelism = 10
 
-## Number of topics used for remote WAL.
+## Number of topics.
-## **It's only used when the provider is `kafka`**.
 num_topics = 64
 
 ## Topic selector type.
 ## Available selector types:
 ## - `round_robin` (default)
-## **It's only used when the provider is `kafka`**.
 selector_type = "round_robin"
 
-
 ## A Kafka topic is constructed by concatenating `topic_name_prefix` and `topic_id`.
 ## Only accepts strings that match the following regular expression pattern:
 ## [a-zA-Z_:-][a-zA-Z0-9_:\-\.@#]*
 ## i.g., greptimedb_wal_topic_0, greptimedb_wal_topic_1.
-## **It's only used when the provider is `kafka`**.
 topic_name_prefix = "greptimedb_wal_topic"
 
 ## Expected number of replicas of each partition.
-## **It's only used when the provider is `kafka`**.
 replication_factor = 1
 
-## The timeout for creating a Kafka topic.
+## Above which a topic creation operation will be cancelled.
-## **It's only used when the provider is `kafka`**.
 create_topic_timeout = "30s"
 
 # The Kafka SASL configuration.
@@ -269,20 +242,8 @@ create_topic_timeout = "30s"
 
 ## Configuration options for the event recorder.
 [event_recorder]
-## TTL for the events table that will be used to store the events. Default is `90d`.
+## TTL for the events table that will be used to store the events.
-ttl = "90d"
+ttl = "30d"
-
-## Configuration options for the stats persistence.
-[stats_persistence]
-## TTL for the stats table that will be used to store the stats.
-## Set to `0s` to disable stats persistence.
-## Default is `0s`.
-## If you want to enable stats persistence, set the TTL to a value greater than 0.
-## It is recommended to set a small value, e.g., `3h`.
-ttl = "0s"
-## The interval to persist the stats. Default is `10m`.
-## The minimum value is `10m`, if the value is less than `10m`, it will be overridden to `10m`.
-interval = "10m"
 
 ## The logging options.
 [logging]
@@ -297,7 +258,7 @@ level = "info"
 enable_otlp_tracing = false
 
 ## The OTLP tracing endpoint.
-otlp_endpoint = "http://localhost:4318/v1/traces"
+otlp_endpoint = "http://localhost:4318"
 
 ## Whether to append logs to stdout.
 append_stdout = true
@@ -311,14 +272,6 @@ max_log_files = 720
 ## The OTLP tracing export protocol. Can be `grpc`/`http`.
 otlp_export_protocol = "http"
 
-## Additional OTLP headers, only valid when using OTLP http
-[logging.otlp_headers]
-## @toml2docs:none-default
-#Authorization = "Bearer my-token"
-## @toml2docs:none-default
-#Database = "My database"
-
-
 ## The percentage of tracing will be sampled and exported.
 ## Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.
 ## ratio > 1 are treated as 1. Fractions < 0 are treated as 0

config/standalone.example.toml

@@ -85,8 +85,7 @@ runtime_size = 2
 ## Server-side keep-alive time.
 ## Set to 0 (default) to disable.
 keep_alive = "0s"
-## Maximum entries in the MySQL prepared statement cache; default is 10,000.
+
-prepared_stmt_cache_size= 10000
 # MySQL server TLS options.
 [mysql.tls]
 
@@ -567,7 +566,7 @@ sst_write_buffer_size = "8MB"
 parallel_scan_channel_size = 32
 
 ## Maximum number of SST files to scan concurrently.
-max_concurrent_scan_files = 384
+max_concurrent_scan_files = 128
 
 ## Whether to allow stale WAL entries read during replay.
 allow_stale_entries = false
@@ -724,7 +723,7 @@ level = "info"
 enable_otlp_tracing = false
 
 ## The OTLP tracing endpoint.
-otlp_endpoint = "http://localhost:4318/v1/traces"
+otlp_endpoint = "http://localhost:4318"
 
 ## Whether to append logs to stdout.
 append_stdout = true
@@ -738,13 +737,6 @@ max_log_files = 720
 ## The OTLP tracing export protocol. Can be `grpc`/`http`.
 otlp_export_protocol = "http"
 
-## Additional OTLP headers, only valid when using OTLP http
-[logging.otlp_headers]
-## @toml2docs:none-default
-#Authorization = "Bearer my-token"
-## @toml2docs:none-default
-#Database = "My database"
-
 ## The percentage of tracing will be sampled and exported.
 ## Valid range `[0, 1]`, 1 means all traces are sampled, 0 means all traces are not sampled, the default value is 1.
 ## ratio > 1 are treated as 1. Fractions < 0 are treated as 0

docker/dev-builder/android/Dockerfile

@@ -13,8 +13,7 @@ RUN apt-get update && apt-get install -y \
     git \
     unzip \
     build-essential \
-    pkg-config \
+    pkg-config
-    openssh-client
 
 # Install protoc
 ARG PROTOBUF_VERSION=29.3

docker/dev-builder/centos/Dockerfile

@@ -19,7 +19,7 @@ ARG PROTOBUF_VERSION=29.3
 
 RUN curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v${PROTOBUF_VERSION}/protoc-${PROTOBUF_VERSION}-linux-x86_64.zip && \
     unzip protoc-${PROTOBUF_VERSION}-linux-x86_64.zip -d protoc3;
-
+    
 RUN mv protoc3/bin/* /usr/local/bin/
 RUN mv protoc3/include/* /usr/local/include/
 

docker/docker-compose/cluster-with-etcd.yaml

@@ -34,48 +34,6 @@ services:
     networks:
       - greptimedb
 
-  etcd-tls:
-    <<: *etcd_common_settings
-    container_name: etcd-tls
-    ports:
-      - 2378:2378
-      - 2381:2381
-    command:
-      - --name=etcd-tls
-      - --data-dir=/var/lib/etcd
-      - --initial-advertise-peer-urls=https://etcd-tls:2381
-      - --listen-peer-urls=https://0.0.0.0:2381
-      - --listen-client-urls=https://0.0.0.0:2378
-      - --advertise-client-urls=https://etcd-tls:2378
-      - --heartbeat-interval=250
-      - --election-timeout=1250
-      - --initial-cluster=etcd-tls=https://etcd-tls:2381
-      - --initial-cluster-state=new
-      - --initial-cluster-token=etcd-tls-cluster
-      - --cert-file=/certs/server.crt
-      - --key-file=/certs/server-key.pem
-      - --peer-cert-file=/certs/server.crt
-      - --peer-key-file=/certs/server-key.pem
-      - --trusted-ca-file=/certs/ca.crt
-      - --peer-trusted-ca-file=/certs/ca.crt
-      - --client-cert-auth
-      - --peer-client-cert-auth
-    volumes:
-      - ./greptimedb-cluster-docker-compose/etcd-tls:/var/lib/etcd
-      - ./greptimedb-cluster-docker-compose/certs:/certs:ro
-    environment:
-      - ETCDCTL_API=3
-      - ETCDCTL_CACERT=/certs/ca.crt
-      - ETCDCTL_CERT=/certs/server.crt
-      - ETCDCTL_KEY=/certs/server-key.pem
-    healthcheck:
-      test: [ "CMD", "etcdctl", "--endpoints=https://etcd-tls:2378", "--cacert=/certs/ca.crt", "--cert=/certs/server.crt", "--key=/certs/server-key.pem", "endpoint", "health" ]
-      interval: 10s
-      timeout: 5s
-      retries: 5
-    networks:
-      - greptimedb
-
   metasrv:
     image: *greptimedb_image
     container_name: metasrv

docs/how-to/how-to-write-aggregate-function.md

@@ -0,0 +1,72 @@
+Currently, our query engine is based on DataFusion, so all aggregate function is executed by DataFusion, through its UDAF interface. You can find DataFusion's UDAF example [here](https://github.com/apache/datafusion/tree/main/datafusion-examples/examples/simple_udaf.rs). Basically, we provide the same way as DataFusion to write aggregate functions: both are centered in a struct called "Accumulator" to accumulates states along the way in aggregation.
+
+However, DataFusion's UDAF implementation has a huge restriction, that it requires user to provide a concrete "Accumulator". Take `Median` aggregate function for example, to aggregate a `u32` datatype column, you have to write a `MedianU32`, and use `SELECT MEDIANU32(x)` in SQL. `MedianU32` cannot be used to aggregate a `i32` datatype column. Or, there's another way: you can use a special type that can hold all kinds of data (like our `Value` enum or Arrow's `ScalarValue`), and `match` all the way up to do aggregate calculations. It might work, though rather tedious. (But I think it's DataFusion's preferred way to write UDAF.)
+
+So is there a way we can make an aggregate function that automatically match the input data's type? For example, a `Median` aggregator that can work on both `u32` column and `i32`? The answer is yes until we find a way to bypass DataFusion's restriction, a restriction that DataFusion simply doesn't pass the input data's type when creating an Accumulator.
+
+> There's an example in `my_sum_udaf_example.rs`, take that as quick start.
+
+# 1. Impl `AggregateFunctionCreator` trait for your accumulator creator.
+
+You must first define a struct that will be used to create your accumulator. For example,
+
+```Rust
+#[as_aggr_func_creator]
+#[derive(Debug, AggrFuncTypeStore)]
+struct MySumAccumulatorCreator {}
+```
+
+Attribute macro `#[as_aggr_func_creator]` and derive macro `#[derive(Debug, AggrFuncTypeStore)]` must both be annotated on the struct. They work together to provide a storage of aggregate function's input data types, which are needed for creating generic accumulator later.  
+
+> Note that the `as_aggr_func_creator` macro will add fields to the struct, so the struct cannot be defined as an empty struct without field like `struct Foo;`, neither as a new type like `struct Foo(bar)`.
+
+Then impl `AggregateFunctionCreator` trait on it. The definition of the trait is:
+
+```Rust
+pub trait AggregateFunctionCreator: Send + Sync + Debug {
+    fn creator(&self) -> AccumulatorCreatorFunction;
+    fn output_type(&self) -> ConcreteDataType;
+    fn state_types(&self) -> Vec<ConcreteDataType>;
+}
+```
+
+You can use input data's type in methods that return output type and state types (just invoke `input_types()`).
+
+The output type is aggregate function's output data's type. For example, `SUM` aggregate function's output type is `u64` for a `u32` datatype column. The state types are accumulator's internal states' types. Take `AVG` aggregate function on a `i32` column as example, its state types are `i64` (for sum) and `u64` (for count).
+
+The `creator` function is where you define how an accumulator (that will be used in DataFusion) is created. You define "how" to create the accumulator (instead of "what" to create), using the input data's type as arguments. With input datatype known, you can create accumulator generically.
+
+# 2. Impl `Accumulator` trait for your accumulator.
+
+The accumulator is where you store the aggregate calculation states and evaluate a result. You must impl `Accumulator` trait for it. The trait's definition is:
+
+```Rust
+pub trait Accumulator: Send + Sync + Debug {
+    fn state(&self) -> Result<Vec<Value>>;
+    fn update_batch(&mut self, values: &[VectorRef]) -> Result<()>;
+    fn merge_batch(&mut self, states: &[VectorRef]) -> Result<()>;
+    fn evaluate(&self) -> Result<Value>;
+}
+```
+
+The DataFusion basically executes aggregate like this:
+
+1. Partitioning all input data for aggregate. Create an accumulator for each part.
+2. Call `update_batch` on each accumulator with partitioned data, to let you update your aggregate calculation.
+3. Call `state` to get each accumulator's internal state, the medial calculation result.
+4. Call `merge_batch` to merge all accumulator's internal state to one.
+5. Execute `evaluate` on the chosen one to get the final calculation result.
+
+Once you know the meaning of each method, you can easily write your accumulator. You can refer to `Median` accumulator or `SUM` accumulator defined in file `my_sum_udaf_example.rs` for more details.
+
+# 3. Register your aggregate function to our query engine.
+
+You can call `register_aggregate_function` method in query engine to register your aggregate function. To do that, you have to new an instance of struct `AggregateFunctionMeta`. The struct has three fields, first is the name of your aggregate function's name. The function name is case-sensitive due to DataFusion's restriction. We strongly recommend using lowercase for your name. If you have to use uppercase name, wrap your aggregate function with quotation marks. For example, if you define an aggregate function named "my_aggr", you can use "`SELECT MY_AGGR(x)`"; if you define "my_AGGR", you have to use "`SELECT "my_AGGR"(x)`".
+
+The second field is arg_counts ,the count of the arguments. Like accumulator `percentile`, calculating the p_number of the column. We need to input the value of column and the value of p to calculate, and so the count of the arguments is two.
+
+The third field is a function about how to create your accumulator creator that you defined in step 1 above. Create creator, that's a bit intertwined, but it is how we make DataFusion use a newly created aggregate function each time it executes a SQL, preventing the stored input types from affecting each other. The key detail can be starting looking at our `DfContextProviderAdapter` struct's `get_aggregate_meta` method.
+
+# (Optional) 4. Make your aggregate function automatically registered.
+
+If you've written a great aggregate function that wants to let everyone use it, you can make it automatically register to our query engine at start time. It's quick and simple, just refer to the `AggregateFunctions::register` function in `common/function/src/scalars/aggregate/mod.rs`.

docs/rfcs/2025-08-16-async-index-build.md

@@ -1,112 +0,0 @@
----
-Feature Name: Async Index Build
-Tracking Issue: https://github.com/GreptimeTeam/greptimedb/issues/6756
-Date: 2025-08-16
-Author: "SNC123 <sinhco@outlook.com>"
----
-
-# Summary
-This RFC proposes an asynchronous index build mechanism in the database, with a configuration option to choose between synchronous and asynchronous modes, aiming to improve flexibility and adapt to different workload requirements.
-
-# Motivation
-Currently, index creation is performed synchronously, which may lead to prolonged write suspension and impact business continuity. As data volume grows, the time required for index building increases significantly. An asynchronous solution is urgently needed to enhance user experience and system throughput.
-
-# Details
-
-## Overview
-
-The following table highlights the difference between async and sync index approach:
-
-| Approach | Trigger | Data Source | Additional Index Metadata Installation | Fine-grained `FileMeta` Index |
-| :--- | :--- | :--- | :--- | :--- |
-| Sync Index | On `write_sst` | Memory (on flush) / Disk (on compact) | Not required(already installed synchronously) | Not required |
-| Async Index | 4 trigger types | Disk | Required | Required |
-
-The index build mode (synchronous or asynchronous) can be selected via configuration file. 
-
-### Four Trigger Types
-
-This RFC introduces four `IndexBuildType`s to trigger index building:
-
-- **Manual Rebuild**: Triggered by the user via `ADMIN build_index("table_name")`, for scenarios like recovering from failed builds or migrating data. SST files whose `ColumnIndexMetadata` (see below) is already consistent with the `RegionMetadata` will be skipped.
-- **Schema Change**: Automatically triggered when the schema of an indexed column is altered.
-- **Flush**: Automatically builds indexes for new SST files created by a flush.
-- **Compact**: Automatically builds indexes for new SST files created by a compaction.
-
-### Additional Index Metadata Installation
-
-Previously, index information in the in-memory `FileMeta` was updated synchronously. The async approach requires an explicit installation step.
-
-A race condition can occur when compaction and index building run concurrently, leading to:
-1. Building an index for a file that is about to be deleted by compaction.
-2. Creating an unnecessary index file and an incorrect manifest record.
-3. On restart, replaying the manifest could load metadata for a non-existent file.
-
-To prevent this, the system checks if a file's `FileMeta` is in a `compacting` state before updating the manifest. If it is, the installation is aborted.
-
-### Fine-grained `FileMeta` Index
-
-The original `FileMeta` only stored file-level index information. However, manual rebuilds require column-level details to identify files inconsistent with the current DDL. Therefore, the `indexes` field in `FileMeta` is updated as follows:
-```rust
-struct FileMeta {
-    ...
-    // From file-level:
-    // available_indexes: SmallVec<[IndexType; 4]>
-    // To column-level:
-    indexes: Vec<ColumnIndexMetadata>,
-    ...
-}
-pub struct ColumnIndexMetadata {
-    pub column_id: ColumnId,
-    pub created_indexes: IndexTypes,
-}
-```
-
-## Process
-
-The index building process is similar to a flush and is illustrated below:
-
-```mermaid
-sequenceDiagram
-    Region0->>Region0: Triggered by one of 4 conditions, targets specific files
-    loop For each target file
-    Region0->>IndexBuildScheduler: Submits an index build task
-    end
-    IndexBuildScheduler->>IndexBuildTask: Executes the task
-    IndexBuildTask->>Storage Interfaces: Reads SST data from disk
-    IndexBuildTask->>IndexBuildTask: Builds the index file
-    alt Index file size > 0
-    IndexBuildTask->>Region0: Sends IndexBuildFinished notification
-    end
-    alt File exists in Version and is not compacting
-    Region0->>Storage Interfaces: Updates manifest and Version
-    end
-```
-
-### Task Triggering and Scheduling
-
-The process starts with one of the four `IndexBuildType` triggers. In `handle_rebuild_index`, the `RegionWorkerLoop` identifies target SSTs from the request or the current region version. It then creates an `IndexBuildTask` for each file and submits it to the `index_build_scheduler`.
-
-Similar to Flush and Compact operations, index build tasks are ultimately dispatched to the LocalScheduler. Resource usage can be adjusted via configuration files. Since asynchronous index tasks are both memory-intensive and IO-intensive but have lower priority, it is recommended to allocate fewer resources to them compared to compaction and flush tasks—for example, limiting them to 1/8 of the CPU cores. 
-
-### Index Building and Notification
-
-The scheduled `IndexBuildTask` executes its `index_build` method. It uses an `indexer_builder` to create an `Indexer` that reads SST data and builds the index. If a new index file is created (`IndexOutput.file_size > 0`), the task sends an `IndexBuildFinished` notification back to the `RegionWorkerLoop`.
-
-### Index Metadata Installation
-
-Upon receiving the `IndexBuildFinished` notification in `handle_index_build_finished`, the `RegionWorkerLoop` verifies that the file still exists in the current `version` and is not being compacted. If the check passes, it calls `manifest_ctx.update_manifest` to apply a `RegionEdit` with the new index information, completing the installation.
-
-# Drawbacks
-
-Asynchronous index building may consume extra system resources, potentially affecting overall performance during peak periods.
-
-There may be a delay before the new index becomes available for queries, which could impact certain use cases.
-
-# Unresolved Questions and Future Work
-
-**Resource Management and Throttling**: The resource consumption (CPU, I/O) of background index building can be managed and limited to some extent by configuring a dedicated background thread pool. However, this approach cannot fully eliminate resource contention, especially under heavy workloads or when I/O is highly competitive. Additional throttling mechanisms or dynamic prioritization may still be necessary to avoid impacting foreground operations.
-
-# Alternatives
-
-Instead of being triggered by events like Flush or Compact, index building could be performed in batches during scheduled maintenance windows. This offers predictable resource usage but delays index availability.

flake.nix

@@ -15,6 +15,8 @@
       let
         pkgs = nixpkgs.legacyPackages.${system};
         buildInputs = with pkgs; [
+          libgit2
+          libz
         ];
         lib = nixpkgs.lib;
         rustToolchain = fenix.packages.${system}.fromToolchainName {

grafana/dashboards/metrics/cluster/dashboard.md

@@ -87,13 +87,6 @@
 | Other Request P99 per Instance | `histogram_quantile(0.99, sum by(instance, pod, le, scheme, operation) (rate(opendal_operation_duration_seconds_bucket{instance=~"$datanode", operation!~"read\|write\|list\|Writer::write\|Writer::close\|Reader::read"}[$__rate_interval])))` | `timeseries` | Other Request P99 per Instance. | `prometheus` | `s` | `[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]` |
 | Opendal traffic | `sum by(instance, pod, scheme, operation) (rate(opendal_operation_bytes_sum{instance=~"$datanode"}[$__rate_interval]))` | `timeseries` | Total traffic as in bytes by instance and operation | `prometheus` | `decbytes` | `[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]` |
 | OpenDAL errors per Instance | `sum by(instance, pod, scheme, operation, error) (rate(opendal_operation_errors_total{instance=~"$datanode", error!="NotFound"}[$__rate_interval]))` | `timeseries` | OpenDAL error counts per Instance. | `prometheus` | -- | `[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]-[{{error}}]` |
-# Remote WAL
-| Title | Query | Type | Description | Datasource | Unit | Legend Format |
-| --- | --- | --- | --- | --- | --- | --- |
-| Triggered region flush total | `meta_triggered_region_flush_total` | `timeseries` | Triggered region flush total | `prometheus` | `none` | `{{pod}}-{{topic_name}}` |
-| Triggered region checkpoint total | `meta_triggered_region_checkpoint_total` | `timeseries` | Triggered region checkpoint total | `prometheus` | `none` | `{{pod}}-{{topic_name}}` |
-| Topic estimated replay size | `meta_topic_estimated_replay_size` | `timeseries` | Topic estimated max replay size | `prometheus` | `bytes` | `{{pod}}-{{topic_name}}` |
-| Kafka logstore's bytes traffic | `rate(greptime_logstore_kafka_client_bytes_total[$__rate_interval])` | `timeseries` | Kafka logstore's bytes traffic | `prometheus` | `bytes` | `{{pod}}-{{logstore}}` |
 # Metasrv
 | Title | Query | Type | Description | Datasource | Unit | Legend Format |
 | --- | --- | --- | --- | --- | --- | --- |
@@ -110,8 +103,6 @@
 | Meta KV Ops Latency | `histogram_quantile(0.99, sum by(pod, le, op, target) (greptime_meta_kv_request_elapsed_bucket))` | `timeseries` | Gauge of load information of each datanode, collected via heartbeat between datanode and metasrv. This information is for metasrv to schedule workloads. | `prometheus` | `s` | `{{pod}}-{{op}} p99` |
 | Rate of meta KV Ops | `rate(greptime_meta_kv_request_elapsed_count[$__rate_interval])` | `timeseries` | Gauge of load information of each datanode, collected via heartbeat between datanode and metasrv. This information is for metasrv to schedule workloads. | `prometheus` | `none` | `{{pod}}-{{op}} p99` |
 | DDL Latency | `histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_tables_bucket))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_table))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_view))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_flow))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_drop_table))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_alter_table))` | `timeseries` | Gauge of load information of each datanode, collected via heartbeat between datanode and metasrv. This information is for metasrv to schedule workloads. | `prometheus` | `s` | `CreateLogicalTables-{{step}} p90` |
-| Reconciliation stats | `greptime_meta_reconciliation_stats` | `timeseries` | Reconciliation stats | `prometheus` | `s` | `{{pod}}-{{table_type}}-{{type}}` |
-| Reconciliation steps | `histogram_quantile(0.9, greptime_meta_reconciliation_procedure_bucket)` | `timeseries` | Elapsed of Reconciliation steps  | `prometheus` | `s` | `{{procedure_name}}-{{step}}-P90` |
 # Flownode
 | Title | Query | Type | Description | Datasource | Unit | Legend Format |
 | --- | --- | --- | --- | --- | --- | --- |

grafana/dashboards/metrics/cluster/dashboard.yaml

@@ -802,48 +802,6 @@ groups:
                 type: prometheus
                 uid: ${metrics}
               legendFormat: '[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]-[{{error}}]'
-    - title: Remote WAL
-      panels:
-        - title: Triggered region flush total
-          type: timeseries
-          description: Triggered region flush total
-          unit: none
-          queries:
-            - expr: meta_triggered_region_flush_total
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{topic_name}}'
-        - title: Triggered region checkpoint total
-          type: timeseries
-          description: Triggered region checkpoint total
-          unit: none
-          queries:
-            - expr: meta_triggered_region_checkpoint_total
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{topic_name}}'
-        - title: Topic estimated replay size
-          type: timeseries
-          description: Topic estimated max replay size
-          unit: bytes
-          queries:
-            - expr: meta_topic_estimated_replay_size
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{topic_name}}'
-        - title: Kafka logstore's bytes traffic
-          type: timeseries
-          description: Kafka logstore's bytes traffic
-          unit: bytes
-          queries:
-            - expr: rate(greptime_logstore_kafka_client_bytes_total[$__rate_interval])
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{logstore}}'
     - title: Metasrv
       panels:
         - title: Region migration datanode
@@ -990,26 +948,6 @@ groups:
                 type: prometheus
                 uid: ${metrics}
               legendFormat: AlterTable-{{step}} p90
-        - title: Reconciliation stats
-          type: timeseries
-          description: Reconciliation stats
-          unit: s
-          queries:
-            - expr: greptime_meta_reconciliation_stats
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{table_type}}-{{type}}'
-        - title: Reconciliation steps
-          type: timeseries
-          description: 'Elapsed of Reconciliation steps '
-          unit: s
-          queries:
-            - expr: histogram_quantile(0.9, greptime_meta_reconciliation_procedure_bucket)
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{procedure_name}}-{{step}}-P90'
     - title: Flownode
       panels:
         - title: Flow Ingest / Output Rate

grafana/dashboards/metrics/standalone/dashboard.md

@@ -87,13 +87,6 @@
 | Other Request P99 per Instance | `histogram_quantile(0.99, sum by(instance, pod, le, scheme, operation) (rate(opendal_operation_duration_seconds_bucket{ operation!~"read\|write\|list\|Writer::write\|Writer::close\|Reader::read"}[$__rate_interval])))` | `timeseries` | Other Request P99 per Instance. | `prometheus` | `s` | `[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]` |
 | Opendal traffic | `sum by(instance, pod, scheme, operation) (rate(opendal_operation_bytes_sum{}[$__rate_interval]))` | `timeseries` | Total traffic as in bytes by instance and operation | `prometheus` | `decbytes` | `[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]` |
 | OpenDAL errors per Instance | `sum by(instance, pod, scheme, operation, error) (rate(opendal_operation_errors_total{ error!="NotFound"}[$__rate_interval]))` | `timeseries` | OpenDAL error counts per Instance. | `prometheus` | -- | `[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]-[{{error}}]` |
-# Remote WAL
-| Title | Query | Type | Description | Datasource | Unit | Legend Format |
-| --- | --- | --- | --- | --- | --- | --- |
-| Triggered region flush total | `meta_triggered_region_flush_total` | `timeseries` | Triggered region flush total | `prometheus` | `none` | `{{pod}}-{{topic_name}}` |
-| Triggered region checkpoint total | `meta_triggered_region_checkpoint_total` | `timeseries` | Triggered region checkpoint total | `prometheus` | `none` | `{{pod}}-{{topic_name}}` |
-| Topic estimated replay size | `meta_topic_estimated_replay_size` | `timeseries` | Topic estimated max replay size | `prometheus` | `bytes` | `{{pod}}-{{topic_name}}` |
-| Kafka logstore's bytes traffic | `rate(greptime_logstore_kafka_client_bytes_total[$__rate_interval])` | `timeseries` | Kafka logstore's bytes traffic | `prometheus` | `bytes` | `{{pod}}-{{logstore}}` |
 # Metasrv
 | Title | Query | Type | Description | Datasource | Unit | Legend Format |
 | --- | --- | --- | --- | --- | --- | --- |
@@ -110,8 +103,6 @@
 | Meta KV Ops Latency | `histogram_quantile(0.99, sum by(pod, le, op, target) (greptime_meta_kv_request_elapsed_bucket))` | `timeseries` | Gauge of load information of each datanode, collected via heartbeat between datanode and metasrv. This information is for metasrv to schedule workloads. | `prometheus` | `s` | `{{pod}}-{{op}} p99` |
 | Rate of meta KV Ops | `rate(greptime_meta_kv_request_elapsed_count[$__rate_interval])` | `timeseries` | Gauge of load information of each datanode, collected via heartbeat between datanode and metasrv. This information is for metasrv to schedule workloads. | `prometheus` | `none` | `{{pod}}-{{op}} p99` |
 | DDL Latency | `histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_tables_bucket))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_table))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_view))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_create_flow))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_drop_table))`<br/>`histogram_quantile(0.9, sum by(le, pod, step) (greptime_meta_procedure_alter_table))` | `timeseries` | Gauge of load information of each datanode, collected via heartbeat between datanode and metasrv. This information is for metasrv to schedule workloads. | `prometheus` | `s` | `CreateLogicalTables-{{step}} p90` |
-| Reconciliation stats | `greptime_meta_reconciliation_stats` | `timeseries` | Reconciliation stats | `prometheus` | `s` | `{{pod}}-{{table_type}}-{{type}}` |
-| Reconciliation steps | `histogram_quantile(0.9, greptime_meta_reconciliation_procedure_bucket)` | `timeseries` | Elapsed of Reconciliation steps  | `prometheus` | `s` | `{{procedure_name}}-{{step}}-P90` |
 # Flownode
 | Title | Query | Type | Description | Datasource | Unit | Legend Format |
 | --- | --- | --- | --- | --- | --- | --- |

grafana/dashboards/metrics/standalone/dashboard.yaml

@@ -802,48 +802,6 @@ groups:
                 type: prometheus
                 uid: ${metrics}
               legendFormat: '[{{instance}}]-[{{pod}}]-[{{scheme}}]-[{{operation}}]-[{{error}}]'
-    - title: Remote WAL
-      panels:
-        - title: Triggered region flush total
-          type: timeseries
-          description: Triggered region flush total
-          unit: none
-          queries:
-            - expr: meta_triggered_region_flush_total
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{topic_name}}'
-        - title: Triggered region checkpoint total
-          type: timeseries
-          description: Triggered region checkpoint total
-          unit: none
-          queries:
-            - expr: meta_triggered_region_checkpoint_total
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{topic_name}}'
-        - title: Topic estimated replay size
-          type: timeseries
-          description: Topic estimated max replay size
-          unit: bytes
-          queries:
-            - expr: meta_topic_estimated_replay_size
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{topic_name}}'
-        - title: Kafka logstore's bytes traffic
-          type: timeseries
-          description: Kafka logstore's bytes traffic
-          unit: bytes
-          queries:
-            - expr: rate(greptime_logstore_kafka_client_bytes_total[$__rate_interval])
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{logstore}}'
     - title: Metasrv
       panels:
         - title: Region migration datanode
@@ -990,26 +948,6 @@ groups:
                 type: prometheus
                 uid: ${metrics}
               legendFormat: AlterTable-{{step}} p90
-        - title: Reconciliation stats
-          type: timeseries
-          description: Reconciliation stats
-          unit: s
-          queries:
-            - expr: greptime_meta_reconciliation_stats
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{pod}}-{{table_type}}-{{type}}'
-        - title: Reconciliation steps
-          type: timeseries
-          description: 'Elapsed of Reconciliation steps '
-          unit: s
-          queries:
-            - expr: histogram_quantile(0.9, greptime_meta_reconciliation_procedure_bucket)
-              datasource:
-                type: prometheus
-                uid: ${metrics}
-              legendFormat: '{{procedure_name}}-{{step}}-P90'
     - title: Flownode
       panels:
         - title: Flow Ingest / Output Rate

scripts/fix-udeps.py

@@ -1,265 +0,0 @@
-# Copyright 2023 Greptime Team
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import json
-import os
-import re
-import sys
-
-
-def load_udeps_report(report_path):
-    try:
-        with open(report_path, "r") as f:
-            return json.load(f)
-    except FileNotFoundError:
-        print(f"Error: Report file '{report_path}' not found.")
-        return None
-    except json.JSONDecodeError as e:
-        print(f"Error: Invalid JSON in report file: {e}")
-        return None
-
-
-def extract_unused_dependencies(report):
-    """
-    Extract and organize unused dependencies from the cargo-udeps JSON report.
-
-    The cargo-udeps report has this structure:
-    {
-        "unused_deps": {
-            "package_name v0.1.0 (/path/to/package)": {
-                "normal": ["dep1", "dep2"],
-                "development": ["dev_dep1"],
-                "build": ["build_dep1"],
-                "manifest_path": "/path/to/Cargo.toml"
-            }
-        }
-    }
-
-    Args:
-        report (dict): The parsed JSON report from cargo-udeps
-
-    Returns:
-        dict: Organized unused dependencies by package name:
-        {
-            "package_name": {
-                "dependencies": [("dep1", "normal"), ("dev_dep1", "dev")],
-                "manifest_path": "/path/to/Cargo.toml"
-            }
-        }
-    """
-    if not report or "unused_deps" not in report:
-        return {}
-
-    unused_deps = {}
-    for package_full_name, deps_info in report["unused_deps"].items():
-        package_name = package_full_name.split(" ")[0]
-
-        all_unused = []
-        if deps_info.get("normal"):
-            all_unused.extend([(dep, "normal") for dep in deps_info["normal"]])
-        if deps_info.get("development"):
-            all_unused.extend([(dep, "dev") for dep in deps_info["development"]])
-        if deps_info.get("build"):
-            all_unused.extend([(dep, "build") for dep in deps_info["build"]])
-
-        if all_unused:
-            unused_deps[package_name] = {
-                "dependencies": all_unused,
-                "manifest_path": deps_info.get("manifest_path", "unknown"),
-            }
-
-    return unused_deps
-
-
-def get_section_pattern(dep_type):
-    """
-    Get regex patterns to identify different dependency sections in Cargo.toml.
-
-    Args:
-        dep_type (str): Type of dependency ("normal", "dev", or "build")
-
-    Returns:
-        list: List of regex patterns to match the appropriate section headers
-
-    """
-    patterns = {
-        "normal": [r"\[dependencies\]", r"\[dependencies\..*?\]"],
-        "dev": [r"\[dev-dependencies\]", r"\[dev-dependencies\..*?\]"],
-        "build": [r"\[build-dependencies\]", r"\[build-dependencies\..*?\]"],
-    }
-    return patterns.get(dep_type, [])
-
-
-def remove_dependency_line(content, dep_name, section_start, section_end):
-    """
-    Remove a dependency line from a specific section of a Cargo.toml file.
-
-    Args:
-        content (str): The entire content of the Cargo.toml file
-        dep_name (str): Name of the dependency to remove (e.g., "serde", "tokio")
-        section_start (int): Starting position of the section in the content
-        section_end (int): Ending position of the section in the content
-
-    Returns:
-        tuple: (new_content, removed) where:
-            - new_content (str): The modified content with dependency removed
-            - removed (bool): True if dependency was found and removed, False otherwise
-
-    Example input content format:
-        content = '''
-        [package]
-        name = "my-crate"
-        version = "0.1.0"
-
-        [dependencies]
-        serde = "1.0"
-        tokio = { version = "1.0", features = ["full"] }
-        serde_json.workspace = true
-
-        [dev-dependencies]
-        tempfile = "3.0"
-        '''
-
-        # If dep_name = "serde", section_start = start of [dependencies],
-        # section_end = start of [dev-dependencies], this function will:
-        # 1. Extract the section: "serde = "1.0"\ntokio = { version = "1.0", features = ["full"] }\nserde_json.workspace = true\n"
-        # 2. Find and remove the line: "serde = "1.0""
-        # 3. Return the modified content with that line removed
-    """
-    section_content = content[section_start:section_end]
-
-    dep_patterns = [
-        rf"^{re.escape(dep_name)}\s*=.*$",  # e.g., "serde = "1.0""
-        rf"^{re.escape(dep_name)}\.workspace\s*=.*$",  # e.g., "serde_json.workspace = true"
-    ]
-
-    for pattern in dep_patterns:
-        match = re.search(pattern, section_content, re.MULTILINE)
-        if match:
-            line_start = section_start + match.start()  # Start of the matched line
-            line_end = section_start + match.end()  # End of the matched line
-
-            if line_end < len(content) and content[line_end] == "\n":
-                line_end += 1
-
-            return content[:line_start] + content[line_end:], True
-
-    return content, False
-
-
-def remove_dependency_from_toml(file_path, dep_name, dep_type):
-    """
-    Remove a specific dependency from a Cargo.toml file.
-
-    Args:
-        file_path (str): Path to the Cargo.toml file
-        dep_name (str): Name of the dependency to remove
-        dep_type (str): Type of dependency ("normal", "dev", or "build")
-
-    Returns:
-        bool: True if dependency was successfully removed, False otherwise
-    """
-    try:
-        with open(file_path, "r") as f:
-            content = f.read()
-
-        section_patterns = get_section_pattern(dep_type)
-        if not section_patterns:
-            return False
-
-        for pattern in section_patterns:
-            section_match = re.search(pattern, content, re.IGNORECASE)
-            if not section_match:
-                continue
-
-            section_start = section_match.end()
-            next_section = re.search(r"\n\s*\[", content[section_start:])
-            section_end = (
-                section_start + next_section.start() if next_section else len(content)
-            )
-
-            new_content, removed = remove_dependency_line(
-                content, dep_name, section_start, section_end
-            )
-            if removed:
-                with open(file_path, "w") as f:
-                    f.write(new_content)
-                return True
-
-        return False
-
-    except Exception as e:
-        print(f"Error processing {file_path}: {e}")
-        return False
-
-
-def process_unused_dependencies(unused_deps):
-    """
-    Process and remove all unused dependencies from their respective Cargo.toml files.
-
-    Args:
-        unused_deps (dict): Dictionary of unused dependencies organized by package:
-            {
-                "package_name": {
-                    "dependencies": [("dep1", "normal"), ("dev_dep1", "dev")],
-                    "manifest_path": "/path/to/Cargo.toml"
-                }
-            }
-
-    """
-    if not unused_deps:
-        print("No unused dependencies found.")
-        return
-
-    total_removed = 0
-    total_failed = 0
-
-    for package, info in unused_deps.items():
-        deps = info["dependencies"]
-        manifest_path = info["manifest_path"]
-
-        if not os.path.exists(manifest_path):
-            print(f"Manifest file not found: {manifest_path}")
-            total_failed += len(deps)
-            continue
-
-        for dep, dep_type in deps:
-            if remove_dependency_from_toml(manifest_path, dep, dep_type):
-                print(f"Removed {dep} from {package}")
-                total_removed += 1
-            else:
-                print(f"Failed to remove {dep} from {package}")
-                total_failed += 1
-
-    print(f"Removed {total_removed} dependencies")
-    if total_failed > 0:
-        print(f"Failed to remove {total_failed} dependencies")
-
-
-def main():
-    if len(sys.argv) > 1:
-        report_path = sys.argv[1]
-    else:
-        report_path = "udeps-report.json"
-
-    report = load_udeps_report(report_path)
-    if report is None:
-        sys.exit(1)
-
-    unused_deps = extract_unused_dependencies(report)
-    process_unused_dependencies(unused_deps)
-
-
-if __name__ == "__main__":
-    main()

scripts/generate-etcd-tls-certs.sh

@@ -1,71 +0,0 @@
-#!/bin/bash
-
-# Generate TLS certificates for etcd testing
-# This script creates certificates for TLS-enabled etcd in testing environments
-
-set -euo pipefail
-
-CERT_DIR="${1:-$(dirname "$0")/../tests-integration/fixtures/etcd-tls-certs}"
-DAYS="${2:-365}"
-
-echo "Generating TLS certificates for etcd in ${CERT_DIR}..."
-
-mkdir -p "${CERT_DIR}"
-cd "${CERT_DIR}"
-
-echo "Generating CA private key..."
-openssl genrsa -out ca-key.pem 2048
-
-echo "Generating CA certificate..."
-openssl req -new -x509 -key ca-key.pem -out ca.crt -days "${DAYS}" \
-  -subj "/C=US/ST=CA/L=SF/O=Greptime/CN=etcd-ca"
-
-# Create server certificate config with Subject Alternative Names
-echo "Creating server certificate configuration..."
-cat > server.conf << 'EOF'
-[req]
-distinguished_name = req
-[v3_req]
-basicConstraints = CA:FALSE
-keyUsage = keyEncipherment, dataEncipherment
-subjectAltName = @alt_names
-[alt_names]
-DNS.1 = localhost
-DNS.2 = etcd-tls
-DNS.3 = 127.0.0.1
-IP.1 = 127.0.0.1
-IP.2 = ::1
-EOF
-
-echo "Generating server private key..."
-openssl genrsa -out server-key.pem 2048
-
-echo "Generating server certificate signing request..."
-openssl req -new -key server-key.pem -out server.csr \
-  -subj "/CN=etcd-tls"
-
-echo "Generating server certificate..."
-openssl x509 -req -in server.csr -CA ca.crt \
-  -CAkey ca-key.pem -CAcreateserial -out server.crt \
-  -days "${DAYS}" -extensions v3_req -extfile server.conf
-
-echo "Generating client private key..."
-openssl genrsa -out client-key.pem 2048
-
-echo "Generating client certificate signing request..."
-openssl req -new -key client-key.pem -out client.csr \
-  -subj "/CN=etcd-client"
-
-echo "Generating client certificate..."
-openssl x509 -req -in client.csr -CA ca.crt \
-  -CAkey ca-key.pem -CAcreateserial -out client.crt \
-  -days "${DAYS}"
-
-echo "Setting proper file permissions..."
-chmod 644 ca.crt server.crt client.crt
-chmod 600 ca-key.pem server-key.pem client-key.pem
-
-# Clean up intermediate files
-rm -f server.csr client.csr server.conf
-
-echo "TLS certificates generated successfully in ${CERT_DIR}"

src/api/Cargo.toml

@@ -19,3 +19,6 @@ paste.workspace = true
 prost.workspace = true
 serde_json.workspace = true
 snafu.workspace = true
+
+[build-dependencies]
+tonic-build = "0.11"

src/api/src/v1.rs

@@ -14,8 +14,6 @@
 
 pub mod column_def;
 
-pub mod helper;
-
 pub mod meta {
     pub use greptime_proto::v1::meta::*;
 }

src/api/src/v1/helper.rs

@@ -1,65 +0,0 @@
-// Copyright 2023 Greptime Team
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-use greptime_proto::v1::value::ValueData;
-use greptime_proto::v1::{ColumnDataType, ColumnSchema, Row, SemanticType, Value};
-
-/// Create a time index [ColumnSchema] with column's name and datatype.
-/// Other fields are left default.
-/// Useful when you just want to create a simple [ColumnSchema] without providing much struct fields.
-pub fn time_index_column_schema(name: &str, datatype: ColumnDataType) -> ColumnSchema {
-    ColumnSchema {
-        column_name: name.to_string(),
-        datatype: datatype as i32,
-        semantic_type: SemanticType::Timestamp as i32,
-        ..Default::default()
-    }
-}
-
-/// Create a tag [ColumnSchema] with column's name and datatype.
-/// Other fields are left default.
-/// Useful when you just want to create a simple [ColumnSchema] without providing much struct fields.
-pub fn tag_column_schema(name: &str, datatype: ColumnDataType) -> ColumnSchema {
-    ColumnSchema {
-        column_name: name.to_string(),
-        datatype: datatype as i32,
-        semantic_type: SemanticType::Tag as i32,
-        ..Default::default()
-    }
-}
-
-/// Create a field [ColumnSchema] with column's name and datatype.
-/// Other fields are left default.
-/// Useful when you just want to create a simple [ColumnSchema] without providing much struct fields.
-pub fn field_column_schema(name: &str, datatype: ColumnDataType) -> ColumnSchema {
-    ColumnSchema {
-        column_name: name.to_string(),
-        datatype: datatype as i32,
-        semantic_type: SemanticType::Field as i32,
-        ..Default::default()
-    }
-}
-
-/// Create a [Row] from [ValueData]s.
-/// Useful when you don't want to write much verbose codes.
-pub fn row(values: Vec<ValueData>) -> Row {
-    Row {
-        values: values
-            .into_iter()
-            .map(|x| Value {
-                value_data: Some(x),
-            })
-            .collect::<Vec<_>>(),
-    }
-}

src/auth/src/permission.rs

@@ -32,7 +32,6 @@ pub enum PermissionReq<'a> {
     PromStoreRead,
     Otlp,
     LogWrite,
-    BulkInsert,
 }
 
 #[derive(Debug)]

src/catalog/Cargo.toml

@@ -21,7 +21,6 @@ bytes.workspace = true
 common-base.workspace = true
 common-catalog.workspace = true
 common-error.workspace = true
-common-event-recorder.workspace = true
 common-frontend.workspace = true
 common-macro.workspace = true
 common-meta.workspace = true

src/catalog/src/kvbackend/manager.rs

@@ -44,7 +44,6 @@ use store_api::metric_engine_consts::METRIC_ENGINE_NAME;
 use table::dist_table::DistTable;
 use table::metadata::{TableId, TableInfoRef};
 use table::table::numbers::{NumbersTable, NUMBERS_TABLE_NAME};
-use table::table::PartitionRules;
 use table::table_name::TableName;
 use table::TableRef;
 use tokio::sync::Semaphore;
@@ -133,8 +132,6 @@ impl KvBackendCatalogManager {
         {
             let mut new_table_info = (*table.table_info()).clone();
 
-            let mut phy_part_cols_not_in_logical_table = vec![];
-
             // Remap partition key indices from physical table to logical table
             new_table_info.meta.partition_key_indices = physical_table_info_value
                 .table_info
@@ -151,30 +148,15 @@ impl KvBackendCatalogManager {
                         .get(physical_index)
                         .and_then(|physical_column| {
                             // Find the corresponding index in the logical table schema
-                            let idx = new_table_info
+                            new_table_info
                                 .meta
                                 .schema
-                                .column_index_by_name(physical_column.name.as_str());
+                                .column_index_by_name(physical_column.name.as_str())
-                            if idx.is_none() {
-                                // not all part columns in physical table that are also in logical table
-                                phy_part_cols_not_in_logical_table
-                                    .push(physical_column.name.clone());
-                            }
-
-                            idx
                         })
                 })
                 .collect();
 
-            let partition_rules = if !phy_part_cols_not_in_logical_table.is_empty() {
+            let new_table = DistTable::table(Arc::new(new_table_info));
-                Some(PartitionRules {
-                    extra_phy_cols_not_in_logical_table: phy_part_cols_not_in_logical_table,
-                })
-            } else {
-                None
-            };
-
-            let new_table = DistTable::table_partitioned(Arc::new(new_table_info), partition_rules);
 
             return Ok(new_table);
         }

src/catalog/src/memory/manager.rs

@@ -38,7 +38,7 @@ use crate::{CatalogManager, DeregisterTableRequest, RegisterSchemaRequest, Regis
 
 type SchemaEntries = HashMap<String, HashMap<String, TableRef>>;
 
-/// Simple in-memory list of catalogs used for tests.
+/// Simple in-memory list of catalogs
 #[derive(Clone)]
 pub struct MemoryCatalogManager {
     /// Collection of catalogs containing schemas and ultimately Tables

src/catalog/src/process_manager.rs

@@ -21,17 +21,17 @@ use std::time::{Duration, Instant, UNIX_EPOCH};
 
 use api::v1::frontend::{KillProcessRequest, ListProcessRequest, ProcessInfo};
 use common_base::cancellation::CancellationHandle;
-use common_event_recorder::EventRecorderRef;
 use common_frontend::selector::{FrontendSelector, MetaClientSelector};
 use common_frontend::slow_query_event::SlowQueryEvent;
-use common_telemetry::logging::SlowQueriesRecordType;
+use common_telemetry::{debug, error, info, warn};
-use common_telemetry::{debug, info, slow, warn};
 use common_time::util::current_time_millis;
 use meta_client::MetaClientRef;
 use promql_parser::parser::EvalStmt;
 use rand::random;
+use session::context::QueryContextRef;
 use snafu::{ensure, OptionExt, ResultExt};
 use sql::statements::statement::Statement;
+use tokio::sync::mpsc::Sender;
 
 use crate::error;
 use crate::metrics::{PROCESS_KILL_COUNT, PROCESS_LIST_COUNT};
@@ -249,8 +249,6 @@ pub struct Ticket {
     pub(crate) manager: ProcessManagerRef,
     pub(crate) id: ProcessId,
     pub cancellation_handle: Arc<CancellationHandle>,
-
-    // Keep the handle of the slow query timer to ensure it will trigger the event recording when dropped.
     _slow_query_timer: Option<SlowQueryTimer>,
 }
 
@@ -297,37 +295,38 @@ impl Debug for CancellableProcess {
 pub struct SlowQueryTimer {
     start: Instant,
     stmt: QueryStatement,
-    threshold: Duration,
+    query_ctx: QueryContextRef,
-    sample_ratio: f64,
+    threshold: Option<Duration>,
-    record_type: SlowQueriesRecordType,
+    sample_ratio: Option<f64>,
-    recorder: EventRecorderRef,
+    tx: Sender<SlowQueryEvent>,
 }
 
 impl SlowQueryTimer {
     pub fn new(
         stmt: QueryStatement,
-        threshold: Duration,
+        query_ctx: QueryContextRef,
-        sample_ratio: f64,
+        threshold: Option<Duration>,
-        record_type: SlowQueriesRecordType,
+        sample_ratio: Option<f64>,
-        recorder: EventRecorderRef,
+        tx: Sender<SlowQueryEvent>,
     ) -> Self {
         Self {
             start: Instant::now(),
             stmt,
+            query_ctx,
             threshold,
             sample_ratio,
-            record_type,
+            tx,
-            recorder,
         }
     }
 }
 
 impl SlowQueryTimer {
-    fn send_slow_query_event(&self, elapsed: Duration) {
+    fn send_slow_query_event(&self, elapsed: Duration, threshold: Duration) {
         let mut slow_query_event = SlowQueryEvent {
             cost: elapsed.as_millis() as u64,
-            threshold: self.threshold.as_millis() as u64,
+            threshold: threshold.as_millis() as u64,
             query: "".to_string(),
+            query_ctx: self.query_ctx.clone(),
 
             // The following fields are only used for PromQL queries.
             is_promql: false,
@@ -364,37 +363,29 @@ impl SlowQueryTimer {
             }
         }
 
-        match self.record_type {
+        // Send SlowQueryEvent to the handler.
-            // Send the slow query event to the event recorder to persist it as the system table.
+        if let Err(e) = self.tx.try_send(slow_query_event) {
-            SlowQueriesRecordType::SystemTable => {
+            error!(e; "Failed to send slow query event");
-                self.recorder.record(Box::new(slow_query_event));
-            }
-            // Record the slow query in a specific logs file.
-            SlowQueriesRecordType::Log => {
-                slow!(
-                    cost = slow_query_event.cost,
-                    threshold = slow_query_event.threshold,
-                    query = slow_query_event.query,
-                    is_promql = slow_query_event.is_promql,
-                    promql_range = slow_query_event.promql_range,
-                    promql_step = slow_query_event.promql_step,
-                    promql_start = slow_query_event.promql_start,
-                    promql_end = slow_query_event.promql_end,
-                );
-            }
         }
     }
 }
 
 impl Drop for SlowQueryTimer {
     fn drop(&mut self) {
-        // Calculate the elaspsed duration since the timer is created.
+        if let Some(threshold) = self.threshold {
-        let elapsed = self.start.elapsed();
+            // Calculate the elaspsed duration since the timer is created.
-        if elapsed > self.threshold {
+            let elapsed = self.start.elapsed();
-            // Only capture a portion of slow queries based on sample_ratio.
+            if elapsed > threshold {
-            // Generate a random number in [0, 1) and compare it with sample_ratio.
+                if let Some(ratio) = self.sample_ratio {
-            if self.sample_ratio >= 1.0 || random::<f64>() <= self.sample_ratio {
+                    // Only capture a portion of slow queries based on sample_ratio.
-                self.send_slow_query_event(elapsed);
+                    // Generate a random number in [0, 1) and compare it with sample_ratio.
+                    if ratio >= 1.0 || random::<f64>() <= ratio {
+                        self.send_slow_query_event(elapsed, threshold);
+                    }
+                } else {
+                    // Captures all slow queries if sample_ratio is not set.
+                    self.send_slow_query_event(elapsed, threshold);
+                }
             }
         }
     }

src/catalog/src/system_schema/information_schema/tables.rs

@@ -30,7 +30,8 @@ use datatypes::prelude::{ConcreteDataType, ScalarVectorBuilder, VectorRef};
 use datatypes::schema::{ColumnSchema, Schema, SchemaRef};
 use datatypes::value::Value;
 use datatypes::vectors::{
-    StringVectorBuilder, TimestampSecondVectorBuilder, UInt32VectorBuilder, UInt64VectorBuilder,
+    StringVectorBuilder, TimestampMicrosecondVectorBuilder, UInt32VectorBuilder,
+    UInt64VectorBuilder,
 };
 use futures::TryStreamExt;
 use snafu::{OptionExt, ResultExt};
@@ -106,17 +107,17 @@ impl InformationSchemaTables {
             ColumnSchema::new(AUTO_INCREMENT, ConcreteDataType::uint64_datatype(), true),
             ColumnSchema::new(
                 CREATE_TIME,
-                ConcreteDataType::timestamp_second_datatype(),
+                ConcreteDataType::timestamp_microsecond_datatype(),
                 true,
             ),
             ColumnSchema::new(
                 UPDATE_TIME,
-                ConcreteDataType::timestamp_second_datatype(),
+                ConcreteDataType::timestamp_microsecond_datatype(),
                 true,
             ),
             ColumnSchema::new(
                 CHECK_TIME,
-                ConcreteDataType::timestamp_second_datatype(),
+                ConcreteDataType::timestamp_microsecond_datatype(),
                 true,
             ),
             ColumnSchema::new(TABLE_COLLATION, ConcreteDataType::string_datatype(), true),
@@ -193,9 +194,9 @@ struct InformationSchemaTablesBuilder {
     max_index_length: UInt64VectorBuilder,
     data_free: UInt64VectorBuilder,
     auto_increment: UInt64VectorBuilder,
-    create_time: TimestampSecondVectorBuilder,
+    create_time: TimestampMicrosecondVectorBuilder,
-    update_time: TimestampSecondVectorBuilder,
+    update_time: TimestampMicrosecondVectorBuilder,
-    check_time: TimestampSecondVectorBuilder,
+    check_time: TimestampMicrosecondVectorBuilder,
     table_collation: StringVectorBuilder,
     checksum: UInt64VectorBuilder,
     create_options: StringVectorBuilder,
@@ -230,9 +231,9 @@ impl InformationSchemaTablesBuilder {
             max_index_length: UInt64VectorBuilder::with_capacity(INIT_CAPACITY),
             data_free: UInt64VectorBuilder::with_capacity(INIT_CAPACITY),
             auto_increment: UInt64VectorBuilder::with_capacity(INIT_CAPACITY),
-            create_time: TimestampSecondVectorBuilder::with_capacity(INIT_CAPACITY),
+            create_time: TimestampMicrosecondVectorBuilder::with_capacity(INIT_CAPACITY),
-            update_time: TimestampSecondVectorBuilder::with_capacity(INIT_CAPACITY),
+            update_time: TimestampMicrosecondVectorBuilder::with_capacity(INIT_CAPACITY),
-            check_time: TimestampSecondVectorBuilder::with_capacity(INIT_CAPACITY),
+            check_time: TimestampMicrosecondVectorBuilder::with_capacity(INIT_CAPACITY),
             table_collation: StringVectorBuilder::with_capacity(INIT_CAPACITY),
             checksum: UInt64VectorBuilder::with_capacity(INIT_CAPACITY),
             create_options: StringVectorBuilder::with_capacity(INIT_CAPACITY),
@@ -379,7 +380,7 @@ impl InformationSchemaTablesBuilder {
         self.create_options
             .push(Some(table_info.meta.options.to_string().as_ref()));
         self.create_time
-            .push(Some(table_info.meta.created_on.timestamp().into()));
+            .push(Some(table_info.meta.created_on.timestamp_millis().into()));
 
         self.temporary
             .push(if matches!(table_type, TableType::Temporary) {

src/catalog/src/system_schema/predicate.rs

@@ -133,7 +133,7 @@ impl Predicate {
                 let Expr::Column(c) = *expr else {
                     unreachable!();
                 };
-                let Expr::Literal(ScalarValue::Utf8(Some(pattern)), _) = *pattern else {
+                let Expr::Literal(ScalarValue::Utf8(Some(pattern))) = *pattern else {
                     unreachable!();
                 };
 
@@ -148,8 +148,8 @@ impl Predicate {
             // left OP right
             Expr::BinaryExpr(bin) => match (*bin.left, bin.op, *bin.right) {
                 // left == right
-                (Expr::Literal(scalar, _), Operator::Eq, Expr::Column(c))
+                (Expr::Literal(scalar), Operator::Eq, Expr::Column(c))
-                | (Expr::Column(c), Operator::Eq, Expr::Literal(scalar, _)) => {
+                | (Expr::Column(c), Operator::Eq, Expr::Literal(scalar)) => {
                     let Ok(v) = Value::try_from(scalar) else {
                         return None;
                     };
@@ -157,8 +157,8 @@ impl Predicate {
                     Some(Predicate::Eq(c.name, v))
                 }
                 // left != right
-                (Expr::Literal(scalar, _), Operator::NotEq, Expr::Column(c))
+                (Expr::Literal(scalar), Operator::NotEq, Expr::Column(c))
-                | (Expr::Column(c), Operator::NotEq, Expr::Literal(scalar, _)) => {
+                | (Expr::Column(c), Operator::NotEq, Expr::Literal(scalar)) => {
                     let Ok(v) = Value::try_from(scalar) else {
                         return None;
                     };
@@ -189,7 +189,7 @@ impl Predicate {
                         let mut values = Vec::with_capacity(list.len());
                         for scalar in list {
                             // Safety: checked by `is_all_scalars`
-                            let Expr::Literal(scalar, _) = scalar else {
+                            let Expr::Literal(scalar) = scalar else {
                                 unreachable!();
                             };
 
@@ -237,7 +237,7 @@ fn like_utf8(s: &str, pattern: &str, case_insensitive: &bool) -> Option<bool> {
 }
 
 fn is_string_literal(expr: &Expr) -> bool {
-    matches!(expr, Expr::Literal(ScalarValue::Utf8(Some(_)), _))
+    matches!(expr, Expr::Literal(ScalarValue::Utf8(Some(_))))
 }
 
 fn is_column(expr: &Expr) -> bool {
@@ -286,14 +286,14 @@ impl Predicates {
 
 /// Returns true when the values are all [`DfExpr::Literal`].
 fn is_all_scalars(list: &[Expr]) -> bool {
-    list.iter().all(|v| matches!(v, Expr::Literal(_, _)))
+    list.iter().all(|v| matches!(v, Expr::Literal(_)))
 }
 
 #[cfg(test)]
 mod tests {
-    use datafusion::common::Column;
+    use datafusion::common::{Column, ScalarValue};
     use datafusion::logical_expr::expr::InList;
-    use datafusion::logical_expr::{BinaryExpr, Literal};
+    use datafusion::logical_expr::BinaryExpr;
 
     use super::*;
 
@@ -378,7 +378,7 @@ mod tests {
         let expr = Expr::Like(Like {
             negated: false,
             expr: Box::new(column("a")),
-            pattern: Box::new("%abc".lit()),
+            pattern: Box::new(string_literal("%abc")),
             case_insensitive: true,
             escape_char: None,
         });
@@ -405,7 +405,7 @@ mod tests {
         let expr = Expr::Like(Like {
             negated: false,
             expr: Box::new(column("a")),
-            pattern: Box::new("%abc".lit()),
+            pattern: Box::new(string_literal("%abc")),
             case_insensitive: false,
             escape_char: None,
         });
@@ -425,7 +425,7 @@ mod tests {
         let expr = Expr::Like(Like {
             negated: true,
             expr: Box::new(column("a")),
-            pattern: Box::new("%abc".lit()),
+            pattern: Box::new(string_literal("%abc")),
             case_insensitive: true,
             escape_char: None,
         });
@@ -440,6 +440,10 @@ mod tests {
         Expr::Column(Column::from_name(name))
     }
 
+    fn string_literal(v: &str) -> Expr {
+        Expr::Literal(ScalarValue::Utf8(Some(v.to_string())))
+    }
+
     fn match_string_value(v: &Value, expected: &str) -> bool {
         matches!(v, Value::String(bs) if bs.as_utf8() == expected)
     }
@@ -459,13 +463,13 @@ mod tests {
         let expr1 = Expr::BinaryExpr(BinaryExpr {
             left: Box::new(column("a")),
             op: Operator::Eq,
-            right: Box::new("a_value".lit()),
+            right: Box::new(string_literal("a_value")),
         });
 
         let expr2 = Expr::BinaryExpr(BinaryExpr {
             left: Box::new(column("b")),
             op: Operator::NotEq,
-            right: Box::new("b_value".lit()),
+            right: Box::new(string_literal("b_value")),
         });
 
         (expr1, expr2)
@@ -504,7 +508,7 @@ mod tests {
 
         let inlist_expr = Expr::InList(InList {
             expr: Box::new(column("a")),
-            list: vec!["a1".lit(), "a2".lit()],
+            list: vec![string_literal("a1"), string_literal("a2")],
             negated: false,
         });
 
@@ -514,7 +518,7 @@ mod tests {
 
         let inlist_expr = Expr::InList(InList {
             expr: Box::new(column("a")),
-            list: vec!["a1".lit(), "a2".lit()],
+            list: vec![string_literal("a1"), string_literal("a2")],
             negated: true,
         });
         let inlist_p = Predicate::from_expr(inlist_expr).unwrap();

src/catalog/src/table_source.rs

@@ -32,7 +32,7 @@ use dummy_catalog::DummyCatalogList;
 use table::TableRef;
 
 use crate::error::{
-    CastManagerSnafu, DecodePlanSnafu, GetViewCacheSnafu, ProjectViewColumnsSnafu,
+    CastManagerSnafu, DatafusionSnafu, DecodePlanSnafu, GetViewCacheSnafu, ProjectViewColumnsSnafu,
     QueryAccessDeniedSnafu, Result, TableNotExistSnafu, ViewInfoNotFoundSnafu,
     ViewPlanColumnsChangedSnafu,
 };
@@ -199,10 +199,10 @@ impl DfTableSourceProvider {
             logical_plan
         };
 
-        Ok(Arc::new(ViewTable::new(
+        Ok(Arc::new(
-            logical_plan,
+            ViewTable::try_new(logical_plan, Some(view_info.definition.to_string()))
-            Some(view_info.definition.to_string()),
+                .context(DatafusionSnafu)?,
-        )))
+        ))
     }
 }
 

src/cli/src/bench.rs

@@ -66,9 +66,6 @@ pub struct BenchTableMetadataCommand {
     #[cfg(feature = "pg_kvbackend")]
     #[clap(long)]
     postgres_addr: Option<String>,
-    #[cfg(feature = "pg_kvbackend")]
-    #[clap(long)]
-    postgres_schema: Option<String>,
     #[cfg(feature = "mysql_kvbackend")]
     #[clap(long)]
     mysql_addr: Option<String>,

src/cli/src/metadata/common.rs

@@ -19,9 +19,8 @@ use common_error::ext::BoxedError;
 use common_meta::kv_backend::chroot::ChrootKvBackend;
 use common_meta::kv_backend::etcd::EtcdStore;
 use common_meta::kv_backend::KvBackendRef;
-use meta_srv::bootstrap::create_etcd_client_with_tls;
+use meta_srv::bootstrap::create_etcd_client;
 use meta_srv::metasrv::BackendImpl;
-use servers::tls::{TlsMode, TlsOption};
 
 use crate::error::{EmptyStoreAddrsSnafu, UnsupportedMemoryBackendSnafu};
 
@@ -56,30 +55,6 @@ pub(crate) struct StoreConfig {
     #[cfg(any(feature = "pg_kvbackend", feature = "mysql_kvbackend"))]
     #[clap(long, default_value = common_meta::kv_backend::DEFAULT_META_TABLE_NAME)]
     meta_table_name: String,
-
-    /// Optional PostgreSQL schema for metadata table (defaults to current search_path if unset).
-    #[cfg(feature = "pg_kvbackend")]
-    #[clap(long)]
-    meta_schema_name: Option<String>,
-    /// TLS mode for backend store connections (etcd, PostgreSQL, MySQL)
-    #[clap(long = "backend-tls-mode", value_enum, default_value = "disable")]
-    backend_tls_mode: TlsMode,
-
-    /// Path to TLS certificate file for backend store connections
-    #[clap(long = "backend-tls-cert-path", default_value = "")]
-    backend_tls_cert_path: String,
-
-    /// Path to TLS private key file for backend store connections
-    #[clap(long = "backend-tls-key-path", default_value = "")]
-    backend_tls_key_path: String,
-
-    /// Path to TLS CA certificate file for backend store connections
-    #[clap(long = "backend-tls-ca-cert-path", default_value = "")]
-    backend_tls_ca_cert_path: String,
-
-    /// Enable watching TLS certificate files for changes
-    #[clap(long = "backend-tls-watch")]
-    backend_tls_watch: bool,
 }
 
 impl StoreConfig {
@@ -92,18 +67,7 @@ impl StoreConfig {
         } else {
             let kvbackend = match self.backend {
                 BackendImpl::EtcdStore => {
-                    let tls_config = if self.backend_tls_mode != TlsMode::Disable {
+                    let etcd_client = create_etcd_client(store_addrs)
-                        Some(TlsOption {
-                            mode: self.backend_tls_mode.clone(),
-                            cert_path: self.backend_tls_cert_path.clone(),
-                            key_path: self.backend_tls_key_path.clone(),
-                            ca_cert_path: self.backend_tls_ca_cert_path.clone(),
-                            watch: self.backend_tls_watch,
-                        })
-                    } else {
-                        None
-                    };
-                    let etcd_client = create_etcd_client_with_tls(store_addrs, tls_config.as_ref())
                         .await
                         .map_err(BoxedError::new)?;
                     Ok(EtcdStore::with_etcd_client(etcd_client, max_txn_ops))
@@ -114,10 +78,8 @@ impl StoreConfig {
                     let pool = meta_srv::bootstrap::create_postgres_pool(store_addrs, None)
                         .await
                         .map_err(BoxedError::new)?;
-                    let schema_name = self.meta_schema_name.as_deref();
                     Ok(common_meta::kv_backend::rds::PgStore::with_pg_pool(
                         pool,
-                        schema_name,
                         table_name,
                         max_txn_ops,
                     )

src/cli/src/metadata/repair/create_table.rs

@@ -74,19 +74,11 @@ pub fn make_create_region_request_for_peer(
     let catalog = &create_table_expr.catalog_name;
     let schema = &create_table_expr.schema_name;
     let storage_path = region_storage_path(catalog, schema);
-    let partition_exprs = region_routes
-        .iter()
-        .map(|r| (r.region.id.region_number(), r.region.partition_expr()))
-        .collect::<HashMap<_, _>>();
 
     for region_number in &regions_on_this_peer {
         let region_id = RegionId::new(logical_table_id, *region_number);
-        let region_request = request_builder.build_one(
+        let region_request =
-            region_id,
+            request_builder.build_one(region_id, storage_path.clone(), &HashMap::new());
-            storage_path.clone(),
-            &HashMap::new(),
-            &partition_exprs,
-        );
         requests.push(region_request);
     }
 

src/client/Cargo.toml

@@ -29,7 +29,6 @@ datatypes.workspace = true
 enum_dispatch = "0.3"
 futures.workspace = true
 futures-util.workspace = true
-humantime.workspace = true
 lazy_static.workspace = true
 moka = { workspace = true, features = ["future"] }
 parking_lot.workspace = true
@@ -39,7 +38,6 @@ query.workspace = true
 rand.workspace = true
 serde_json.workspace = true
 snafu.workspace = true
-store-api.workspace = true
 substrait.workspace = true
 tokio.workspace = true
 tokio-stream = { workspace = true, features = ["net"] }

src/client/src/client_manager.rs

@@ -17,7 +17,7 @@ use std::sync::Arc;
 use std::time::Duration;
 
 use common_grpc::channel_manager::{ChannelConfig, ChannelManager};
-use common_meta::node_manager::{DatanodeManager, DatanodeRef, FlownodeManager, FlownodeRef};
+use common_meta::node_manager::{DatanodeRef, FlownodeRef, NodeManager};
 use common_meta::peer::Peer;
 use moka::future::{Cache, CacheBuilder};
 
@@ -45,7 +45,7 @@ impl Debug for NodeClients {
 }
 
 #[async_trait::async_trait]
-impl DatanodeManager for NodeClients {
+impl NodeManager for NodeClients {
     async fn datanode(&self, datanode: &Peer) -> DatanodeRef {
         let client = self.get_client(datanode).await;
 
@@ -60,10 +60,7 @@ impl DatanodeManager for NodeClients {
             *accept_compression,
         ))
     }
-}
 
-#[async_trait::async_trait]
-impl FlownodeManager for NodeClients {
     async fn flownode(&self, flownode: &Peer) -> FlownodeRef {
         let client = self.get_client(flownode).await;
 

src/client/src/database.rs

@@ -75,24 +75,12 @@ pub struct Database {
 }
 
 pub struct DatabaseClient {
-    pub addr: String,
     pub inner: GreptimeDatabaseClient<Channel>,
 }
 
-impl DatabaseClient {
-    /// Returns a closure that logs the error when the request fails.
-    pub fn inspect_err<'a>(&'a self, context: &'a str) -> impl Fn(&tonic::Status) + 'a {
-        let addr = &self.addr;
-        move |status| {
-            error!("Failed to {context} request, peer: {addr}, status: {status:?}");
-        }
-    }
-}
-
 fn make_database_client(client: &Client) -> Result<DatabaseClient> {
-    let (addr, channel) = client.find_channel()?;
+    let (_, channel) = client.find_channel()?;
     Ok(DatabaseClient {
-        addr,
         inner: GreptimeDatabaseClient::new(channel)
             .max_decoding_message_size(client.max_grpc_recv_message_size())
             .max_encoding_message_size(client.max_grpc_send_message_size()),
@@ -179,19 +167,14 @@ impl Database {
         requests: InsertRequests,
         hints: &[(&str, &str)],
     ) -> Result<u32> {
-        let mut client = make_database_client(&self.client)?;
+        let mut client = make_database_client(&self.client)?.inner;
         let request = self.to_rpc_request(Request::Inserts(requests));
 
         let mut request = tonic::Request::new(request);
         let metadata = request.metadata_mut();
         Self::put_hints(metadata, hints)?;
 
-        let response = client
+        let response = client.handle(request).await?.into_inner();
-            .inner
-            .handle(request)
-            .await
-            .inspect_err(client.inspect_err("insert_with_hints"))?
-            .into_inner();
         from_grpc_response(response)
     }
 
@@ -206,19 +189,14 @@ impl Database {
         requests: RowInsertRequests,
         hints: &[(&str, &str)],
     ) -> Result<u32> {
-        let mut client = make_database_client(&self.client)?;
+        let mut client = make_database_client(&self.client)?.inner;
         let request = self.to_rpc_request(Request::RowInserts(requests));
 
         let mut request = tonic::Request::new(request);
         let metadata = request.metadata_mut();
         Self::put_hints(metadata, hints)?;
 
-        let response = client
+        let response = client.handle(request).await?.into_inner();
-            .inner
-            .handle(request)
-            .await
-            .inspect_err(client.inspect_err("row_inserts_with_hints"))?
-            .into_inner();
         from_grpc_response(response)
     }
 
@@ -239,14 +217,9 @@ impl Database {
 
     /// Make a request to the database.
     pub async fn handle(&self, request: Request) -> Result<u32> {
-        let mut client = make_database_client(&self.client)?;
+        let mut client = make_database_client(&self.client)?.inner;
         let request = self.to_rpc_request(request);
-        let response = client
+        let response = client.handle(request).await?.into_inner();
-            .inner
-            .handle(request)
-            .await
-            .inspect_err(client.inspect_err("handle"))?
-            .into_inner();
         from_grpc_response(response)
     }
 
@@ -258,7 +231,7 @@ impl Database {
         max_retries: u32,
         hints: &[(&str, &str)],
     ) -> Result<u32> {
-        let mut client = make_database_client(&self.client)?;
+        let mut client = make_database_client(&self.client)?.inner;
         let mut retries = 0;
 
         let request = self.to_rpc_request(request);
@@ -267,11 +240,7 @@ impl Database {
             let mut tonic_request = tonic::Request::new(request.clone());
             let metadata = tonic_request.metadata_mut();
             Self::put_hints(metadata, hints)?;
-            let raw_response = client
+            let raw_response = client.handle(tonic_request).await;
-                .inner
-                .handle(tonic_request)
-                .await
-                .inspect_err(client.inspect_err("handle"));
             match (raw_response, retries < max_retries) {
                 (Ok(resp), _) => return from_grpc_response(resp.into_inner()),
                 (Err(err), true) => {
@@ -473,8 +442,8 @@ impl Database {
         }) = &self.ctx.auth_header
         {
             let encoded = BASE64_STANDARD.encode(format!("{username}:{password}"));
-            let value = MetadataValue::from_str(&format!("Basic {encoded}"))
+            let value =
-                .context(InvalidTonicMetadataValueSnafu)?;
+                MetadataValue::from_str(&encoded).context(InvalidTonicMetadataValueSnafu)?;
             request.metadata_mut().insert("x-greptime-auth", value);
         }
 

src/client/src/error.rs

@@ -133,13 +133,6 @@ pub enum Error {
         #[snafu(implicit)]
         location: Location,
     },
-
-    #[snafu(display("External error"))]
-    External {
-        #[snafu(implicit)]
-        location: Location,
-        source: BoxedError,
-    },
 }
 
 pub type Result<T> = std::result::Result<T, Error>;
@@ -161,7 +154,6 @@ impl ErrorExt for Error {
             Error::IllegalGrpcClientState { .. } => StatusCode::Unexpected,
             Error::InvalidTonicMetadataValue { .. } => StatusCode::InvalidArguments,
             Error::ConvertSchema { source, .. } => source.status_code(),
-            Error::External { source, .. } => source.status_code(),
         }
     }
 

src/client/src/inserter.rs

@@ -1,68 +0,0 @@
-// Copyright 2023 Greptime Team
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-use std::time::Duration;
-
-use api::v1::RowInsertRequests;
-use humantime::format_duration;
-use store_api::mito_engine_options::{APPEND_MODE_KEY, TTL_KEY, TWCS_TIME_WINDOW};
-
-use crate::error::Result;
-
-/// Context holds the catalog and schema information.
-pub struct Context<'a> {
-    /// The catalog name.
-    pub catalog: &'a str,
-    /// The schema name.
-    pub schema: &'a str,
-}
-
-/// Options for insert operations.
-#[derive(Debug, Clone, Copy)]
-pub struct InsertOptions {
-    /// Time-to-live for the inserted data.
-    pub ttl: Duration,
-    /// Whether to use append mode for the insert.
-    pub append_mode: bool,
-    /// Time window for twcs compaction.
-    pub twcs_compaction_time_window: Option<Duration>,
-}
-
-impl InsertOptions {
-    /// Converts the insert options to a list of key-value string hints.
-    pub fn to_hints(&self) -> Vec<(&'static str, String)> {
-        let mut hints = vec![
-            (TTL_KEY, format_duration(self.ttl).to_string()),
-            (APPEND_MODE_KEY, self.append_mode.to_string()),
-        ];
-
-        if let Some(time_window) = self.twcs_compaction_time_window {
-            hints.push((TWCS_TIME_WINDOW, format_duration(time_window).to_string()));
-        }
-
-        hints
-    }
-}
-
-/// [`Inserter`] allows different components to share a unified mechanism for inserting data.
-///
-/// An implementation may perform the insert locally (e.g., via a direct procedure call) or
-/// delegate/forward it to another node for processing (e.g., MetaSrv forwarding to an
-/// available Frontend).
-#[async_trait::async_trait]
-pub trait Inserter: Send + Sync {
-    async fn insert_rows(&self, context: &Context<'_>, requests: RowInsertRequests) -> Result<()>;
-
-    fn set_options(&mut self, options: &InsertOptions);
-}

src/client/src/lib.rs

@@ -19,7 +19,6 @@ pub mod client_manager;
 pub mod database;
 pub mod error;
 pub mod flow;
-pub mod inserter;
 pub mod load_balance;
 mod metrics;
 pub mod region;

src/cmd/Cargo.toml

@@ -103,6 +103,3 @@ tempfile.workspace = true
 
 [target.'cfg(not(windows))'.dev-dependencies]
 rexpect = "0.5"
-
-[package.metadata.cargo-udeps.ignore]
-development = ["rexpect"]

src/cmd/src/flownode.rs

@@ -376,8 +376,7 @@ impl StartCommand {
             flow_auth_header,
             opts.query.clone(),
             opts.flow.batching_mode.clone(),
-        )
+        );
-        .context(StartFlownodeSnafu)?;
         let frontend_client = Arc::new(frontend_client);
         let flownode_builder = FlownodeBuilder::new(
             opts.clone(),

src/cmd/src/frontend.rs

@@ -41,7 +41,6 @@ use frontend::server::Services;
 use meta_client::{MetaClientOptions, MetaClientType};
 use servers::addrs;
 use servers::export_metrics::ExportMetricsTask;
-use servers::grpc::GrpcOptions;
 use servers::tls::{TlsMode, TlsOption};
 use snafu::{OptionExt, ResultExt};
 use tracing_appender::non_blocking::WorkerGuard;
@@ -145,14 +144,6 @@ pub struct StartCommand {
     /// on the host, with the same port number as the one specified in `rpc_bind_addr`.
     #[clap(long, alias = "rpc-hostname")]
     rpc_server_addr: Option<String>,
-    /// The address to bind the internal gRPC server.
-    #[clap(long, alias = "internal-rpc-addr")]
-    internal_rpc_bind_addr: Option<String>,
-    /// The address advertised to the metasrv, and used for connections from outside the host.
-    /// If left empty or unset, the server will automatically use the IP address of the first network interface
-    /// on the host, with the same port number as the one specified in `internal_rpc_bind_addr`.
-    #[clap(long, alias = "internal-rpc-hostname")]
-    internal_rpc_server_addr: Option<String>,
     #[clap(long)]
     http_addr: Option<String>,
     #[clap(long)]
@@ -250,31 +241,6 @@ impl StartCommand {
             opts.grpc.server_addr.clone_from(addr);
         }
 
-        if let Some(addr) = &self.internal_rpc_bind_addr {
-            if let Some(internal_grpc) = &mut opts.internal_grpc {
-                internal_grpc.bind_addr = addr.to_string();
-            } else {
-                let grpc_options = GrpcOptions {
-                    bind_addr: addr.to_string(),
-                    ..Default::default()
-                };
-
-                opts.internal_grpc = Some(grpc_options);
-            }
-        }
-
-        if let Some(addr) = &self.internal_rpc_server_addr {
-            if let Some(internal_grpc) = &mut opts.internal_grpc {
-                internal_grpc.server_addr = addr.to_string();
-            } else {
-                let grpc_options = GrpcOptions {
-                    server_addr: addr.to_string(),
-                    ..Default::default()
-                };
-                opts.internal_grpc = Some(grpc_options);
-            }
-        }
-
         if let Some(addr) = &self.mysql_addr {
             opts.mysql.enable = true;
             opts.mysql.addr.clone_from(addr);
@@ -313,7 +279,7 @@ impl StartCommand {
             &opts.component.logging,
             &opts.component.tracing,
             opts.component.node_id.clone(),
-            Some(&opts.component.slow_query),
+            opts.component.slow_query.as_ref(),
         );
 
         log_versions(verbose_version(), short_version(), APP_NAME);
@@ -482,8 +448,6 @@ mod tests {
             http_addr: Some("127.0.0.1:1234".to_string()),
             mysql_addr: Some("127.0.0.1:5678".to_string()),
             postgres_addr: Some("127.0.0.1:5432".to_string()),
-            internal_rpc_bind_addr: Some("127.0.0.1:4010".to_string()),
-            internal_rpc_server_addr: Some("10.0.0.24:4010".to_string()),
             influxdb_enable: Some(false),
             disable_dashboard: Some(false),
             ..Default::default()
@@ -496,10 +460,6 @@ mod tests {
         assert_eq!(opts.mysql.addr, "127.0.0.1:5678");
         assert_eq!(opts.postgres.addr, "127.0.0.1:5432");
 
-        let internal_grpc = opts.internal_grpc.as_ref().unwrap();
-        assert_eq!(internal_grpc.bind_addr, "127.0.0.1:4010");
-        assert_eq!(internal_grpc.server_addr, "10.0.0.24:4010");
-
         let default_opts = FrontendOptions::default().component;
 
         assert_eq!(opts.grpc.bind_addr, default_opts.grpc.bind_addr);

src/cmd/src/standalone.rs

@@ -157,7 +157,7 @@ pub struct StandaloneOptions {
     pub init_regions_in_background: bool,
     pub init_regions_parallelism: usize,
     pub max_in_flight_write_bytes: Option<ReadableSize>,
-    pub slow_query: SlowQueryOptions,
+    pub slow_query: Option<SlowQueryOptions>,
     pub query: QueryOptions,
     pub memory: MemoryOptions,
 }
@@ -191,7 +191,7 @@ impl Default for StandaloneOptions {
             init_regions_in_background: false,
             init_regions_parallelism: 16,
             max_in_flight_write_bytes: None,
-            slow_query: SlowQueryOptions::default(),
+            slow_query: Some(SlowQueryOptions::default()),
             query: QueryOptions::default(),
             memory: MemoryOptions::default(),
         }
@@ -486,7 +486,7 @@ impl StartCommand {
             &opts.component.logging,
             &opts.component.tracing,
             None,
-            Some(&opts.component.slow_query),
+            opts.component.slow_query.as_ref(),
         );
 
         log_versions(verbose_version(), short_version(), APP_NAME);
@@ -834,7 +834,6 @@ impl InformationExtension for StandaloneInformationExtension {
                     region_manifest: region_stat.manifest.into(),
                     data_topic_latest_entry_id: region_stat.data_topic_latest_entry_id,
                     metadata_topic_latest_entry_id: region_stat.metadata_topic_latest_entry_id,
-                    write_bytes: 0,
                 }
             })
             .collect::<Vec<_>>();

src/cmd/tests/load_config_test.rs

@@ -146,7 +146,6 @@ fn test_load_frontend_example_config() {
             grpc: GrpcOptions::default()
                 .with_bind_addr("127.0.0.1:4001")
                 .with_server_addr("127.0.0.1:4001"),
-            internal_grpc: Some(GrpcOptions::internal_default()),
             http: HttpOptions {
                 cors_allowed_origins: vec!["https://example.com".to_string()],
                 ..Default::default()
@@ -199,7 +198,6 @@ fn test_load_metasrv_example_config() {
                 ca_cert_path: String::new(),
                 watch: false,
             }),
-            meta_schema_name: Some("greptime_schema".to_string()),
             ..Default::default()
         },
         ..Default::default()

src/common/base/src/lib.rs

@@ -20,7 +20,6 @@ pub mod range_read;
 #[allow(clippy::all)]
 pub mod readable_size;
 pub mod secrets;
-pub mod serde;
 
 pub type AffectedRows = usize;
 

src/common/base/src/serde.rs

@@ -1,31 +0,0 @@
-// Copyright 2023 Greptime Team
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-use serde::{Deserialize, Deserializer};
-
-/// Deserialize an empty string as the default value.
-pub fn empty_string_as_default<'de, D, T>(deserializer: D) -> Result<T, D::Error>
-where
-    D: Deserializer<'de>,
-    T: Default + Deserialize<'de>,
-{
-    let s = String::deserialize(deserializer)?;
-
-    if s.is_empty() {
-        Ok(T::default())
-    } else {
-        T::deserialize(serde::de::value::StringDeserializer::<D::Error>::new(s))
-            .map_err(serde::de::Error::custom)
-    }
-}

src/common/datasource/Cargo.toml

@@ -25,17 +25,19 @@ common-error.workspace = true
 common-macro.workspace = true
 common-recordbatch.workspace = true
 common-runtime.workspace = true
-common-telemetry.workspace = true
 datafusion.workspace = true
-datafusion-orc.workspace = true
 datatypes.workspace = true
+derive_builder.workspace = true
 futures.workspace = true
 lazy_static.workspace = true
 object-store.workspace = true
 object_store_opendal.workspace = true
-orc-rust = { version = "0.6.3", default-features = false, features = ["async"] }
+orc-rust = { git = "https://github.com/datafusion-contrib/orc-rust", rev = "3134cab581a8e91b942d6a23aca2916ea965f6bb", default-features = false, features = [
+    "async",
+] }
 parquet.workspace = true
 paste.workspace = true
+rand.workspace = true
 regex = "1.7"
 serde.workspace = true
 snafu.workspace = true
@@ -45,4 +47,6 @@ tokio-util.workspace = true
 url = "2.3"
 
 [dev-dependencies]
+common-telemetry.workspace = true
 common-test-util.workspace = true
+uuid.workspace = true

src/common/datasource/src/file_format/orc.rs

@@ -12,11 +12,16 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-use arrow_schema::Schema;
+use std::sync::Arc;
+
+use arrow_schema::{ArrowError, Schema, SchemaRef};
 use async_trait::async_trait;
 use bytes::Bytes;
+use common_recordbatch::adapter::RecordBatchStreamTypeAdapter;
+use datafusion::datasource::physical_plan::{FileMeta, FileOpenFuture, FileOpener};
+use datafusion::error::{DataFusionError, Result as DfResult};
 use futures::future::BoxFuture;
-use futures::FutureExt;
+use futures::{FutureExt, StreamExt, TryStreamExt};
 use object_store::ObjectStore;
 use orc_rust::arrow_reader::ArrowReaderBuilder;
 use orc_rust::async_arrow_reader::ArrowStreamReader;
@@ -92,6 +97,67 @@ impl FileFormat for OrcFormat {
     }
 }
 
+#[derive(Debug, Clone)]
+pub struct OrcOpener {
+    object_store: Arc<ObjectStore>,
+    output_schema: SchemaRef,
+    projection: Option<Vec<usize>>,
+}
+
+impl OrcOpener {
+    pub fn new(
+        object_store: ObjectStore,
+        output_schema: SchemaRef,
+        projection: Option<Vec<usize>>,
+    ) -> Self {
+        Self {
+            object_store: Arc::from(object_store),
+            output_schema,
+            projection,
+        }
+    }
+}
+
+impl FileOpener for OrcOpener {
+    fn open(&self, meta: FileMeta) -> DfResult<FileOpenFuture> {
+        let object_store = self.object_store.clone();
+        let projected_schema = if let Some(projection) = &self.projection {
+            let projected_schema = self
+                .output_schema
+                .project(projection)
+                .map_err(|e| DataFusionError::External(Box::new(e)))?;
+            Arc::new(projected_schema)
+        } else {
+            self.output_schema.clone()
+        };
+        let projection = self.projection.clone();
+        Ok(Box::pin(async move {
+            let path = meta.location().to_string();
+
+            let meta = object_store
+                .stat(&path)
+                .await
+                .map_err(|e| DataFusionError::External(Box::new(e)))?;
+
+            let reader = object_store
+                .reader(&path)
+                .await
+                .map_err(|e| DataFusionError::External(Box::new(e)))?;
+
+            let stream_reader =
+                new_orc_stream_reader(ReaderAdapter::new(reader, meta.content_length()))
+                    .await
+                    .map_err(|e| DataFusionError::External(Box::new(e)))?;
+
+            let stream =
+                RecordBatchStreamTypeAdapter::new(projected_schema, stream_reader, projection);
+
+            let adopted = stream.map_err(|e| ArrowError::ExternalError(Box::new(e)));
+            Ok(adopted.boxed())
+        }))
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use common_test_util::find_workspace_path;

src/common/datasource/src/file_format/parquet.rs

@@ -31,7 +31,6 @@ use datatypes::schema::SchemaRef;
 use futures::future::BoxFuture;
 use futures::StreamExt;
 use object_store::{FuturesAsyncReader, ObjectStore};
-use parquet::arrow::arrow_reader::ArrowReaderOptions;
 use parquet::arrow::AsyncArrowWriter;
 use parquet::basic::{Compression, Encoding, ZstdLevel};
 use parquet::file::properties::{WriterProperties, WriterPropertiesBuilder};
@@ -66,7 +65,7 @@ impl FileFormat for ParquetFormat {
             .compat();
 
         let metadata = reader
-            .get_metadata(None)
+            .get_metadata()
             .await
             .context(error::ReadParquetSnafuSnafu)?;
 
@@ -147,7 +146,7 @@ impl LazyParquetFileReader {
 impl AsyncFileReader for LazyParquetFileReader {
     fn get_bytes(
         &mut self,
-        range: std::ops::Range<u64>,
+        range: std::ops::Range<usize>,
     ) -> BoxFuture<'_, ParquetResult<bytes::Bytes>> {
         Box::pin(async move {
             self.maybe_initialize()
@@ -158,16 +157,13 @@ impl AsyncFileReader for LazyParquetFileReader {
         })
     }
 
-    fn get_metadata<'a>(
+    fn get_metadata(&mut self) -> BoxFuture<'_, ParquetResult<Arc<ParquetMetaData>>> {
-        &'a mut self,
-        options: Option<&'a ArrowReaderOptions>,
-    ) -> BoxFuture<'a, parquet::errors::Result<Arc<ParquetMetaData>>> {
         Box::pin(async move {
             self.maybe_initialize()
                 .await
                 .map_err(|e| ParquetError::External(Box::new(e)))?;
             // Safety: Must initialized
-            self.reader.as_mut().unwrap().get_metadata(options).await
+            self.reader.as_mut().unwrap().get_metadata().await
         })
     }
 }

src/common/datasource/src/file_format/tests.rs

@@ -19,39 +19,35 @@ use std::vec;
 
 use common_test_util::find_workspace_path;
 use datafusion::assert_batches_eq;
+use datafusion::datasource::file_format::file_compression_type::FileCompressionType;
 use datafusion::datasource::physical_plan::{
-    CsvSource, FileScanConfig, FileSource, FileStream, JsonSource, ParquetSource,
+    CsvConfig, CsvOpener, FileOpener, FileScanConfig, FileStream, JsonOpener, ParquetExec,
 };
-use datafusion::datasource::source::DataSourceExec;
 use datafusion::execution::context::TaskContext;
 use datafusion::physical_plan::metrics::ExecutionPlanMetricsSet;
 use datafusion::physical_plan::ExecutionPlan;
 use datafusion::prelude::SessionContext;
-use datafusion_orc::OrcSource;
 use futures::StreamExt;
-use object_store::ObjectStore;
 
 use super::FORMAT_TYPE;
+use crate::file_format::orc::{OrcFormat, OrcOpener};
 use crate::file_format::parquet::DefaultParquetFileReaderFactory;
-use crate::file_format::{FileFormat, Format, OrcFormat};
+use crate::file_format::{FileFormat, Format};
 use crate::test_util::{scan_config, test_basic_schema, test_store};
 use crate::{error, test_util};
 
-struct Test<'a> {
+struct Test<'a, T: FileOpener> {
     config: FileScanConfig,
-    file_source: Arc<dyn FileSource>,
+    opener: T,
     expected: Vec<&'a str>,
 }
 
-impl Test<'_> {
+impl<T: FileOpener> Test<'_, T> {
-    async fn run(self, store: &ObjectStore) {
+    pub async fn run(self) {
-        let store = Arc::new(object_store_opendal::OpendalStore::new(store.clone()));
-        let file_opener = self.file_source.create_file_opener(store, &self.config, 0);
-
         let result = FileStream::new(
             &self.config,
             0,
-            file_opener,
+            self.opener,
             &ExecutionPlanMetricsSet::new(),
         )
         .unwrap()
@@ -66,16 +62,26 @@ impl Test<'_> {
 #[tokio::test]
 async fn test_json_opener() {
     let store = test_store("/");
+    let store = Arc::new(object_store_opendal::OpendalStore::new(store));
+
     let schema = test_basic_schema();
-    let file_source = Arc::new(JsonSource::new()).with_batch_size(test_util::TEST_BATCH_SIZE);
+
+    let json_opener = || {
+        JsonOpener::new(
+            test_util::TEST_BATCH_SIZE,
+            schema.clone(),
+            FileCompressionType::UNCOMPRESSED,
+            store.clone(),
+        )
+    };
 
     let path = &find_workspace_path("/src/common/datasource/tests/json/basic.json")
         .display()
         .to_string();
     let tests = [
         Test {
-            config: scan_config(schema.clone(), None, path, file_source.clone()),
+            config: scan_config(schema.clone(), None, path),
-            file_source: file_source.clone(),
+            opener: json_opener(),
             expected: vec![
                 "+-----+-------+",
                 "| num | str   |",
@@ -87,8 +93,8 @@ async fn test_json_opener() {
             ],
         },
         Test {
-            config: scan_config(schema, Some(1), path, file_source.clone()),
+            config: scan_config(schema.clone(), Some(1), path),
-            file_source,
+            opener: json_opener(),
             expected: vec![
                 "+-----+------+",
                 "| num | str  |",
@@ -100,26 +106,37 @@ async fn test_json_opener() {
     ];
 
     for test in tests {
-        test.run(&store).await;
+        test.run().await;
     }
 }
 
 #[tokio::test]
 async fn test_csv_opener() {
     let store = test_store("/");
+    let store = Arc::new(object_store_opendal::OpendalStore::new(store));
+
     let schema = test_basic_schema();
     let path = &find_workspace_path("/src/common/datasource/tests/csv/basic.csv")
         .display()
         .to_string();
+    let csv_config = Arc::new(CsvConfig::new(
+        test_util::TEST_BATCH_SIZE,
+        schema.clone(),
+        None,
+        true,
+        b',',
+        b'"',
+        None,
+        store,
+        None,
+    ));
 
-    let file_source = CsvSource::new(true, b',', b'"')
+    let csv_opener = || CsvOpener::new(csv_config.clone(), FileCompressionType::UNCOMPRESSED);
-        .with_batch_size(test_util::TEST_BATCH_SIZE)
-        .with_schema(schema.clone());
 
     let tests = [
         Test {
-            config: scan_config(schema.clone(), None, path, file_source.clone()),
+            config: scan_config(schema.clone(), None, path),
-            file_source: file_source.clone(),
+            opener: csv_opener(),
             expected: vec![
                 "+-----+-------+",
                 "| num | str   |",
@@ -131,8 +148,8 @@ async fn test_csv_opener() {
             ],
         },
         Test {
-            config: scan_config(schema, Some(1), path, file_source.clone()),
+            config: scan_config(schema.clone(), Some(1), path),
-            file_source,
+            opener: csv_opener(),
             expected: vec![
                 "+-----+------+",
                 "| num | str  |",
@@ -144,7 +161,7 @@ async fn test_csv_opener() {
     ];
 
     for test in tests {
-        test.run(&store).await;
+        test.run().await;
     }
 }
 
@@ -157,12 +174,12 @@ async fn test_parquet_exec() {
     let path = &find_workspace_path("/src/common/datasource/tests/parquet/basic.parquet")
         .display()
         .to_string();
+    let base_config = scan_config(schema.clone(), None, path);
 
-    let parquet_source = ParquetSource::default()
+    let exec = ParquetExec::builder(base_config)
-        .with_parquet_file_reader_factory(Arc::new(DefaultParquetFileReaderFactory::new(store)));
+        .with_parquet_file_reader_factory(Arc::new(DefaultParquetFileReaderFactory::new(store)))
+        .build();
 
-    let config = scan_config(schema, None, path, Arc::new(parquet_source));
-    let exec = DataSourceExec::from_data_source(config);
     let ctx = SessionContext::new();
 
     let context = Arc::new(TaskContext::from(&ctx));
@@ -191,18 +208,20 @@ async fn test_parquet_exec() {
 
 #[tokio::test]
 async fn test_orc_opener() {
-    let path = &find_workspace_path("/src/common/datasource/tests/orc/test.orc")
+    let root = find_workspace_path("/src/common/datasource/tests/orc")
         .display()
         .to_string();
+    let store = test_store(&root);
+    let schema = OrcFormat.infer_schema(&store, "test.orc").await.unwrap();
+    let schema = Arc::new(schema);
 
-    let store = test_store("/");
+    let orc_opener = OrcOpener::new(store.clone(), schema.clone(), None);
-    let schema = Arc::new(OrcFormat.infer_schema(&store, path).await.unwrap());
+    let path = "test.orc";
-    let file_source = Arc::new(OrcSource::default());
 
     let tests = [
         Test {
-            config: scan_config(schema.clone(), None, path, file_source.clone()),
+            config: scan_config(schema.clone(), None, path),
-            file_source: file_source.clone(),
+            opener: orc_opener.clone(),
             expected: vec![
             "+----------+-----+-------+------------+-----+-----+-------+--------------------+------------------------+-----------+---------------+------------+----------------+---------------+-------------------+--------------+---------------+---------------+----------------------------+-------------+",
             "| double_a | a   | b     | str_direct | d   | e   | f     | int_short_repeated | int_neg_short_repeated | int_delta | int_neg_delta | int_direct | int_neg_direct | bigint_direct | bigint_neg_direct | bigint_other | utf8_increase | utf8_decrease | timestamp_simple           | date_simple |",
@@ -216,8 +235,8 @@ async fn test_orc_opener() {
             ],
         },
         Test {
-            config: scan_config(schema.clone(), Some(1), path, file_source.clone()),
+            config: scan_config(schema.clone(), Some(1), path),
-            file_source,
+            opener: orc_opener.clone(),
             expected: vec![
                 "+----------+-----+------+------------+---+-----+-------+--------------------+------------------------+-----------+---------------+------------+----------------+---------------+-------------------+--------------+---------------+---------------+-------------------------+-------------+",
                 "| double_a | a   | b    | str_direct | d | e   | f     | int_short_repeated | int_neg_short_repeated | int_delta | int_neg_delta | int_direct | int_neg_direct | bigint_direct | bigint_neg_direct | bigint_other | utf8_increase | utf8_decrease | timestamp_simple        | date_simple |",
@@ -229,7 +248,7 @@ async fn test_orc_opener() {
     ];
 
     for test in tests {
-        test.run(&store).await;
+        test.run().await;
     }
 }
 

src/common/datasource/src/test_util.rs

@@ -16,12 +16,12 @@ use std::sync::Arc;
 
 use arrow_schema::{DataType, Field, Schema, SchemaRef};
 use common_test_util::temp_dir::{create_temp_dir, TempDir};
+use datafusion::common::{Constraints, Statistics};
 use datafusion::datasource::file_format::file_compression_type::FileCompressionType;
 use datafusion::datasource::listing::PartitionedFile;
 use datafusion::datasource::object_store::ObjectStoreUrl;
 use datafusion::datasource::physical_plan::{
-    CsvSource, FileGroup, FileScanConfig, FileScanConfigBuilder, FileSource, FileStream,
+    CsvConfig, CsvOpener, FileScanConfig, FileStream, JsonOpener,
-    JsonOpener, JsonSource,
 };
 use datafusion::physical_plan::metrics::ExecutionPlanMetricsSet;
 use object_store::services::Fs;
@@ -68,20 +68,21 @@ pub fn test_basic_schema() -> SchemaRef {
     Arc::new(schema)
 }
 
-pub(crate) fn scan_config(
+pub fn scan_config(file_schema: SchemaRef, limit: Option<usize>, filename: &str) -> FileScanConfig {
-    file_schema: SchemaRef,
-    limit: Option<usize>,
-    filename: &str,
-    file_source: Arc<dyn FileSource>,
-) -> FileScanConfig {
     // object_store only recognize the Unix style path, so make it happy.
     let filename = &filename.replace('\\', "/");
-    let file_group = FileGroup::new(vec![PartitionedFile::new(filename.to_string(), 4096)]);
+    let statistics = Statistics::new_unknown(file_schema.as_ref());
-
+    FileScanConfig {
-    FileScanConfigBuilder::new(ObjectStoreUrl::local_filesystem(), file_schema, file_source)
+        object_store_url: ObjectStoreUrl::parse("empty://").unwrap(), // won't be used
-        .with_file_group(file_group)
+        file_schema,
-        .with_limit(limit)
+        file_groups: vec![vec![PartitionedFile::new(filename.to_string(), 10)]],
-        .build()
+        constraints: Constraints::empty(),
+        statistics,
+        projection: None,
+        limit,
+        table_partition_cols: vec![],
+        output_ordering: vec![],
+    }
 }
 
 pub async fn setup_stream_to_json_test(origin_path: &str, threshold: impl Fn(usize) -> usize) {
@@ -98,14 +99,9 @@ pub async fn setup_stream_to_json_test(origin_path: &str, threshold: impl Fn(usi
 
     let size = store.read(origin_path).await.unwrap().len();
 
-    let config = scan_config(schema, None, origin_path, Arc::new(JsonSource::new()));
+    let config = scan_config(schema.clone(), None, origin_path);
-    let stream = FileStream::new(
+
-        &config,
+    let stream = FileStream::new(&config, 0, json_opener, &ExecutionPlanMetricsSet::new()).unwrap();
-        0,
-        Arc::new(json_opener),
-        &ExecutionPlanMetricsSet::new(),
-    )
-    .unwrap();
 
     let (tmp_store, dir) = test_tmp_store("test_stream_to_json");
 
@@ -131,17 +127,24 @@ pub async fn setup_stream_to_csv_test(origin_path: &str, threshold: impl Fn(usiz
 
     let schema = test_basic_schema();
 
-    let csv_source = CsvSource::new(true, b',', b'"')
+    let csv_config = Arc::new(CsvConfig::new(
-        .with_schema(schema.clone())
+        TEST_BATCH_SIZE,
-        .with_batch_size(TEST_BATCH_SIZE);
+        schema.clone(),
-    let config = scan_config(schema, None, origin_path, csv_source.clone());
+        None,
+        true,
+        b',',
+        b'"',
+        None,
+        Arc::new(object_store_opendal::OpendalStore::new(store.clone())),
+        None,
+    ));
+
+    let csv_opener = CsvOpener::new(csv_config, FileCompressionType::UNCOMPRESSED);
+
     let size = store.read(origin_path).await.unwrap().len();
 
-    let csv_opener = csv_source.create_file_opener(
+    let config = scan_config(schema.clone(), None, origin_path);
-        Arc::new(object_store_opendal::OpendalStore::new(store.clone())),
+
-        &config,
-        0,
-    );
     let stream = FileStream::new(&config, 0, csv_opener, &ExecutionPlanMetricsSet::new()).unwrap();
 
     let (tmp_store, dir) = test_tmp_store("test_stream_to_csv");

src/common/error/src/status_code.rs

@@ -251,6 +251,7 @@ macro_rules! define_from_tonic_status {
                         .get(key)
                         .and_then(|v| String::from_utf8(v.as_bytes().to_vec()).ok())
                 }
+
                 let code = metadata_value(&e, $crate::GREPTIME_DB_HEADER_ERROR_CODE)
                     .and_then(|s| {
                         if let Ok(code) = s.parse::<u32>() {
@@ -289,8 +290,6 @@ macro_rules! define_into_tonic_status {
                 use tonic::metadata::MetadataMap;
                 use $crate::GREPTIME_DB_HEADER_ERROR_CODE;
 
-                common_telemetry::error!(err; "Failed to handle request");
-
                 let mut headers = HeaderMap::<HeaderValue>::with_capacity(2);
 
                 // If either of the status_code or error msg cannot convert to valid HTTP header value

src/common/event-recorder/Cargo.toml

@@ -12,9 +12,6 @@ common-error.workspace = true
 common-macro.workspace = true
 common-telemetry.workspace = true
 common-time.workspace = true
-humantime.workspace = true
-humantime-serde.workspace = true
-itertools.workspace = true
 serde.workspace = true
 serde_json.workspace = true
 snafu.workspace = true

src/common/event-recorder/src/error.rs

@@ -22,6 +22,12 @@ use snafu::{Location, Snafu};
 #[snafu(visibility(pub))]
 #[stack_trace_debug]
 pub enum Error {
+    #[snafu(display("No available frontend"))]
+    NoAvailableFrontend {
+        #[snafu(implicit)]
+        location: Location,
+    },
+
     #[snafu(display("Mismatched schema, expected: {:?}, actual: {:?}", expected, actual))]
     MismatchedSchema {
         #[snafu(implicit)]
@@ -63,7 +69,9 @@ impl ErrorExt for Error {
             Error::MismatchedSchema { .. } | Error::SerializeEvent { .. } => {
                 StatusCode::InvalidArguments
             }
-            Error::InsertEvents { .. } | Error::KvBackend { .. } => StatusCode::Internal,
+            Error::NoAvailableFrontend { .. }
+            | Error::InsertEvents { .. }
+            | Error::KvBackend { .. } => StatusCode::Internal,
         }
     }
 

src/common/event-recorder/src/lib.rs

@@ -12,8 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#![feature(duration_constructors)]
-
 pub mod error;
 pub mod recorder;
 

src/common/event-recorder/src/recorder.rs

@@ -15,7 +15,7 @@
 use std::any::Any;
 use std::collections::HashMap;
 use std::fmt::Debug;
-use std::sync::Arc;
+use std::sync::{Arc, OnceLock};
 use std::time::Duration;
 
 use api::v1::column_data_type_extension::TypeExt;
@@ -28,8 +28,6 @@ use async_trait::async_trait;
 use backon::{BackoffBuilder, ExponentialBuilder};
 use common_telemetry::{debug, error, info, warn};
 use common_time::timestamp::{TimeUnit, Timestamp};
-use humantime::format_duration;
-use itertools::Itertools;
 use serde::{Deserialize, Serialize};
 use store_api::mito_engine_options::{APPEND_MODE_KEY, TTL_KEY};
 use tokio::sync::mpsc::{channel, Receiver, Sender};
@@ -52,12 +50,12 @@ pub const EVENTS_TABLE_TIMESTAMP_COLUMN_NAME: &str = "timestamp";
 /// EventRecorderRef is the reference to the event recorder.
 pub type EventRecorderRef = Arc<dyn EventRecorder>;
 
+static EVENTS_TABLE_TTL: OnceLock<String> = OnceLock::new();
+
 /// The time interval for flushing batched events to the event handler.
 pub const DEFAULT_FLUSH_INTERVAL_SECONDS: Duration = Duration::from_secs(5);
-/// The default TTL(90 days) for the events table.
+// The default TTL for the events table.
-const DEFAULT_EVENTS_TABLE_TTL: Duration = Duration::from_days(90);
+const DEFAULT_EVENTS_TABLE_TTL: &str = "30d";
-/// The default compaction time window for the events table.
-pub const DEFAULT_COMPACTION_TIME_WINDOW: Duration = Duration::from_days(1);
 // The capacity of the tokio channel for transmitting events to background processor.
 const DEFAULT_CHANNEL_SIZE: usize = 2048;
 // The size of the buffer for batching events before flushing to event handler.
@@ -74,11 +72,6 @@ const DEFAULT_MAX_RETRY_TIMES: u64 = 3;
 ///
 /// The event can also add the extra schema and row to the event by overriding the `extra_schema` and `extra_row` methods.
 pub trait Event: Send + Sync + Debug {
-    /// Returns the table name of the event.
-    fn table_name(&self) -> &str {
-        DEFAULT_EVENTS_TABLE_NAME
-    }
-
     /// Returns the type of the event.
     fn event_type(&self) -> &str;
 
@@ -114,68 +107,88 @@ pub trait Eventable: Send + Sync + Debug {
     }
 }
 
-/// Groups events by its `event_type`.
+/// Returns the hints for the insert operation.
-#[allow(clippy::borrowed_box)]
+pub fn insert_hints() -> Vec<(&'static str, &'static str)> {
-pub fn group_events_by_type(events: &[Box<dyn Event>]) -> HashMap<&str, Vec<&Box<dyn Event>>> {
+    vec![
-    events
+        (
-        .iter()
+            TTL_KEY,
-        .into_grouping_map_by(|event| event.event_type())
+            EVENTS_TABLE_TTL
-        .collect()
+                .get()
+                .map(|s| s.as_str())
+                .unwrap_or(DEFAULT_EVENTS_TABLE_TTL),
+        ),
+        (APPEND_MODE_KEY, "true"),
+    ]
 }
 
-/// Builds the row inserts request for the events that will be persisted to the events table. The `events` should have the same event type, or it will return an error.
+/// Builds the row inserts request for the events that will be persisted to the events table.
-#[allow(clippy::borrowed_box)]
+pub fn build_row_inserts_request(events: &[Box<dyn Event>]) -> Result<RowInsertRequests> {
-pub fn build_row_inserts_request(events: &[&Box<dyn Event>]) -> Result<RowInsertRequests> {
+    // Aggregate the events by the event type.
-    // Ensure all the events are the same type.
+    let mut event_groups: HashMap<&str, Vec<&Box<dyn Event>>> = HashMap::new();
-    validate_events(events)?;
 
-    // We already validated the events, so it's safe to get the first event to build the schema for the RowInsertRequest.
-    let event = &events[0];
-    let mut schema: Vec<ColumnSchema> = Vec::with_capacity(3 + event.extra_schema().len());
-    schema.extend(vec![
-        ColumnSchema {
-            column_name: EVENTS_TABLE_TYPE_COLUMN_NAME.to_string(),
-            datatype: ColumnDataType::String.into(),
-            semantic_type: SemanticType::Tag.into(),
-            ..Default::default()
-        },
-        ColumnSchema {
-            column_name: EVENTS_TABLE_PAYLOAD_COLUMN_NAME.to_string(),
-            datatype: ColumnDataType::Binary as i32,
-            semantic_type: SemanticType::Field as i32,
-            datatype_extension: Some(ColumnDataTypeExtension {
-                type_ext: Some(TypeExt::JsonType(JsonTypeExtension::JsonBinary.into())),
-            }),
-            ..Default::default()
-        },
-        ColumnSchema {
-            column_name: EVENTS_TABLE_TIMESTAMP_COLUMN_NAME.to_string(),
-            datatype: ColumnDataType::TimestampNanosecond.into(),
-            semantic_type: SemanticType::Timestamp.into(),
-            ..Default::default()
-        },
-    ]);
-    schema.extend(event.extra_schema());
-
-    let mut rows: Vec<Row> = Vec::with_capacity(events.len());
     for event in events {
-        let extra_row = event.extra_row()?;
+        event_groups
-        let mut values = Vec::with_capacity(3 + extra_row.values.len());
+            .entry(event.event_type())
-        values.extend([
+            .or_default()
-            ValueData::StringValue(event.event_type().to_string()).into(),
+            .push(event);
-            ValueData::BinaryValue(event.json_payload()?.into_bytes()).into(),
-            ValueData::TimestampNanosecondValue(event.timestamp().value()).into(),
-        ]);
-        values.extend(extra_row.values);
-        rows.push(Row { values });
     }
 
-    Ok(RowInsertRequests {
+    let mut row_insert_requests = RowInsertRequests {
-        inserts: vec![RowInsertRequest {
+        inserts: Vec::with_capacity(event_groups.len()),
-            table_name: event.table_name().to_string(),
+    };
+
+    for (_, events) in event_groups {
+        validate_events(&events)?;
+
+        // We already validated the events, so it's safe to get the first event to build the schema for the RowInsertRequest.
+        let event = &events[0];
+        let mut schema = vec![
+            ColumnSchema {
+                column_name: EVENTS_TABLE_TYPE_COLUMN_NAME.to_string(),
+                datatype: ColumnDataType::String.into(),
+                semantic_type: SemanticType::Tag.into(),
+                ..Default::default()
+            },
+            ColumnSchema {
+                column_name: EVENTS_TABLE_PAYLOAD_COLUMN_NAME.to_string(),
+                datatype: ColumnDataType::Binary as i32,
+                semantic_type: SemanticType::Field as i32,
+                datatype_extension: Some(ColumnDataTypeExtension {
+                    type_ext: Some(TypeExt::JsonType(JsonTypeExtension::JsonBinary.into())),
+                }),
+                ..Default::default()
+            },
+            ColumnSchema {
+                column_name: EVENTS_TABLE_TIMESTAMP_COLUMN_NAME.to_string(),
+                datatype: ColumnDataType::TimestampNanosecond.into(),
+                semantic_type: SemanticType::Timestamp.into(),
+                ..Default::default()
+            },
+        ];
+        schema.extend(event.extra_schema());
+
+        let rows = events
+            .iter()
+            .map(|event| {
+                let mut row = Row {
+                    values: vec![
+                        ValueData::StringValue(event.event_type().to_string()).into(),
+                        ValueData::BinaryValue(event.json_payload()?.as_bytes().to_vec()).into(),
+                        ValueData::TimestampNanosecondValue(event.timestamp().value()).into(),
+                    ],
+                };
+                row.values.extend(event.extra_row()?.values);
+                Ok(row)
+            })
+            .collect::<Result<Vec<_>>>()?;
+
+        row_insert_requests.inserts.push(RowInsertRequest {
+            table_name: DEFAULT_EVENTS_TABLE_NAME.to_string(),
             rows: Some(Rows { schema, rows }),
-        }],
+        });
-    })
+    }
+
+    Ok(row_insert_requests)
 }
 
 // Ensure the events with the same event type have the same extra schema.
@@ -204,34 +217,6 @@ pub trait EventRecorder: Send + Sync + Debug + 'static {
     fn close(&self);
 }
 
-/// EventHandlerOptions is the options for the event handler.
-#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq)]
-pub struct EventHandlerOptions {
-    /// TTL for the events table that will be used to store the events.
-    pub ttl: Duration,
-    /// Append mode for the events table that will be used to store the events.
-    pub append_mode: bool,
-}
-
-impl Default for EventHandlerOptions {
-    fn default() -> Self {
-        Self {
-            ttl: DEFAULT_EVENTS_TABLE_TTL,
-            append_mode: true,
-        }
-    }
-}
-
-impl EventHandlerOptions {
-    /// Converts the options to the hints for the insert operation.
-    pub fn to_hints(&self) -> Vec<(&str, String)> {
-        vec![
-            (TTL_KEY, format_duration(self.ttl).to_string()),
-            (APPEND_MODE_KEY, self.append_mode.to_string()),
-        ]
-    }
-}
-
 /// EventHandler trait defines the interface for how to handle the event.
 #[async_trait]
 pub trait EventHandler: Send + Sync + 'static {
@@ -244,14 +229,13 @@ pub trait EventHandler: Send + Sync + 'static {
 #[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq)]
 pub struct EventRecorderOptions {
     /// TTL for the events table that will be used to store the events.
-    #[serde(with = "humantime_serde")]
+    pub ttl: String,
-    pub ttl: Duration,
 }
 
 impl Default for EventRecorderOptions {
     fn default() -> Self {
         Self {
-            ttl: DEFAULT_EVENTS_TABLE_TTL,
+            ttl: DEFAULT_EVENTS_TABLE_TTL.to_string(),
         }
     }
 }
@@ -268,7 +252,9 @@ pub struct EventRecorderImpl {
 }
 
 impl EventRecorderImpl {
-    pub fn new(event_handler: Box<dyn EventHandler>) -> Self {
+    pub fn new(event_handler: Box<dyn EventHandler>, opts: EventRecorderOptions) -> Self {
+        info!("Creating event recorder with options: {:?}", opts);
+
         let (tx, rx) = channel(DEFAULT_CHANNEL_SIZE);
         let cancel_token = CancellationToken::new();
 
@@ -293,6 +279,14 @@ impl EventRecorderImpl {
 
         recorder.handle = Some(handle);
 
+        // It only sets the ttl once, so it's safe to skip the error.
+        if EVENTS_TABLE_TTL.set(opts.ttl.clone()).is_err() {
+            info!(
+                "Events table ttl already set to {}, skip setting it",
+                opts.ttl
+            );
+        }
+
         recorder
     }
 }
@@ -477,7 +471,10 @@ mod tests {
 
     #[tokio::test]
     async fn test_event_recorder() {
-        let mut event_recorder = EventRecorderImpl::new(Box::new(TestEventHandlerImpl {}));
+        let mut event_recorder = EventRecorderImpl::new(
+            Box::new(TestEventHandlerImpl {}),
+            EventRecorderOptions::default(),
+        );
         event_recorder.record(Box::new(TestEvent {}));
 
         // Sleep for a while to let the event be sent to the event handler.
@@ -518,8 +515,10 @@ mod tests {
 
     #[tokio::test]
     async fn test_event_recorder_should_panic() {
-        let mut event_recorder =
+        let mut event_recorder = EventRecorderImpl::new(
-            EventRecorderImpl::new(Box::new(TestEventHandlerImplShouldPanic {}));
+            Box::new(TestEventHandlerImplShouldPanic {}),
+            EventRecorderOptions::default(),
+        );
 
         event_recorder.record(Box::new(TestEvent {}));
 
@@ -536,135 +535,4 @@ mod tests {
             assert!(handle.await.unwrap_err().is_panic());
         }
     }
-
-    #[derive(Debug)]
-    struct TestEventA {}
-
-    impl Event for TestEventA {
-        fn event_type(&self) -> &str {
-            "A"
-        }
-
-        fn as_any(&self) -> &dyn Any {
-            self
-        }
-    }
-
-    #[derive(Debug)]
-    struct TestEventB {}
-
-    impl Event for TestEventB {
-        fn table_name(&self) -> &str {
-            "table_B"
-        }
-
-        fn event_type(&self) -> &str {
-            "B"
-        }
-
-        fn as_any(&self) -> &dyn Any {
-            self
-        }
-    }
-
-    #[derive(Debug)]
-    struct TestEventC {}
-
-    impl Event for TestEventC {
-        fn table_name(&self) -> &str {
-            "table_C"
-        }
-
-        fn event_type(&self) -> &str {
-            "C"
-        }
-
-        fn as_any(&self) -> &dyn Any {
-            self
-        }
-    }
-
-    #[test]
-    fn test_group_events_by_type() {
-        let events: Vec<Box<dyn Event>> = vec![
-            Box::new(TestEventA {}),
-            Box::new(TestEventB {}),
-            Box::new(TestEventA {}),
-            Box::new(TestEventC {}),
-            Box::new(TestEventB {}),
-            Box::new(TestEventC {}),
-            Box::new(TestEventA {}),
-        ];
-
-        let event_groups = group_events_by_type(&events);
-        assert_eq!(event_groups.len(), 3);
-        assert_eq!(event_groups.get("A").unwrap().len(), 3);
-        assert_eq!(event_groups.get("B").unwrap().len(), 2);
-        assert_eq!(event_groups.get("C").unwrap().len(), 2);
-    }
-
-    #[test]
-    fn test_build_row_inserts_request() {
-        let events: Vec<Box<dyn Event>> = vec![
-            Box::new(TestEventA {}),
-            Box::new(TestEventB {}),
-            Box::new(TestEventA {}),
-            Box::new(TestEventC {}),
-            Box::new(TestEventB {}),
-            Box::new(TestEventC {}),
-            Box::new(TestEventA {}),
-        ];
-
-        let event_groups = group_events_by_type(&events);
-        assert_eq!(event_groups.len(), 3);
-        assert_eq!(event_groups.get("A").unwrap().len(), 3);
-        assert_eq!(event_groups.get("B").unwrap().len(), 2);
-        assert_eq!(event_groups.get("C").unwrap().len(), 2);
-
-        for (event_type, events) in event_groups {
-            let row_inserts_request = build_row_inserts_request(&events).unwrap();
-            if event_type == "A" {
-                assert_eq!(row_inserts_request.inserts.len(), 1);
-                assert_eq!(
-                    row_inserts_request.inserts[0].table_name,
-                    DEFAULT_EVENTS_TABLE_NAME
-                );
-                assert_eq!(
-                    row_inserts_request.inserts[0]
-                        .rows
-                        .as_ref()
-                        .unwrap()
-                        .rows
-                        .len(),
-                    3
-                );
-            } else if event_type == "B" {
-                assert_eq!(row_inserts_request.inserts.len(), 1);
-                assert_eq!(row_inserts_request.inserts[0].table_name, "table_B");
-                assert_eq!(
-                    row_inserts_request.inserts[0]
-                        .rows
-                        .as_ref()
-                        .unwrap()
-                        .rows
-                        .len(),
-                    2
-                );
-            } else if event_type == "C" {
-                assert_eq!(row_inserts_request.inserts.len(), 1);
-                assert_eq!(row_inserts_request.inserts[0].table_name, "table_C");
-                assert_eq!(
-                    row_inserts_request.inserts[0]
-                        .rows
-                        .as_ref()
-                        .unwrap()
-                        .rows
-                        .len(),
-                    2
-                );
-            } else {
-                panic!("Unexpected event type: {}", event_type);
-            }
-        }
-    }
 }

src/common/frontend/Cargo.toml

@@ -5,18 +5,13 @@ edition.workspace = true
 license.workspace = true
 
 [dependencies]
-api.workspace = true
 async-trait.workspace = true
 common-error.workspace = true
-common-event-recorder.workspace = true
 common-grpc.workspace = true
 common-macro.workspace = true
 common-meta.workspace = true
-common-time.workspace = true
 greptime-proto.workspace = true
-humantime.workspace = true
 meta-client.workspace = true
-serde.workspace = true
 session.workspace = true
 snafu.workspace = true
 tonic.workspace = true

src/common/frontend/src/slow_query_event.rs

@@ -12,121 +12,17 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-use std::any::Any;
+use session::context::QueryContextRef;
 
-use api::v1::value::ValueData;
+#[derive(Debug)]
-use api::v1::{ColumnDataType, ColumnSchema, Row, SemanticType};
-use common_event_recorder::error::Result;
-use common_event_recorder::Event;
-use serde::Serialize;
-
-pub const SLOW_QUERY_TABLE_NAME: &str = "slow_queries";
-pub const SLOW_QUERY_TABLE_COST_COLUMN_NAME: &str = "cost";
-pub const SLOW_QUERY_TABLE_THRESHOLD_COLUMN_NAME: &str = "threshold";
-pub const SLOW_QUERY_TABLE_QUERY_COLUMN_NAME: &str = "query";
-pub const SLOW_QUERY_TABLE_TIMESTAMP_COLUMN_NAME: &str = "timestamp";
-pub const SLOW_QUERY_TABLE_IS_PROMQL_COLUMN_NAME: &str = "is_promql";
-pub const SLOW_QUERY_TABLE_PROMQL_START_COLUMN_NAME: &str = "promql_start";
-pub const SLOW_QUERY_TABLE_PROMQL_END_COLUMN_NAME: &str = "promql_end";
-pub const SLOW_QUERY_TABLE_PROMQL_RANGE_COLUMN_NAME: &str = "promql_range";
-pub const SLOW_QUERY_TABLE_PROMQL_STEP_COLUMN_NAME: &str = "promql_step";
-pub const SLOW_QUERY_EVENT_TYPE: &str = "slow_query";
-
-/// SlowQueryEvent is the event of slow query.
-#[derive(Debug, Serialize)]
 pub struct SlowQueryEvent {
     pub cost: u64,
     pub threshold: u64,
     pub query: String,
     pub is_promql: bool,
+    pub query_ctx: QueryContextRef,
     pub promql_range: Option<u64>,
     pub promql_step: Option<u64>,
     pub promql_start: Option<i64>,
     pub promql_end: Option<i64>,
 }
-
-impl Event for SlowQueryEvent {
-    fn table_name(&self) -> &str {
-        SLOW_QUERY_TABLE_NAME
-    }
-
-    fn event_type(&self) -> &str {
-        SLOW_QUERY_EVENT_TYPE
-    }
-
-    fn extra_schema(&self) -> Vec<ColumnSchema> {
-        vec![
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_COST_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::Uint64.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_THRESHOLD_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::Uint64.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_QUERY_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::String.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_IS_PROMQL_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::Boolean.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_PROMQL_RANGE_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::Uint64.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_PROMQL_STEP_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::Uint64.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_PROMQL_START_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::TimestampMillisecond.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-            ColumnSchema {
-                column_name: SLOW_QUERY_TABLE_PROMQL_END_COLUMN_NAME.to_string(),
-                datatype: ColumnDataType::TimestampMillisecond.into(),
-                semantic_type: SemanticType::Field.into(),
-                ..Default::default()
-            },
-        ]
-    }
-
-    fn extra_row(&self) -> Result<Row> {
-        Ok(Row {
-            values: vec![
-                ValueData::U64Value(self.cost).into(),
-                ValueData::U64Value(self.threshold).into(),
-                ValueData::StringValue(self.query.to_string()).into(),
-                ValueData::BoolValue(self.is_promql).into(),
-                ValueData::U64Value(self.promql_range.unwrap_or(0)).into(),
-                ValueData::U64Value(self.promql_step.unwrap_or(0)).into(),
-                ValueData::TimestampMillisecondValue(self.promql_start.unwrap_or(0)).into(),
-                ValueData::TimestampMillisecondValue(self.promql_end.unwrap_or(0)).into(),
-            ],
-        })
-    }
-
-    fn json_payload(&self) -> Result<String> {
-        Ok("".to_string())
-    }
-
-    fn as_any(&self) -> &dyn Any {
-        self
-    }
-}

src/common/function/Cargo.toml

@@ -57,6 +57,7 @@ serde_json.workspace = true
 session.workspace = true
 snafu.workspace = true
 sql.workspace = true
+statrs = "0.16"
 store-api.workspace = true
 table.workspace = true
 uddsketch = { git = "https://github.com/GreptimeTeam/timescaledb-toolkit.git", rev = "84828fe8fb494a6a61412a3da96517fc80f7bb20" }

src/common/function/src/admin.rs

@@ -21,6 +21,8 @@ mod reconcile_database;
 mod reconcile_table;
 mod remove_region_follower;
 
+use std::sync::Arc;
+
 use add_region_follower::AddRegionFollowerFunction;
 use flush_compact_region::{CompactRegionFunction, FlushRegionFunction};
 use flush_compact_table::{CompactTableFunction, FlushTableFunction};
@@ -33,22 +35,22 @@ use remove_region_follower::RemoveRegionFollowerFunction;
 use crate::flush_flow::FlushFlowFunction;
 use crate::function_registry::FunctionRegistry;
 
-/// Administration functions
+/// Table functions
 pub(crate) struct AdminFunction;
 
 impl AdminFunction {
-    /// Register all admin functions to [`FunctionRegistry`].
+    /// Register all table functions to [`FunctionRegistry`].
     pub fn register(registry: &FunctionRegistry) {
-        registry.register(MigrateRegionFunction::factory());
+        registry.register_async(Arc::new(MigrateRegionFunction));
-        registry.register(AddRegionFollowerFunction::factory());
+        registry.register_async(Arc::new(AddRegionFollowerFunction));
-        registry.register(RemoveRegionFollowerFunction::factory());
+        registry.register_async(Arc::new(RemoveRegionFollowerFunction));
-        registry.register(FlushRegionFunction::factory());
+        registry.register_async(Arc::new(FlushRegionFunction));
-        registry.register(CompactRegionFunction::factory());
+        registry.register_async(Arc::new(CompactRegionFunction));
-        registry.register(FlushTableFunction::factory());
+        registry.register_async(Arc::new(FlushTableFunction));
-        registry.register(CompactTableFunction::factory());
+        registry.register_async(Arc::new(CompactTableFunction));
-        registry.register(FlushFlowFunction::factory());
+        registry.register_async(Arc::new(FlushFlowFunction));
-        registry.register(ReconcileCatalogFunction::factory());
+        registry.register_async(Arc::new(ReconcileCatalogFunction));
-        registry.register(ReconcileDatabaseFunction::factory());
+        registry.register_async(Arc::new(ReconcileDatabaseFunction));
-        registry.register(ReconcileTableFunction::factory());
+        registry.register_async(Arc::new(ReconcileTableFunction));
     }
 }

src/common/function/src/admin/add_region_follower.rs

@@ -18,8 +18,7 @@ use common_query::error::{
     InvalidFuncArgsSnafu, MissingProcedureServiceHandlerSnafu, Result,
     UnsupportedInputDataTypeSnafu,
 };
-use datafusion_expr::{Signature, TypeSignature, Volatility};
+use common_query::prelude::{Signature, TypeSignature, Volatility};
-use datatypes::data_type::DataType;
 use datatypes::prelude::ConcreteDataType;
 use datatypes::value::{Value, ValueRef};
 use session::context::QueryContextRef;
@@ -83,13 +82,7 @@ fn signature() -> Signature {
     Signature::one_of(
         vec![
             // add_region_follower(region_id, peer)
-            TypeSignature::Uniform(
+            TypeSignature::Uniform(2, ConcreteDataType::numerics()),
-                2,
-                ConcreteDataType::numerics()
-                    .into_iter()
-                    .map(|dt| dt.as_arrow_type())
-                    .collect(),
-            ),
         ],
         Volatility::Immutable,
     )
@@ -99,57 +92,38 @@ fn signature() -> Signature {
 mod tests {
     use std::sync::Arc;
 
-    use arrow::array::UInt64Array;
+    use common_query::prelude::TypeSignature;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::{UInt64Vector, VectorRef};
-    use datafusion_expr::ColumnarValue;
 
     use super::*;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[test]
     fn test_add_region_follower_misc() {
-        let factory: ScalarFunctionFactory = AddRegionFollowerFunction::factory().into();
+        let f = AddRegionFollowerFunction;
-        let f = factory.provide(FunctionContext::mock());
         assert_eq!("add_region_follower", f.name());
-        assert_eq!(DataType::UInt64, f.return_type(&[]).unwrap());
+        assert_eq!(
+            ConcreteDataType::uint64_datatype(),
+            f.return_type(&[]).unwrap()
+        );
         assert!(matches!(f.signature(),
-                         datafusion_expr::Signature {
+                         Signature {
-                             type_signature: datafusion_expr::TypeSignature::OneOf(sigs),
+                             type_signature: TypeSignature::OneOf(sigs),
-                             volatility: datafusion_expr::Volatility::Immutable
+                             volatility: Volatility::Immutable
                          } if sigs.len() == 1));
     }
 
     #[tokio::test]
     async fn test_add_region_follower() {
-        let factory: ScalarFunctionFactory = AddRegionFollowerFunction::factory().into();
+        let f = AddRegionFollowerFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![1, 1];
-        let f = provider.as_async().unwrap();
+        let args = args
+            .into_iter()
+            .map(|arg| Arc::new(UInt64Vector::from_slice([arg])) as _)
+            .collect::<Vec<_>>();
 
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-            args: vec![
+        let expect: VectorRef = Arc::new(UInt64Vector::from_slice([0u64]));
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
+        assert_eq!(result, expect);
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![2]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::UInt64, false)),
-                Arc::new(Field::new("arg_1", DataType::UInt64, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::UInt64, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<UInt64Array>().unwrap();
-                assert_eq!(result_array.value(0), 0u64);
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(scalar, datafusion_common::ScalarValue::UInt64(Some(0)));
-            }
-        }
     }
 }

src/common/function/src/admin/flush_compact_region.rs

@@ -16,8 +16,7 @@ use common_macro::admin_fn;
 use common_query::error::{
     InvalidFuncArgsSnafu, MissingTableMutationHandlerSnafu, Result, UnsupportedInputDataTypeSnafu,
 };
-use datafusion_expr::{Signature, Volatility};
+use common_query::prelude::{Signature, Volatility};
-use datatypes::data_type::DataType;
 use datatypes::prelude::*;
 use session::context::QueryContextRef;
 use snafu::ensure;
@@ -67,99 +66,71 @@ define_region_function!(FlushRegionFunction, flush_region, flush_region);
 define_region_function!(CompactRegionFunction, compact_region, compact_region);
 
 fn signature() -> Signature {
-    Signature::uniform(
+    Signature::uniform(1, ConcreteDataType::numerics(), Volatility::Immutable)
-        1,
-        ConcreteDataType::numerics()
-            .into_iter()
-            .map(|dt| dt.as_arrow_type())
-            .collect(),
-        Volatility::Immutable,
-    )
 }
 
 #[cfg(test)]
 mod tests {
     use std::sync::Arc;
 
-    use arrow::array::UInt64Array;
+    use common_query::prelude::TypeSignature;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::UInt64Vector;
-    use datafusion_expr::ColumnarValue;
 
     use super::*;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     macro_rules! define_region_function_test {
         ($name: ident, $func: ident) => {
             paste::paste! {
                 #[test]
                 fn [<test_ $name _misc>]() {
-                    let factory: ScalarFunctionFactory = $func::factory().into();
+                    let f = $func;
-                    let f = factory.provide(FunctionContext::mock());
                     assert_eq!(stringify!($name), f.name());
                     assert_eq!(
-                        DataType::UInt64,
+                        ConcreteDataType::uint64_datatype(),
                         f.return_type(&[]).unwrap()
                     );
                     assert!(matches!(f.signature(),
-                                     datafusion_expr::Signature {
+                                     Signature {
-                                         type_signature: datafusion_expr::TypeSignature::Uniform(1, valid_types),
+                                         type_signature: TypeSignature::Uniform(1, valid_types),
-                                         volatility: datafusion_expr::Volatility::Immutable
+                                         volatility: Volatility::Immutable
-                                     } if valid_types == &ConcreteDataType::numerics().into_iter().map(|dt| { use datatypes::data_type::DataType; dt.as_arrow_type() }).collect::<Vec<_>>()));
+                                     } if valid_types == ConcreteDataType::numerics()));
                 }
 
                 #[tokio::test]
                 async fn [<test_ $name _missing_table_mutation>]() {
-                    let factory: ScalarFunctionFactory = $func::factory().into();
+                    let f = $func;
-                    let provider = factory.provide(FunctionContext::default());
-                    let f = provider.as_async().unwrap();
 
-                    let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+                    let args = vec![99];
-                        args: vec![
+
-                            ColumnarValue::Array(Arc::new(UInt64Array::from(vec![99]))),
+                    let args = args
-                        ],
+                        .into_iter()
-                        arg_fields: vec![
+                        .map(|arg| Arc::new(UInt64Vector::from_slice([arg])) as _)
-                            Arc::new(Field::new("arg_0", DataType::UInt64, false)),
+                        .collect::<Vec<_>>();
-                        ],
+
-                        return_field: Arc::new(Field::new("result", DataType::UInt64, true)),
+                    let result = f.eval(FunctionContext::default(), &args).await.unwrap_err();
-                        number_rows: 1,
-                        config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-                    };
-                    let result = f.invoke_async_with_args(func_args).await.unwrap_err();
                     assert_eq!(
-                        "Execution error: Handler error: Missing TableMutationHandler, not expected",
+                        "Missing TableMutationHandler, not expected",
                         result.to_string()
                     );
                 }
 
                 #[tokio::test]
                 async fn [<test_ $name>]() {
-                    let factory: ScalarFunctionFactory = $func::factory().into();
+                    let f = $func;
-                    let provider = factory.provide(FunctionContext::mock());
-                    let f = provider.as_async().unwrap();
 
-                    let func_args = datafusion::logical_expr::ScalarFunctionArgs {
-                        args: vec![
-                            ColumnarValue::Array(Arc::new(UInt64Array::from(vec![99]))),
-                        ],
-                        arg_fields: vec![
-                            Arc::new(Field::new("arg_0", DataType::UInt64, false)),
-                        ],
-                        return_field: Arc::new(Field::new("result", DataType::UInt64, true)),
-                        number_rows: 1,
-                        config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-                    };
-                    let result = f.invoke_async_with_args(func_args).await.unwrap();
 
-                    match result {
+                    let args = vec![99];
-                        ColumnarValue::Array(array) => {
+
-                            let result_array = array.as_any().downcast_ref::<UInt64Array>().unwrap();
+                    let args = args
-                            assert_eq!(result_array.value(0), 42u64);
+                        .into_iter()
-                        }
+                        .map(|arg| Arc::new(UInt64Vector::from_slice([arg])) as _)
-                        ColumnarValue::Scalar(scalar) => {
+                        .collect::<Vec<_>>();
-                            assert_eq!(scalar, datafusion_common::ScalarValue::UInt64(Some(42)));
+
-                        }
+                    let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                    }
+
+                    let expect: VectorRef = Arc::new(UInt64Vector::from_slice([42]));
+                    assert_eq!(expect, result);
                 }
             }
         };

src/common/function/src/admin/flush_compact_table.rs

@@ -15,15 +15,14 @@
 use std::str::FromStr;
 
 use api::v1::region::{compact_request, StrictWindow};
-use arrow::datatypes::DataType as ArrowDataType;
 use common_error::ext::BoxedError;
 use common_macro::admin_fn;
 use common_query::error::{
     InvalidFuncArgsSnafu, MissingTableMutationHandlerSnafu, Result, TableMutationSnafu,
     UnsupportedInputDataTypeSnafu,
 };
+use common_query::prelude::{Signature, Volatility};
 use common_telemetry::info;
-use datafusion_expr::{Signature, Volatility};
 use datatypes::prelude::*;
 use session::context::QueryContextRef;
 use session::table_name::table_name_to_full_name;
@@ -106,11 +105,18 @@ pub(crate) async fn compact_table(
 }
 
 fn flush_signature() -> Signature {
-    Signature::uniform(1, vec![ArrowDataType::Utf8], Volatility::Immutable)
+    Signature::uniform(
+        1,
+        vec![ConcreteDataType::string_datatype()],
+        Volatility::Immutable,
+    )
 }
 
 fn compact_signature() -> Signature {
-    Signature::variadic(vec![ArrowDataType::Utf8], Volatility::Immutable)
+    Signature::variadic(
+        vec![ConcreteDataType::string_datatype()],
+        Volatility::Immutable,
+    )
 }
 
 /// Parses `compact_table` UDF parameters. This function accepts following combinations:
@@ -198,87 +204,66 @@ mod tests {
     use std::sync::Arc;
 
     use api::v1::region::compact_request::Options;
-    use arrow::array::StringArray;
-    use arrow::datatypes::{DataType, Field};
     use common_catalog::consts::{DEFAULT_CATALOG_NAME, DEFAULT_SCHEMA_NAME};
-    use datafusion_expr::ColumnarValue;
+    use common_query::prelude::TypeSignature;
+    use datatypes::vectors::{StringVector, UInt64Vector};
     use session::context::QueryContext;
 
     use super::*;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     macro_rules! define_table_function_test {
         ($name: ident, $func: ident) => {
             paste::paste!{
                 #[test]
                 fn [<test_ $name _misc>]() {
-                    let factory: ScalarFunctionFactory = $func::factory().into();
+                    let f = $func;
-                    let f = factory.provide(FunctionContext::mock());
                     assert_eq!(stringify!($name), f.name());
                     assert_eq!(
-                        DataType::UInt64,
+                        ConcreteDataType::uint64_datatype(),
                         f.return_type(&[]).unwrap()
                     );
                     assert!(matches!(f.signature(),
-                                     datafusion_expr::Signature {
+                                     Signature {
-                                         type_signature: datafusion_expr::TypeSignature::Uniform(1, valid_types),
+                                         type_signature: TypeSignature::Uniform(1, valid_types),
-                                         volatility: datafusion_expr::Volatility::Immutable
+                                         volatility: Volatility::Immutable
-                                     } if valid_types == &vec![ArrowDataType::Utf8]));
+                                     } if valid_types == vec![ConcreteDataType::string_datatype()]));
                 }
 
                 #[tokio::test]
                 async fn [<test_ $name _missing_table_mutation>]() {
-                    let factory: ScalarFunctionFactory = $func::factory().into();
+                    let f = $func;
-                    let provider = factory.provide(FunctionContext::default());
-                    let f = provider.as_async().unwrap();
 
-                    let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+                    let args = vec!["test"];
-                        args: vec![
+
-                            ColumnarValue::Array(Arc::new(StringArray::from(vec!["test"]))),
+                    let args = args
-                        ],
+                        .into_iter()
-                        arg_fields: vec![
+                        .map(|arg| Arc::new(StringVector::from(vec![arg])) as _)
-                            Arc::new(Field::new("arg_0", DataType::Utf8, false)),
+                        .collect::<Vec<_>>();
-                        ],
+
-                        return_field: Arc::new(Field::new("result", DataType::UInt64, true)),
+                    let result = f.eval(FunctionContext::default(), &args).await.unwrap_err();
-                        number_rows: 1,
-                        config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-                    };
-                    let result = f.invoke_async_with_args(func_args).await.unwrap_err();
                     assert_eq!(
-                        "Execution error: Handler error: Missing TableMutationHandler, not expected",
+                        "Missing TableMutationHandler, not expected",
                         result.to_string()
                     );
                 }
 
                 #[tokio::test]
                 async fn [<test_ $name>]() {
-                    let factory: ScalarFunctionFactory = $func::factory().into();
+                    let f = $func;
-                    let provider = factory.provide(FunctionContext::mock());
-                    let f = provider.as_async().unwrap();
 
-                    let func_args = datafusion::logical_expr::ScalarFunctionArgs {
-                        args: vec![
-                            ColumnarValue::Array(Arc::new(StringArray::from(vec!["test"]))),
-                        ],
-                        arg_fields: vec![
-                            Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                        ],
-                        return_field: Arc::new(Field::new("result", DataType::UInt64, true)),
-                        number_rows: 1,
-                        config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-                    };
-                    let result = f.invoke_async_with_args(func_args).await.unwrap();
 
-                    match result {
+                    let args = vec!["test"];
-                        ColumnarValue::Array(array) => {
+
-                            let result_array = array.as_any().downcast_ref::<arrow::array::UInt64Array>().unwrap();
+                    let args = args
-                            assert_eq!(result_array.value(0), 42u64);
+                        .into_iter()
-                        }
+                        .map(|arg| Arc::new(StringVector::from(vec![arg])) as _)
-                        ColumnarValue::Scalar(scalar) => {
+                        .collect::<Vec<_>>();
-                            assert_eq!(scalar, datafusion_common::ScalarValue::UInt64(Some(42)));
+
-                        }
+                    let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                    }
+
+                    let expect: VectorRef = Arc::new(UInt64Vector::from_slice([42]));
+                    assert_eq!(expect, result);
                 }
             }
         }

src/common/function/src/admin/migrate_region.rs

@@ -17,8 +17,7 @@ use std::time::Duration;
 use common_macro::admin_fn;
 use common_meta::rpc::procedure::MigrateRegionRequest;
 use common_query::error::{InvalidFuncArgsSnafu, MissingProcedureServiceHandlerSnafu, Result};
-use datafusion_expr::{Signature, TypeSignature, Volatility};
+use common_query::prelude::{Signature, TypeSignature, Volatility};
-use datatypes::data_type::DataType;
 use datatypes::prelude::ConcreteDataType;
 use datatypes::value::{Value, ValueRef};
 use session::context::QueryContextRef;
@@ -104,21 +103,9 @@ fn signature() -> Signature {
     Signature::one_of(
         vec![
             // migrate_region(region_id, from_peer, to_peer)
-            TypeSignature::Uniform(
+            TypeSignature::Uniform(3, ConcreteDataType::numerics()),
-                3,
-                ConcreteDataType::numerics()
-                    .into_iter()
-                    .map(|dt| dt.as_arrow_type())
-                    .collect(),
-            ),
             // migrate_region(region_id, from_peer, to_peer, timeout(secs))
-            TypeSignature::Uniform(
+            TypeSignature::Uniform(4, ConcreteDataType::numerics()),
-                4,
-                ConcreteDataType::numerics()
-                    .into_iter()
-                    .map(|dt| dt.as_arrow_type())
-                    .collect(),
-            ),
         ],
         Volatility::Immutable,
     )
@@ -128,89 +115,59 @@ fn signature() -> Signature {
 mod tests {
     use std::sync::Arc;
 
-    use arrow::array::{StringArray, UInt64Array};
+    use common_query::prelude::TypeSignature;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::{StringVector, UInt64Vector, VectorRef};
-    use datafusion_expr::ColumnarValue;
 
     use super::*;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[test]
     fn test_migrate_region_misc() {
-        let factory: ScalarFunctionFactory = MigrateRegionFunction::factory().into();
+        let f = MigrateRegionFunction;
-        let f = factory.provide(FunctionContext::mock());
         assert_eq!("migrate_region", f.name());
-        assert_eq!(DataType::Utf8, f.return_type(&[]).unwrap());
+        assert_eq!(
+            ConcreteDataType::string_datatype(),
+            f.return_type(&[]).unwrap()
+        );
         assert!(matches!(f.signature(),
-                         datafusion_expr::Signature {
+                         Signature {
-                             type_signature: datafusion_expr::TypeSignature::OneOf(sigs),
+                             type_signature: TypeSignature::OneOf(sigs),
-                             volatility: datafusion_expr::Volatility::Immutable
+                             volatility: Volatility::Immutable
                          } if sigs.len() == 2));
     }
 
     #[tokio::test]
     async fn test_missing_procedure_service() {
-        let factory: ScalarFunctionFactory = MigrateRegionFunction::factory().into();
+        let f = MigrateRegionFunction;
-        let provider = factory.provide(FunctionContext::default());
-        let f = provider.as_async().unwrap();
 
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        let args = vec![1, 1, 1];
-            args: vec![
+
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
+        let args = args
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
+            .into_iter()
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
+            .map(|arg| Arc::new(UInt64Vector::from_slice([arg])) as _)
-            ],
+            .collect::<Vec<_>>();
-            arg_fields: vec![
+
-                Arc::new(Field::new("arg_0", DataType::UInt64, false)),
+        let result = f.eval(FunctionContext::default(), &args).await.unwrap_err();
-                Arc::new(Field::new("arg_1", DataType::UInt64, false)),
-                Arc::new(Field::new("arg_2", DataType::UInt64, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap_err();
         assert_eq!(
-            "Execution error: Handler error: Missing ProcedureServiceHandler, not expected",
+            "Missing ProcedureServiceHandler, not expected",
             result.to_string()
         );
     }
 
     #[tokio::test]
     async fn test_migrate_region() {
-        let factory: ScalarFunctionFactory = MigrateRegionFunction::factory().into();
+        let f = MigrateRegionFunction;
-        let provider = factory.provide(FunctionContext::mock());
-        let f = provider.as_async().unwrap();
 
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        let args = vec![1, 1, 1];
-            args: vec![
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::UInt64, false)),
-                Arc::new(Field::new("arg_1", DataType::UInt64, false)),
-                Arc::new(Field::new("arg_2", DataType::UInt64, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
 
-        match result {
+        let args = args
-            ColumnarValue::Array(array) => {
+            .into_iter()
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
+            .map(|arg| Arc::new(UInt64Vector::from_slice([arg])) as _)
-                assert_eq!(result_array.value(0), "test_pid");
+            .collect::<Vec<_>>();
-            }
+
-            ColumnarValue::Scalar(scalar) => {
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                assert_eq!(
+
-                    scalar,
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
+        assert_eq!(expect, result);
-                );
-            }
-        }
     }
 }

src/common/function/src/admin/reconcile_catalog.rs

@@ -14,15 +14,13 @@
 
 use api::v1::meta::reconcile_request::Target;
 use api::v1::meta::{ReconcileCatalog, ReconcileRequest};
-use arrow::datatypes::DataType as ArrowDataType;
 use common_macro::admin_fn;
 use common_query::error::{
     InvalidFuncArgsSnafu, MissingProcedureServiceHandlerSnafu, Result,
     UnsupportedInputDataTypeSnafu,
 };
+use common_query::prelude::{Signature, TypeSignature, Volatility};
 use common_telemetry::info;
-use datafusion_expr::{Signature, TypeSignature, Volatility};
-use datatypes::data_type::DataType;
 use datatypes::prelude::*;
 use session::context::QueryContextRef;
 
@@ -106,15 +104,15 @@ fn signature() -> Signature {
     let mut signs = Vec::with_capacity(2 + nums.len());
     signs.extend([
         // reconcile_catalog()
-        TypeSignature::Nullary,
+        TypeSignature::NullAry,
         // reconcile_catalog(resolve_strategy)
-        TypeSignature::Exact(vec![ArrowDataType::Utf8]),
+        TypeSignature::Exact(vec![ConcreteDataType::string_datatype()]),
     ]);
     for sign in nums {
         // reconcile_catalog(resolve_strategy, parallelism)
         signs.push(TypeSignature::Exact(vec![
-            ArrowDataType::Utf8,
+            ConcreteDataType::string_datatype(),
-            sign.as_arrow_type(),
+            sign,
         ]));
     }
     Signature::one_of(signs, Volatility::Immutable)
@@ -122,149 +120,60 @@ fn signature() -> Signature {
 
 #[cfg(test)]
 mod tests {
+    use std::assert_matches::assert_matches;
     use std::sync::Arc;
 
-    use arrow::array::{StringArray, UInt64Array};
+    use common_query::error::Error;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::{StringVector, UInt64Vector, VectorRef};
-    use datafusion_expr::ColumnarValue;
 
     use crate::admin::reconcile_catalog::ReconcileCatalogFunction;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[tokio::test]
     async fn test_reconcile_catalog() {
         common_telemetry::init_default_ut_logging();
 
         // reconcile_catalog()
-        let factory: ScalarFunctionFactory = ReconcileCatalogFunction::factory().into();
+        let f = ReconcileCatalogFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![];
-        let f = provider.as_async().unwrap();
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        assert_eq!(expect, result);
-            args: vec![],
-            arg_fields: vec![],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // reconcile_catalog(resolve_strategy)
-        let factory: ScalarFunctionFactory = ReconcileCatalogFunction::factory().into();
+        let f = ReconcileCatalogFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![Arc::new(StringVector::from(vec!["UseMetasrv"])) as _];
-        let f = provider.as_async().unwrap();
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        assert_eq!(expect, result);
-            args: vec![ColumnarValue::Array(Arc::new(StringArray::from(vec![
-                "UseMetasrv",
-            ])))],
-            arg_fields: vec![Arc::new(Field::new("arg_0", DataType::Utf8, false))],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // reconcile_catalog(resolve_strategy, parallelism)
-        let factory: ScalarFunctionFactory = ReconcileCatalogFunction::factory().into();
+        let f = ReconcileCatalogFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["UseLatest"])) as _,
-
+            Arc::new(UInt64Vector::from_slice([10])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        ];
-            args: vec![
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseLatest"]))),
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![10]))),
+        assert_eq!(expect, result);
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::UInt64, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // unsupported input data type
-        let factory: ScalarFunctionFactory = ReconcileCatalogFunction::factory().into();
+        let f = ReconcileCatalogFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["UseLatest"])) as _,
-
+            Arc::new(StringVector::from(vec!["test"])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        ];
-            args: vec![
+        let err = f.eval(FunctionContext::mock(), &args).await.unwrap_err();
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseLatest"]))),
+        assert_matches!(err, Error::UnsupportedInputDataType { .. });
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["test"]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::Utf8, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let _err = f.invoke_async_with_args(func_args).await.unwrap_err();
-        // Note: Error type is DataFusionError at this level, not common_query::Error
 
         // invalid function args
-        let factory: ScalarFunctionFactory = ReconcileCatalogFunction::factory().into();
+        let f = ReconcileCatalogFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["UseLatest"])) as _,
-
+            Arc::new(UInt64Vector::from_slice([10])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+            Arc::new(StringVector::from(vec!["10"])) as _,
-            args: vec![
+        ];
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseLatest"]))),
+        let err = f.eval(FunctionContext::mock(), &args).await.unwrap_err();
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![10]))),
+        assert_matches!(err, Error::InvalidFuncArgs { .. });
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["10"]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::UInt64, false)),
-                Arc::new(Field::new("arg_2", DataType::Utf8, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let _err = f.invoke_async_with_args(func_args).await.unwrap_err();
-        // Note: Error type is DataFusionError at this level, not common_query::Error
     }
 }

src/common/function/src/admin/reconcile_database.rs

@@ -14,15 +14,13 @@
 
 use api::v1::meta::reconcile_request::Target;
 use api::v1::meta::{ReconcileDatabase, ReconcileRequest};
-use arrow::datatypes::DataType as ArrowDataType;
 use common_macro::admin_fn;
 use common_query::error::{
     InvalidFuncArgsSnafu, MissingProcedureServiceHandlerSnafu, Result,
     UnsupportedInputDataTypeSnafu,
 };
+use common_query::prelude::{Signature, TypeSignature, Volatility};
 use common_telemetry::info;
-use datafusion_expr::{Signature, TypeSignature, Volatility};
-use datatypes::data_type::DataType;
 use datatypes::prelude::*;
 use session::context::QueryContextRef;
 
@@ -115,16 +113,19 @@ fn signature() -> Signature {
     let mut signs = Vec::with_capacity(2 + nums.len());
     signs.extend([
         // reconcile_database(datanode_name)
-        TypeSignature::Exact(vec![ArrowDataType::Utf8]),
+        TypeSignature::Exact(vec![ConcreteDataType::string_datatype()]),
         // reconcile_database(database_name, resolve_strategy)
-        TypeSignature::Exact(vec![ArrowDataType::Utf8, ArrowDataType::Utf8]),
+        TypeSignature::Exact(vec![
+            ConcreteDataType::string_datatype(),
+            ConcreteDataType::string_datatype(),
+        ]),
     ]);
     for sign in nums {
         // reconcile_database(database_name, resolve_strategy, parallelism)
         signs.push(TypeSignature::Exact(vec![
-            ArrowDataType::Utf8,
+            ConcreteDataType::string_datatype(),
-            ArrowDataType::Utf8,
+            ConcreteDataType::string_datatype(),
-            sign.as_arrow_type(),
+            sign,
         ]));
     }
     Signature::one_of(signs, Volatility::Immutable)
@@ -132,160 +133,66 @@ fn signature() -> Signature {
 
 #[cfg(test)]
 mod tests {
+    use std::assert_matches::assert_matches;
     use std::sync::Arc;
 
-    use arrow::array::{StringArray, UInt32Array};
+    use common_query::error::Error;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::{StringVector, UInt32Vector, VectorRef};
-    use datafusion_expr::ColumnarValue;
 
     use crate::admin::reconcile_database::ReconcileDatabaseFunction;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[tokio::test]
     async fn test_reconcile_catalog() {
         common_telemetry::init_default_ut_logging();
 
         // reconcile_database(database_name)
-        let factory: ScalarFunctionFactory = ReconcileDatabaseFunction::factory().into();
+        let f = ReconcileDatabaseFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![Arc::new(StringVector::from(vec!["test"])) as _];
-        let f = provider.as_async().unwrap();
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        assert_eq!(expect, result);
-            args: vec![ColumnarValue::Array(Arc::new(StringArray::from(vec![
-                "test",
-            ])))],
-            arg_fields: vec![Arc::new(Field::new("arg_0", DataType::Utf8, false))],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // reconcile_database(database_name, resolve_strategy)
-        let factory: ScalarFunctionFactory = ReconcileDatabaseFunction::factory().into();
+        let f = ReconcileDatabaseFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["test"])) as _,
-
+            Arc::new(StringVector::from(vec!["UseLatest"])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        ];
-            args: vec![
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["test"]))),
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseLatest"]))),
+        assert_eq!(expect, result);
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::Utf8, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // reconcile_database(database_name, resolve_strategy, parallelism)
-        let factory: ScalarFunctionFactory = ReconcileDatabaseFunction::factory().into();
+        let f = ReconcileDatabaseFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["test"])) as _,
-
+            Arc::new(StringVector::from(vec!["UseLatest"])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+            Arc::new(UInt32Vector::from_slice([10])) as _,
-            args: vec![
+        ];
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["test"]))),
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseLatest"]))),
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-                ColumnarValue::Array(Arc::new(UInt32Array::from(vec![10]))),
+        assert_eq!(expect, result);
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_2", DataType::UInt32, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // invalid function args
-        let factory: ScalarFunctionFactory = ReconcileDatabaseFunction::factory().into();
+        let f = ReconcileDatabaseFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["UseLatest"])) as _,
-
+            Arc::new(UInt32Vector::from_slice([10])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+            Arc::new(StringVector::from(vec!["v1"])) as _,
-            args: vec![
+            Arc::new(StringVector::from(vec!["v2"])) as _,
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseLatest"]))),
+        ];
-                ColumnarValue::Array(Arc::new(UInt32Array::from(vec![10]))),
+        let err = f.eval(FunctionContext::mock(), &args).await.unwrap_err();
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["v1"]))),
+        assert_matches!(err, Error::InvalidFuncArgs { .. });
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["v2"]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::UInt32, false)),
-                Arc::new(Field::new("arg_2", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_3", DataType::Utf8, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let _err = f.invoke_async_with_args(func_args).await.unwrap_err();
-        // Note: Error type is DataFusionError at this level, not common_query::Error
 
         // unsupported input data type
-        let factory: ScalarFunctionFactory = ReconcileDatabaseFunction::factory().into();
+        let f = ReconcileDatabaseFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["UseLatest"])) as _,
-
+            Arc::new(UInt32Vector::from_slice([10])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+            Arc::new(StringVector::from(vec!["v1"])) as _,
-            args: vec![
+        ];
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseLatest"]))),
+        let err = f.eval(FunctionContext::mock(), &args).await.unwrap_err();
-                ColumnarValue::Array(Arc::new(UInt32Array::from(vec![10]))),
+        assert_matches!(err, Error::UnsupportedInputDataType { .. });
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["v1"]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::UInt32, false)),
-                Arc::new(Field::new("arg_2", DataType::Utf8, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let _err = f.invoke_async_with_args(func_args).await.unwrap_err();
-        // Note: Error type is DataFusionError at this level, not common_query::Error
     }
 }

src/common/function/src/admin/reconcile_table.rs

@@ -14,15 +14,14 @@
 
 use api::v1::meta::reconcile_request::Target;
 use api::v1::meta::{ReconcileRequest, ReconcileTable, ResolveStrategy};
-use arrow::datatypes::DataType as ArrowDataType;
 use common_catalog::format_full_table_name;
 use common_error::ext::BoxedError;
 use common_macro::admin_fn;
 use common_query::error::{
     MissingProcedureServiceHandlerSnafu, Result, TableMutationSnafu, UnsupportedInputDataTypeSnafu,
 };
+use common_query::prelude::{Signature, TypeSignature, Volatility};
 use common_telemetry::info;
-use datafusion_expr::{Signature, TypeSignature, Volatility};
 use datatypes::prelude::*;
 use session::context::QueryContextRef;
 use session::table_name::table_name_to_full_name;
@@ -94,9 +93,12 @@ fn signature() -> Signature {
     Signature::one_of(
         vec![
             // reconcile_table(table_name)
-            TypeSignature::Exact(vec![ArrowDataType::Utf8]),
+            TypeSignature::Exact(vec![ConcreteDataType::string_datatype()]),
             // reconcile_table(table_name, resolve_strategy)
-            TypeSignature::Exact(vec![ArrowDataType::Utf8, ArrowDataType::Utf8]),
+            TypeSignature::Exact(vec![
+                ConcreteDataType::string_datatype(),
+                ConcreteDataType::string_datatype(),
+            ]),
         ],
         Volatility::Immutable,
     )
@@ -104,101 +106,44 @@ fn signature() -> Signature {
 
 #[cfg(test)]
 mod tests {
+    use std::assert_matches::assert_matches;
     use std::sync::Arc;
 
-    use arrow::array::StringArray;
+    use common_query::error::Error;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::{StringVector, VectorRef};
-    use datafusion_expr::ColumnarValue;
 
     use crate::admin::reconcile_table::ReconcileTableFunction;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[tokio::test]
     async fn test_reconcile_table() {
         common_telemetry::init_default_ut_logging();
 
         // reconcile_table(table_name)
-        let factory: ScalarFunctionFactory = ReconcileTableFunction::factory().into();
+        let f = ReconcileTableFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![Arc::new(StringVector::from(vec!["test"])) as _];
-        let f = provider.as_async().unwrap();
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        assert_eq!(expect, result);
-            args: vec![ColumnarValue::Array(Arc::new(StringArray::from(vec![
-                "test",
-            ])))],
-            arg_fields: vec![Arc::new(Field::new("arg_0", DataType::Utf8, false))],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // reconcile_table(table_name, resolve_strategy)
-        let factory: ScalarFunctionFactory = ReconcileTableFunction::factory().into();
+        let f = ReconcileTableFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["test"])) as _,
-
+            Arc::new(StringVector::from(vec!["UseMetasrv"])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        ];
-            args: vec![
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["test"]))),
+        let expect: VectorRef = Arc::new(StringVector::from(vec!["test_pid"]));
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseMetasrv"]))),
+        assert_eq!(expect, result);
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::Utf8, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
-                assert_eq!(result_array.value(0), "test_pid");
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(
-                    scalar,
-                    datafusion_common::ScalarValue::Utf8(Some("test_pid".to_string()))
-                );
-            }
-        }
 
         // unsupported input data type
-        let factory: ScalarFunctionFactory = ReconcileTableFunction::factory().into();
+        let f = ReconcileTableFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![
-        let f = provider.as_async().unwrap();
+            Arc::new(StringVector::from(vec!["test"])) as _,
-
+            Arc::new(StringVector::from(vec!["UseMetasrv"])) as _,
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+            Arc::new(StringVector::from(vec!["10"])) as _,
-            args: vec![
+        ];
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["test"]))),
+        let err = f.eval(FunctionContext::mock(), &args).await.unwrap_err();
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["UseMetasrv"]))),
+        assert_matches!(err, Error::UnsupportedInputDataType { .. });
-                ColumnarValue::Array(Arc::new(StringArray::from(vec!["10"]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_1", DataType::Utf8, false)),
-                Arc::new(Field::new("arg_2", DataType::Utf8, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let _err = f.invoke_async_with_args(func_args).await.unwrap_err();
-        // Note: Error type is DataFusionError at this level, not common_query::Error
     }
 }

src/common/function/src/admin/remove_region_follower.rs

@@ -18,8 +18,7 @@ use common_query::error::{
     InvalidFuncArgsSnafu, MissingProcedureServiceHandlerSnafu, Result,
     UnsupportedInputDataTypeSnafu,
 };
-use datafusion_expr::{Signature, TypeSignature, Volatility};
+use common_query::prelude::{Signature, TypeSignature, Volatility};
-use datatypes::data_type::DataType;
 use datatypes::prelude::ConcreteDataType;
 use datatypes::value::{Value, ValueRef};
 use session::context::QueryContextRef;
@@ -83,13 +82,7 @@ fn signature() -> Signature {
     Signature::one_of(
         vec![
             // remove_region_follower(region_id, peer_id)
-            TypeSignature::Uniform(
+            TypeSignature::Uniform(2, ConcreteDataType::numerics()),
-                2,
-                ConcreteDataType::numerics()
-                    .into_iter()
-                    .map(|dt| dt.as_arrow_type())
-                    .collect(),
-            ),
         ],
         Volatility::Immutable,
     )
@@ -99,57 +92,38 @@ fn signature() -> Signature {
 mod tests {
     use std::sync::Arc;
 
-    use arrow::array::UInt64Array;
+    use common_query::prelude::TypeSignature;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::{UInt64Vector, VectorRef};
-    use datafusion_expr::ColumnarValue;
 
     use super::*;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[test]
     fn test_remove_region_follower_misc() {
-        let factory: ScalarFunctionFactory = RemoveRegionFollowerFunction::factory().into();
+        let f = RemoveRegionFollowerFunction;
-        let f = factory.provide(FunctionContext::mock());
         assert_eq!("remove_region_follower", f.name());
-        assert_eq!(DataType::UInt64, f.return_type(&[]).unwrap());
+        assert_eq!(
+            ConcreteDataType::uint64_datatype(),
+            f.return_type(&[]).unwrap()
+        );
         assert!(matches!(f.signature(),
-                         datafusion_expr::Signature {
+                         Signature {
-                             type_signature: datafusion_expr::TypeSignature::OneOf(sigs),
+                             type_signature: TypeSignature::OneOf(sigs),
-                             volatility: datafusion_expr::Volatility::Immutable
+                             volatility: Volatility::Immutable
                          } if sigs.len() == 1));
     }
 
     #[tokio::test]
     async fn test_remove_region_follower() {
-        let factory: ScalarFunctionFactory = RemoveRegionFollowerFunction::factory().into();
+        let f = RemoveRegionFollowerFunction;
-        let provider = factory.provide(FunctionContext::mock());
+        let args = vec![1, 1];
-        let f = provider.as_async().unwrap();
+        let args = args
+            .into_iter()
+            .map(|arg| Arc::new(UInt64Vector::from_slice([arg])) as _)
+            .collect::<Vec<_>>();
 
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-            args: vec![
+        let expect: VectorRef = Arc::new(UInt64Vector::from_slice([0u64]));
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
+        assert_eq!(result, expect);
-                ColumnarValue::Array(Arc::new(UInt64Array::from(vec![1]))),
-            ],
-            arg_fields: vec![
-                Arc::new(Field::new("arg_0", DataType::UInt64, false)),
-                Arc::new(Field::new("arg_1", DataType::UInt64, false)),
-            ],
-            return_field: Arc::new(Field::new("result", DataType::UInt64, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
-
-        match result {
-            ColumnarValue::Array(array) => {
-                let result_array = array.as_any().downcast_ref::<UInt64Array>().unwrap();
-                assert_eq!(result_array.value(0), 0u64);
-            }
-            ColumnarValue::Scalar(scalar) => {
-                assert_eq!(scalar, datafusion_common::ScalarValue::UInt64(Some(0)));
-            }
-        }
     }
 }

src/common/function/src/aggrs/aggr_wrapper.rs

@@ -25,14 +25,14 @@
 use std::sync::Arc;
 
 use arrow::array::StructArray;
-use arrow_schema::{FieldRef, Fields};
+use arrow_schema::Fields;
 use common_telemetry::debug;
 use datafusion::functions_aggregate::all_default_aggregate_functions;
 use datafusion::optimizer::analyzer::type_coercion::TypeCoercion;
 use datafusion::optimizer::AnalyzerRule;
 use datafusion::physical_planner::create_aggregate_expr_and_maybe_filter;
 use datafusion_common::{Column, ScalarValue};
-use datafusion_expr::expr::{AggregateFunction, AggregateFunctionParams};
+use datafusion_expr::expr::AggregateFunction;
 use datafusion_expr::function::StateFieldsArgs;
 use datafusion_expr::{
     Accumulator, Aggregate, AggregateUDF, AggregateUDFImpl, Expr, ExprSchemable, LogicalPlan,
@@ -146,7 +146,6 @@ impl StateMergeHelper {
             };
 
             let original_input_types = aggr_func
-                .params
                 .args
                 .iter()
                 .map(|e| e.get_type(&aggr.input.schema()))
@@ -157,7 +156,11 @@ impl StateMergeHelper {
 
             let expr = AggregateFunction {
                 func: Arc::new(state_func.into()),
-                params: aggr_func.params.clone(),
+                args: aggr_func.args.clone(),
+                distinct: aggr_func.distinct,
+                filter: aggr_func.filter.clone(),
+                order_by: aggr_func.order_by.clone(),
+                null_treatment: aggr_func.null_treatment,
             };
             let expr = Expr::AggregateFunction(expr);
             let lower_state_output_col_name = expr.schema_name().to_string();
@@ -179,10 +182,11 @@ impl StateMergeHelper {
             let arg = Expr::Column(Column::new_unqualified(lower_state_output_col_name));
             let expr = AggregateFunction {
                 func: Arc::new(merge_func.into()),
-                params: AggregateFunctionParams {
+                args: vec![arg],
-                    args: vec![arg],
+                distinct: aggr_func.distinct,
-                    ..aggr_func.params.clone()
+                filter: aggr_func.filter.clone(),
-                },
+                order_by: aggr_func.order_by.clone(),
+                null_treatment: aggr_func.null_treatment,
             };
 
             // alias to the original aggregate expr's schema name, so parent plan can refer to it
@@ -243,8 +247,15 @@ impl StateWrapper {
     pub fn deduce_aggr_return_type(
         &self,
         acc_args: &datafusion_expr::function::AccumulatorArgs,
-    ) -> datafusion_common::Result<FieldRef> {
+    ) -> datafusion_common::Result<DataType> {
-        self.inner.return_field(acc_args.schema.fields())
+        let input_exprs = acc_args.exprs;
+        let input_schema = acc_args.schema;
+        let input_types = input_exprs
+            .iter()
+            .map(|e| e.data_type(input_schema))
+            .collect::<Result<Vec<_>, _>>()?;
+        let return_type = self.inner.return_type(&input_types)?;
+        Ok(return_type)
     }
 }
 
@@ -254,13 +265,14 @@ impl AggregateUDFImpl for StateWrapper {
         acc_args: datafusion_expr::function::AccumulatorArgs<'b>,
     ) -> datafusion_common::Result<Box<dyn Accumulator>> {
         // fix and recover proper acc args for the original aggregate function.
-        let state_type = acc_args.return_type().clone();
+        let state_type = acc_args.return_type.clone();
         let inner = {
+            let old_return_type = self.deduce_aggr_return_type(&acc_args)?;
             let acc_args = datafusion_expr::function::AccumulatorArgs {
-                return_field: self.deduce_aggr_return_type(&acc_args)?,
+                return_type: &old_return_type,
                 schema: acc_args.schema,
                 ignore_nulls: acc_args.ignore_nulls,
-                order_bys: acc_args.order_bys,
+                ordering_req: acc_args.ordering_req,
                 is_reversed: acc_args.is_reversed,
                 name: acc_args.name,
                 is_distinct: acc_args.is_distinct,
@@ -285,15 +297,11 @@ impl AggregateUDFImpl for StateWrapper {
     /// Return state_fields as the output struct type.
     ///
     fn return_type(&self, arg_types: &[DataType]) -> datafusion_common::Result<DataType> {
-        let input_fields = &arg_types
+        let old_return_type = self.inner.return_type(arg_types)?;
-            .iter()
-            .map(|x| Arc::new(Field::new("x", x.clone(), false)))
-            .collect::<Vec<_>>();
-
         let state_fields_args = StateFieldsArgs {
             name: self.inner().name(),
-            input_fields,
+            input_types: arg_types,
-            return_field: self.inner.return_field(input_fields)?,
+            return_type: &old_return_type,
             // TODO(discord9): how to get this?, probably ok?
             ordering_fields: &[],
             is_distinct: false,
@@ -307,11 +315,12 @@ impl AggregateUDFImpl for StateWrapper {
     fn state_fields(
         &self,
         args: datafusion_expr::function::StateFieldsArgs,
-    ) -> datafusion_common::Result<Vec<FieldRef>> {
+    ) -> datafusion_common::Result<Vec<Field>> {
+        let old_return_type = self.inner.return_type(args.input_types)?;
         let state_fields_args = StateFieldsArgs {
             name: args.name,
-            input_fields: args.input_fields,
+            input_types: args.input_types,
-            return_field: self.inner.return_field(args.input_fields)?,
+            return_type: &old_return_type,
             ordering_fields: args.ordering_fields,
             is_distinct: args.is_distinct,
         };
@@ -493,7 +502,7 @@ impl AggregateUDFImpl for MergeWrapper {
     fn state_fields(
         &self,
         _args: datafusion_expr::function::StateFieldsArgs,
-    ) -> datafusion_common::Result<Vec<FieldRef>> {
+    ) -> datafusion_common::Result<Vec<Field>> {
         self.original_phy_expr.state_fields()
     }
 }

src/common/function/src/aggrs/aggr_wrapper/tests.rs

@@ -35,7 +35,7 @@ use datafusion::prelude::SessionContext;
 use datafusion_common::{Column, TableReference};
 use datafusion_expr::expr::AggregateFunction;
 use datafusion_expr::sqlparser::ast::NullTreatment;
-use datafusion_expr::{lit, Aggregate, Expr, LogicalPlan, SortExpr, TableScan};
+use datafusion_expr::{Aggregate, Expr, LogicalPlan, SortExpr, TableScan};
 use datafusion_physical_expr::aggregate::AggregateExprBuilder;
 use datafusion_physical_expr::{EquivalenceProperties, Partitioning};
 use datatypes::arrow_array::StringArray;
@@ -234,7 +234,7 @@ async fn test_sum_udaf() {
             vec![Expr::Column(Column::new_unqualified("number"))],
             false,
             None,
-            vec![],
+            None,
             None,
         ))],
     )
@@ -250,7 +250,7 @@ async fn test_sum_udaf() {
                 vec![Expr::Column(Column::new_unqualified("number"))],
                 false,
                 None,
-                vec![],
+                None,
                 None,
             ))],
         )
@@ -290,7 +290,7 @@ async fn test_sum_udaf() {
                 vec![Expr::Column(Column::new_unqualified("__sum_state(number)"))],
                 false,
                 None,
-                vec![],
+                None,
                 None,
             ))
             .alias("sum(number)")],
@@ -378,7 +378,7 @@ async fn test_avg_udaf() {
             vec![Expr::Column(Column::new_unqualified("number"))],
             false,
             None,
-            vec![],
+            None,
             None,
         ))],
     )
@@ -395,7 +395,7 @@ async fn test_avg_udaf() {
                 vec![Expr::Column(Column::new_unqualified("number"))],
                 false,
                 None,
-                vec![],
+                None,
                 None,
             ))],
         )
@@ -449,7 +449,7 @@ async fn test_avg_udaf() {
                 vec![Expr::Column(Column::new_unqualified("__avg_state(number)"))],
                 false,
                 None,
-                vec![],
+                None,
                 None,
             ))
             .alias("avg(number)")],
@@ -551,7 +551,7 @@ async fn test_udaf_correct_eval_result() {
         expected_fn: Option<ExpectedFn>,
         distinct: bool,
         filter: Option<Box<Expr>>,
-        order_by: Vec<SortExpr>,
+        order_by: Option<Vec<SortExpr>>,
         null_treatment: Option<NullTreatment>,
     }
     type ExpectedFn = fn(ArrayRef) -> bool;
@@ -575,7 +575,7 @@ async fn test_udaf_correct_eval_result() {
             expected_fn: None,
             distinct: false,
             filter: None,
-            order_by: vec![],
+            order_by: None,
             null_treatment: None,
         },
         TestCase {
@@ -596,7 +596,7 @@ async fn test_udaf_correct_eval_result() {
             expected_fn: None,
             distinct: false,
             filter: None,
-            order_by: vec![],
+            order_by: None,
             null_treatment: None,
         },
         TestCase {
@@ -619,7 +619,7 @@ async fn test_udaf_correct_eval_result() {
             expected_fn: None,
             distinct: false,
             filter: None,
-            order_by: vec![],
+            order_by: None,
             null_treatment: None,
         },
         TestCase {
@@ -630,8 +630,8 @@ async fn test_udaf_correct_eval_result() {
                 true,
             )])),
             args: vec![
-                lit(128i64),
+                Expr::Literal(ScalarValue::Int64(Some(128))),
-                lit(0.05f64),
+                Expr::Literal(ScalarValue::Float64(Some(0.05))),
                 Expr::Column(Column::new_unqualified("number")),
             ],
             input: vec![Arc::new(Float64Array::from(vec![
@@ -659,7 +659,7 @@ async fn test_udaf_correct_eval_result() {
             }),
             distinct: false,
             filter: None,
-            order_by: vec![],
+            order_by: None,
             null_treatment: None,
         },
         TestCase {
@@ -690,7 +690,7 @@ async fn test_udaf_correct_eval_result() {
             }),
             distinct: false,
             filter: None,
-            order_by: vec![],
+            order_by: None,
             null_treatment: None,
         },
         // TODO(discord9): udd_merge/hll_merge/geo_path/quantile_aggr tests

src/common/function/src/aggrs/count_hash.rs

@@ -41,7 +41,7 @@ use datatypes::arrow::array::{
     Array, ArrayRef, AsArray, BooleanArray, Int64Array, ListArray, UInt64Array,
 };
 use datatypes::arrow::buffer::{OffsetBuffer, ScalarBuffer};
-use datatypes::arrow::datatypes::{DataType, Field, FieldRef};
+use datatypes::arrow::datatypes::{DataType, Field};
 
 use crate::function_registry::FunctionRegistry;
 
@@ -94,14 +94,14 @@ impl AggregateUDFImpl for CountHash {
         false
     }
 
-    fn state_fields(&self, args: StateFieldsArgs) -> Result<Vec<FieldRef>> {
+    fn state_fields(&self, args: StateFieldsArgs) -> Result<Vec<Field>> {
-        Ok(vec![Arc::new(Field::new_list(
+        Ok(vec![Field::new_list(
             format_state_name(args.name, "count_hash"),
             Field::new_list_field(DataType::UInt64, true),
             // For count_hash accumulator, null list item stands for an
             // empty value set (i.e., all NULL value so far for that group).
             true,
-        ))])
+        )])
     }
 
     fn accumulator(&self, acc_args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> {

src/common/function/src/aggrs/geo.rs

@@ -21,7 +21,7 @@ pub(crate) struct GeoFunction;
 
 impl GeoFunction {
     pub fn register(registry: &FunctionRegistry) {
-        registry.register_aggr(encoding::JsonEncodePathAccumulator::uadf_impl());
         registry.register_aggr(geo_path::GeoPathAccumulator::uadf_impl());
+        registry.register_aggr(encoding::JsonPathAccumulator::uadf_impl());
     }
 }

src/common/function/src/aggrs/geo/encoding.rs

@@ -14,332 +14,223 @@
 
 use std::sync::Arc;
 
-use arrow::array::AsArray;
+use common_error::ext::{BoxedError, PlainError};
-use datafusion::arrow::array::{Array, ArrayRef};
+use common_error::status_code::StatusCode;
-use datafusion::common::cast::as_primitive_array;
+use common_macro::{as_aggr_func_creator, AggrFuncTypeStore};
-use datafusion::error::{DataFusionError, Result as DfResult};
+use common_query::error::{self, InvalidInputStateSnafu, Result};
-use datafusion::logical_expr::{Accumulator as DfAccumulator, AggregateUDF, Volatility};
+use common_query::logical_plan::accumulator::AggrFuncTypeStore;
-use datafusion::prelude::create_udaf;
+use common_query::logical_plan::{
-use datafusion_common::cast::{as_list_array, as_struct_array};
+    create_aggregate_function, Accumulator, AggregateFunctionCreator,
-use datafusion_common::ScalarValue;
-use datatypes::arrow::array::{Float64Array, Int64Array, ListArray, StructArray};
-use datatypes::arrow::datatypes::{
-    DataType, Field, Float64Type, Int64Type, TimeUnit, TimestampNanosecondType,
 };
-use datatypes::compute::{self, sort_to_indices};
+use common_query::prelude::AccumulatorCreatorFunction;
+use common_time::Timestamp;
+use datafusion_expr::AggregateUDF;
+use datatypes::prelude::ConcreteDataType;
+use datatypes::value::{ListValue, Value};
+use datatypes::vectors::VectorRef;
+use snafu::{ensure, ResultExt};
 
-pub const JSON_ENCODE_PATH_NAME: &str = "json_encode_path";
+use crate::scalars::geo::helpers::{ensure_columns_len, ensure_columns_n};
 
-const LATITUDE_FIELD: &str = "lat";
+/// Accumulator of lat, lng, timestamp tuples
-const LONGITUDE_FIELD: &str = "lng";
+#[derive(Debug)]
-const TIMESTAMP_FIELD: &str = "timestamp";
+pub struct JsonPathAccumulator {
-const DEFAULT_LIST_FIELD_NAME: &str = "item";
+    timestamp_type: ConcreteDataType,
-
-#[derive(Debug, Default)]
-pub struct JsonEncodePathAccumulator {
     lat: Vec<Option<f64>>,
     lng: Vec<Option<f64>>,
-    timestamp: Vec<Option<i64>>,
+    timestamp: Vec<Option<Timestamp>>,
 }
 
-impl JsonEncodePathAccumulator {
+impl JsonPathAccumulator {
-    pub fn new() -> Self {
+    fn new(timestamp_type: ConcreteDataType) -> Self {
-        Self::default()
+        Self {
-    }
+            lat: Vec::default(),
-
+            lng: Vec::default(),
-    pub fn uadf_impl() -> AggregateUDF {
+            timestamp: Vec::default(),
-        create_udaf(
+            timestamp_type,
-            JSON_ENCODE_PATH_NAME,
-            // Input types: lat, lng, timestamp
-            vec![
-                DataType::Float64,
-                DataType::Float64,
-                DataType::Timestamp(TimeUnit::Nanosecond, None),
-            ],
-            // Output type: geojson compatible linestring
-            Arc::new(DataType::Utf8),
-            Volatility::Immutable,
-            // Create the accumulator
-            Arc::new(|_| Ok(Box::new(Self::new()))),
-            // Intermediate state types
-            Arc::new(vec![DataType::Struct(
-                vec![
-                    Field::new(
-                        LATITUDE_FIELD,
-                        DataType::List(Arc::new(Field::new(
-                            DEFAULT_LIST_FIELD_NAME,
-                            DataType::Float64,
-                            true,
-                        ))),
-                        false,
-                    ),
-                    Field::new(
-                        LONGITUDE_FIELD,
-                        DataType::List(Arc::new(Field::new(
-                            DEFAULT_LIST_FIELD_NAME,
-                            DataType::Float64,
-                            true,
-                        ))),
-                        false,
-                    ),
-                    Field::new(
-                        TIMESTAMP_FIELD,
-                        DataType::List(Arc::new(Field::new(
-                            DEFAULT_LIST_FIELD_NAME,
-                            DataType::Int64,
-                            true,
-                        ))),
-                        false,
-                    ),
-                ]
-                .into(),
-            )]),
-        )
-    }
-}
-
-impl DfAccumulator for JsonEncodePathAccumulator {
-    fn update_batch(&mut self, values: &[ArrayRef]) -> datafusion::error::Result<()> {
-        if values.len() != 3 {
-            return Err(DataFusionError::Internal(format!(
-                "Expected 3 columns for json_encode_path, got {}",
-                values.len()
-            )));
         }
+    }
 
-        let lat_array = as_primitive_array::<Float64Type>(&values[0])?;
+    /// Create a new `AggregateUDF` for the `json_encode_path` aggregate function.
-        let lng_array = as_primitive_array::<Float64Type>(&values[1])?;
+    pub fn uadf_impl() -> AggregateUDF {
-        let ts_array = as_primitive_array::<TimestampNanosecondType>(&values[2])?;
+        create_aggregate_function(
+            "json_encode_path".to_string(),
+            3,
+            Arc::new(JsonPathEncodeFunctionCreator::default()),
+        )
+        .into()
+    }
+}
 
-        let size = lat_array.len();
+impl Accumulator for JsonPathAccumulator {
-        self.lat.reserve(size);
+    fn state(&self) -> Result<Vec<Value>> {
-        self.lng.reserve(size);
+        Ok(vec![
+            Value::List(ListValue::new(
+                self.lat.iter().map(|i| Value::from(*i)).collect(),
+                ConcreteDataType::float64_datatype(),
+            )),
+            Value::List(ListValue::new(
+                self.lng.iter().map(|i| Value::from(*i)).collect(),
+                ConcreteDataType::float64_datatype(),
+            )),
+            Value::List(ListValue::new(
+                self.timestamp.iter().map(|i| Value::from(*i)).collect(),
+                self.timestamp_type.clone(),
+            )),
+        ])
+    }
+
+    fn update_batch(&mut self, columns: &[VectorRef]) -> Result<()> {
+        // update batch as in datafusion just provides the accumulator original
+        //  input.
+        //
+        // columns is vec of [`lat`, `lng`, `timestamp`]
+        // where
+        // - `lat` is a vector of `Value::Float64` or similar type. Each item in
+        //  the vector is a row in given dataset.
+        // - so on so forth for `lng` and `timestamp`
+        ensure_columns_n!(columns, 3);
+
+        let lat = &columns[0];
+        let lng = &columns[1];
+        let ts = &columns[2];
+
+        let size = lat.len();
 
         for idx in 0..size {
-            self.lat.push(if lat_array.is_null(idx) {
+            self.lat.push(lat.get(idx).as_f64_lossy());
-                None
+            self.lng.push(lng.get(idx).as_f64_lossy());
-            } else {
+            self.timestamp.push(ts.get(idx).as_timestamp());
-                Some(lat_array.value(idx))
-            });
-
-            self.lng.push(if lng_array.is_null(idx) {
-                None
-            } else {
-                Some(lng_array.value(idx))
-            });
-
-            self.timestamp.push(if ts_array.is_null(idx) {
-                None
-            } else {
-                Some(ts_array.value(idx))
-            });
         }
 
         Ok(())
     }
 
-    fn evaluate(&mut self) -> DfResult<ScalarValue> {
+    fn merge_batch(&mut self, states: &[VectorRef]) -> Result<()> {
-        let unordered_lng_array = Float64Array::from(self.lng.clone());
+        // merge batch as in datafusion gives state accumulated from the data
-        let unordered_lat_array = Float64Array::from(self.lat.clone());
+        //  returned from child accumulators' state() call
-        let ts_array = Int64Array::from(self.timestamp.clone());
+        // In our particular implementation, the data structure is like
+        //
+        // states is vec of [`lat`, `lng`, `timestamp`]
+        // where
+        // - `lat` is a vector of `Value::List`. Each item in the list is all
+        //  coordinates from a child accumulator.
+        // - so on so forth for `lng` and `timestamp`
 
-        let ordered_indices = sort_to_indices(&ts_array, None, None)?;
+        ensure_columns_n!(states, 3);
-        let lat_array = compute::take(&unordered_lat_array, &ordered_indices, None)?;
-        let lng_array = compute::take(&unordered_lng_array, &ordered_indices, None)?;
 
-        let len = ts_array.len();
+        let lat_lists = &states[0];
-        let lat_array = lat_array.as_primitive::<Float64Type>();
+        let lng_lists = &states[1];
-        let lng_array = lng_array.as_primitive::<Float64Type>();
+        let ts_lists = &states[2];
 
-        let mut coords = Vec::with_capacity(len);
+        let len = lat_lists.len();
-        for i in 0..len {
-            let lng = lng_array.value(i);
-            let lat = lat_array.value(i);
-            coords.push(vec![lng, lat]);
-        }
 
-        let result = serde_json::to_string(&coords)
+        for idx in 0..len {
-            .map_err(|e| DataFusionError::Execution(format!("Failed to encode json, {}", e)))?;
+            if let Some(lat_list) = lat_lists
+                .get(idx)
+                .as_list()
+                .map_err(BoxedError::new)
+                .context(error::ExecuteSnafu)?
+            {
+                for v in lat_list.items() {
+                    self.lat.push(v.as_f64_lossy());
+                }
+            }
 
-        Ok(ScalarValue::Utf8(Some(result)))
+            if let Some(lng_list) = lng_lists
-    }
+                .get(idx)
+                .as_list()
+                .map_err(BoxedError::new)
+                .context(error::ExecuteSnafu)?
+            {
+                for v in lng_list.items() {
+                    self.lng.push(v.as_f64_lossy());
+                }
+            }
 
-    fn size(&self) -> usize {
+            if let Some(ts_list) = ts_lists
-        // Base size of JsonEncodePathAccumulator struct fields
+                .get(idx)
-        let mut total_size = std::mem::size_of::<Self>();
+                .as_list()
-
+                .map_err(BoxedError::new)
-        // Size of vectors (approximation)
+                .context(error::ExecuteSnafu)?
-        total_size += self.lat.capacity() * std::mem::size_of::<Option<f64>>();
+            {
-        total_size += self.lng.capacity() * std::mem::size_of::<Option<f64>>();
+                for v in ts_list.items() {
-        total_size += self.timestamp.capacity() * std::mem::size_of::<Option<i64>>();
+                    self.timestamp.push(v.as_timestamp());
-
+                }
-        total_size
+            }
-    }
-
-    fn state(&mut self) -> datafusion::error::Result<Vec<ScalarValue>> {
-        let lat_array = Arc::new(ListArray::from_iter_primitive::<Float64Type, _, _>(vec![
-            Some(self.lat.clone()),
-        ]));
-        let lng_array = Arc::new(ListArray::from_iter_primitive::<Float64Type, _, _>(vec![
-            Some(self.lng.clone()),
-        ]));
-        let ts_array = Arc::new(ListArray::from_iter_primitive::<Int64Type, _, _>(vec![
-            Some(self.timestamp.clone()),
-        ]));
-
-        let state_struct = StructArray::new(
-            vec![
-                Field::new(
-                    LATITUDE_FIELD,
-                    DataType::List(Arc::new(Field::new("item", DataType::Float64, true))),
-                    false,
-                ),
-                Field::new(
-                    LONGITUDE_FIELD,
-                    DataType::List(Arc::new(Field::new("item", DataType::Float64, true))),
-                    false,
-                ),
-                Field::new(
-                    TIMESTAMP_FIELD,
-                    DataType::List(Arc::new(Field::new("item", DataType::Int64, true))),
-                    false,
-                ),
-            ]
-            .into(),
-            vec![lat_array, lng_array, ts_array],
-            None,
-        );
-
-        Ok(vec![ScalarValue::Struct(Arc::new(state_struct))])
-    }
-
-    fn merge_batch(&mut self, states: &[ArrayRef]) -> datafusion::error::Result<()> {
-        if states.len() != 1 {
-            return Err(DataFusionError::Internal(format!(
-                "Expected 1 states for json_encode_path, got {}",
-                states.len()
-            )));
-        }
-
-        for state in states {
-            let state = as_struct_array(state)?;
-            let lat_list = as_list_array(state.column(0))?.value(0);
-            let lat_array = as_primitive_array::<Float64Type>(&lat_list)?;
-            let lng_list = as_list_array(state.column(1))?.value(0);
-            let lng_array = as_primitive_array::<Float64Type>(&lng_list)?;
-            let ts_list = as_list_array(state.column(2))?.value(0);
-            let ts_array = as_primitive_array::<Int64Type>(&ts_list)?;
-
-            self.lat.extend(lat_array);
-            self.lng.extend(lng_array);
-            self.timestamp.extend(ts_array);
         }
 
         Ok(())
     }
-}
 
-#[cfg(test)]
+    fn evaluate(&self) -> Result<Value> {
-mod tests {
+        let mut work_vec: Vec<(&Option<f64>, &Option<f64>, &Option<Timestamp>)> = self
-    use datafusion::arrow::array::{Float64Array, TimestampNanosecondArray};
+            .lat
-    use datafusion::scalar::ScalarValue;
+            .iter()
+            .zip(self.lng.iter())
+            .zip(self.timestamp.iter())
+            .map(|((a, b), c)| (a, b, c))
+            .collect();
 
-    use super::*;
+        // sort by timestamp, we treat null timestamp as 0
+        work_vec.sort_unstable_by_key(|tuple| tuple.2.unwrap_or_else(|| Timestamp::new_second(0)));
 
-    #[test]
+        let result = serde_json::to_string(
-    fn test_json_encode_path_basic() {
+            &work_vec
-        let mut accumulator = JsonEncodePathAccumulator::new();
+                .into_iter()
+                // note that we transform to lng,lat for geojson compatibility
+                .map(|(lat, lng, _)| vec![lng, lat])
+                .collect::<Vec<Vec<&Option<f64>>>>(),
+        )
+        .map_err(|e| {
+            BoxedError::new(PlainError::new(
+                format!("Serialization failure: {}", e),
+                StatusCode::EngineExecuteQuery,
+            ))
+        })
+        .context(error::ExecuteSnafu)?;
 
-        // Create test data
+        Ok(Value::String(result.into()))
-        let lat_array = Arc::new(Float64Array::from(vec![1.0, 2.0, 3.0]));
+    }
-        let lng_array = Arc::new(Float64Array::from(vec![4.0, 5.0, 6.0]));
+}
-        let ts_array = Arc::new(TimestampNanosecondArray::from(vec![100, 200, 300]));
+
-
+/// This function accept rows of lat, lng and timestamp, sort with timestamp and
-        // Update batch
+/// encoding them into a geojson-like path.
-        accumulator
+///
-            .update_batch(&[lat_array, lng_array, ts_array])
+/// Example:
-            .unwrap();
+///
-
+/// ```sql
-        // Evaluate
+/// SELECT json_encode_path(lat, lon, timestamp) FROM table [group by ...];
-        let result = accumulator.evaluate().unwrap();
+/// ```
-        assert_eq!(
+///
-            result,
+#[as_aggr_func_creator]
-            ScalarValue::Utf8(Some("[[4.0,1.0],[5.0,2.0],[6.0,3.0]]".to_string()))
+#[derive(Debug, Default, AggrFuncTypeStore)]
-        );
+pub struct JsonPathEncodeFunctionCreator {}
-    }
+
-
+impl AggregateFunctionCreator for JsonPathEncodeFunctionCreator {
-    #[test]
+    fn creator(&self) -> AccumulatorCreatorFunction {
-    fn test_json_encode_path_sort_by_timestamp() {
+        let creator: AccumulatorCreatorFunction = Arc::new(move |types: &[ConcreteDataType]| {
-        let mut accumulator = JsonEncodePathAccumulator::new();
+            let ts_type = types[2].clone();
-
+            Ok(Box::new(JsonPathAccumulator::new(ts_type)))
-        // Create test data with unordered timestamps
+        });
-        let lat_array = Arc::new(Float64Array::from(vec![1.0, 2.0, 3.0]));
+
-        let lng_array = Arc::new(Float64Array::from(vec![4.0, 5.0, 6.0]));
+        creator
-        let ts_array = Arc::new(TimestampNanosecondArray::from(vec![300, 100, 200]));
+    }
-
+
-        // Update batch
+    fn output_type(&self) -> Result<ConcreteDataType> {
-        accumulator
+        Ok(ConcreteDataType::string_datatype())
-            .update_batch(&[lat_array, lng_array, ts_array])
+    }
-            .unwrap();
+
-
+    fn state_types(&self) -> Result<Vec<ConcreteDataType>> {
-        // Evaluate
+        let input_types = self.input_types()?;
-        let result = accumulator.evaluate().unwrap();
+        ensure!(input_types.len() == 3, InvalidInputStateSnafu);
-        assert_eq!(
+
-            result,
+        let timestamp_type = input_types[2].clone();
-            ScalarValue::Utf8(Some("[[5.0,2.0],[6.0,3.0],[4.0,1.0]]".to_string()))
+
-        );
+        Ok(vec![
-    }
+            ConcreteDataType::list_datatype(ConcreteDataType::float64_datatype()),
-
+            ConcreteDataType::list_datatype(ConcreteDataType::float64_datatype()),
-    #[test]
+            ConcreteDataType::list_datatype(timestamp_type),
-    fn test_json_encode_path_merge() {
+        ])
-        let mut accumulator1 = JsonEncodePathAccumulator::new();
-        let mut accumulator2 = JsonEncodePathAccumulator::new();
-
-        // Create test data for first accumulator
-        let lat_array1 = Arc::new(Float64Array::from(vec![1.0]));
-        let lng_array1 = Arc::new(Float64Array::from(vec![4.0]));
-        let ts_array1 = Arc::new(TimestampNanosecondArray::from(vec![100]));
-
-        // Create test data for second accumulator
-        let lat_array2 = Arc::new(Float64Array::from(vec![2.0]));
-        let lng_array2 = Arc::new(Float64Array::from(vec![5.0]));
-        let ts_array2 = Arc::new(TimestampNanosecondArray::from(vec![200]));
-
-        // Update batches
-        accumulator1
-            .update_batch(&[lat_array1, lng_array1, ts_array1])
-            .unwrap();
-        accumulator2
-            .update_batch(&[lat_array2, lng_array2, ts_array2])
-            .unwrap();
-
-        // Get states
-        let state1 = accumulator1.state().unwrap();
-        let state2 = accumulator2.state().unwrap();
-
-        // Create a merged accumulator
-        let mut merged = JsonEncodePathAccumulator::new();
-
-        // Extract the struct arrays from the states
-        let state_array1 = match &state1[0] {
-            ScalarValue::Struct(array) => array.clone(),
-            _ => panic!("Expected Struct scalar value"),
-        };
-
-        let state_array2 = match &state2[0] {
-            ScalarValue::Struct(array) => array.clone(),
-            _ => panic!("Expected Struct scalar value"),
-        };
-
-        // Merge state arrays
-        merged.merge_batch(&[state_array1]).unwrap();
-        merged.merge_batch(&[state_array2]).unwrap();
-
-        // Evaluate merged result
-        let result = merged.evaluate().unwrap();
-        assert_eq!(
-            result,
-            ScalarValue::Utf8(Some("[[4.0,1.0],[5.0,2.0]]".to_string()))
-        );
     }
 }

src/common/function/src/aggrs/vector/product.rs

@@ -12,20 +12,21 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-use std::borrow::Cow;
 use std::sync::Arc;
 
-use arrow::array::{Array, ArrayRef, AsArray, BinaryArray, StringArray};
+use common_macro::{as_aggr_func_creator, AggrFuncTypeStore};
-use arrow_schema::{DataType, Field};
+use common_query::error::{CreateAccumulatorSnafu, Error, InvalidFuncArgsSnafu};
-use datafusion::logical_expr::{Signature, TypeSignature, Volatility};
+use common_query::logical_plan::{
-use datafusion_common::{Result, ScalarValue};
+    create_aggregate_function, Accumulator, AggregateFunctionCreator,
-use datafusion_expr::{Accumulator, AggregateUDF, SimpleAggregateUDF};
-use datafusion_functions_aggregate_common::accumulator::AccumulatorArgs;
-use nalgebra::{Const, DVectorView, Dyn, OVector};
-
-use crate::scalars::vector::impl_conv::{
-    binlit_as_veclit, parse_veclit_from_strlit, veclit_to_binlit,
 };
+use common_query::prelude::AccumulatorCreatorFunction;
+use datafusion_expr::AggregateUDF;
+use datatypes::prelude::{ConcreteDataType, Value, *};
+use datatypes::vectors::VectorRef;
+use nalgebra::{Const, DVectorView, Dyn, OVector};
+use snafu::ensure;
+
+use crate::scalars::vector::impl_conv::{as_veclit, as_veclit_if_const, veclit_to_binlit};
 
 /// Aggregates by multiplying elements across the same dimension, returns a vector.
 #[derive(Debug, Default)]
@@ -34,42 +35,57 @@ pub struct VectorProduct {
     has_null: bool,
 }
 
+#[as_aggr_func_creator]
+#[derive(Debug, Default, AggrFuncTypeStore)]
+pub struct VectorProductCreator {}
+
+impl AggregateFunctionCreator for VectorProductCreator {
+    fn creator(&self) -> AccumulatorCreatorFunction {
+        let creator: AccumulatorCreatorFunction = Arc::new(move |types: &[ConcreteDataType]| {
+            ensure!(
+                types.len() == 1,
+                InvalidFuncArgsSnafu {
+                    err_msg: format!(
+                        "The length of the args is not correct, expect exactly one, have: {}",
+                        types.len()
+                    )
+                }
+            );
+            let input_type = &types[0];
+            match input_type {
+                ConcreteDataType::String(_) | ConcreteDataType::Binary(_) => {
+                    Ok(Box::new(VectorProduct::default()))
+                }
+                _ => {
+                    let err_msg = format!(
+                        "\"VEC_PRODUCT\" aggregate function not support data type {:?}",
+                        input_type.logical_type_id(),
+                    );
+                    CreateAccumulatorSnafu { err_msg }.fail()?
+                }
+            }
+        });
+        creator
+    }
+
+    fn output_type(&self) -> common_query::error::Result<ConcreteDataType> {
+        Ok(ConcreteDataType::binary_datatype())
+    }
+
+    fn state_types(&self) -> common_query::error::Result<Vec<ConcreteDataType>> {
+        Ok(vec![self.output_type()?])
+    }
+}
+
 impl VectorProduct {
     /// Create a new `AggregateUDF` for the `vec_product` aggregate function.
     pub fn uadf_impl() -> AggregateUDF {
-        let signature = Signature::one_of(
+        create_aggregate_function(
-            vec![
+            "vec_product".to_string(),
-                TypeSignature::Exact(vec![DataType::Utf8]),
+            1,
-                TypeSignature::Exact(vec![DataType::Binary]),
+            Arc::new(VectorProductCreator::default()),
-            ],
+        )
-            Volatility::Immutable,
+        .into()
-        );
-        let udaf = SimpleAggregateUDF::new_with_signature(
-            "vec_product",
-            signature,
-            DataType::Binary,
-            Arc::new(Self::accumulator),
-            vec![Arc::new(Field::new("x", DataType::Binary, true))],
-        );
-        AggregateUDF::from(udaf)
-    }
-
-    fn accumulator(args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> {
-        if args.schema.fields().len() != 1 {
-            return Err(datafusion_common::DataFusionError::Internal(format!(
-                "expect creating `VEC_PRODUCT` with only one input field, actual {}",
-                args.schema.fields().len()
-            )));
-        }
-
-        let t = args.schema.field(0).data_type();
-        if !matches!(t, DataType::Utf8 | DataType::Binary) {
-            return Err(datafusion_common::DataFusionError::Internal(format!(
-                "unexpected input datatype {t} when creating `VEC_PRODUCT`"
-            )));
-        }
-
-        Ok(Box::new(VectorProduct::default()))
     }
 
     fn inner(&mut self, len: usize) -> &mut OVector<f32, Dyn> {
@@ -78,82 +94,67 @@ impl VectorProduct {
         })
     }
 
-    fn update(&mut self, values: &[ArrayRef], is_update: bool) -> Result<()> {
+    fn update(&mut self, values: &[VectorRef], is_update: bool) -> Result<(), Error> {
         if values.is_empty() || self.has_null {
             return Ok(());
         };
+        let column = &values[0];
+        let len = column.len();
 
-        let vectors = match values[0].data_type() {
+        match as_veclit_if_const(column)? {
-            DataType::Utf8 => {
+            Some(column) => {
-                let arr: &StringArray = values[0].as_string();
+                let vec_column = DVectorView::from_slice(&column, column.len()).scale(len as f32);
-                arr.iter()
+                *self.inner(vec_column.len()) =
-                    .filter_map(|x| x.map(|s| parse_veclit_from_strlit(s).map_err(Into::into)))
+                    (*self.inner(vec_column.len())).component_mul(&vec_column);
-                    .map(|x| x.map(Cow::Owned))
-                    .collect::<Result<Vec<_>>>()?
             }
-            DataType::Binary => {
+            None => {
-                let arr: &BinaryArray = values[0].as_binary();
+                for i in 0..len {
-                arr.iter()
+                    let Some(arg0) = as_veclit(column.get_ref(i))? else {
-                    .filter_map(|x| x.map(|b| binlit_as_veclit(b).map_err(Into::into)))
+                        if is_update {
-                    .collect::<Result<Vec<_>>>()?
+                            self.has_null = true;
+                            self.product = None;
+                        }
+                        return Ok(());
+                    };
+                    let vec_column = DVectorView::from_slice(&arg0, arg0.len());
+                    *self.inner(vec_column.len()) =
+                        (*self.inner(vec_column.len())).component_mul(&vec_column);
+                }
             }
-            _ => {
-                return Err(datafusion_common::DataFusionError::NotImplemented(format!(
-                    "unsupported data type {} for `VEC_PRODUCT`",
-                    values[0].data_type()
-                )))
-            }
-        };
-        if vectors.len() != values[0].len() {
-            if is_update {
-                self.has_null = true;
-                self.product = None;
-            }
-            return Ok(());
         }
-
-        vectors.iter().for_each(|v| {
-            let v = DVectorView::from_slice(v, v.len());
-            let inner = self.inner(v.len());
-            *inner = inner.component_mul(&v);
-        });
         Ok(())
     }
 }
 
 impl Accumulator for VectorProduct {
-    fn state(&mut self) -> Result<Vec<ScalarValue>> {
+    fn state(&self) -> common_query::error::Result<Vec<Value>> {
         self.evaluate().map(|v| vec![v])
     }
 
-    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+    fn update_batch(&mut self, values: &[VectorRef]) -> common_query::error::Result<()> {
         self.update(values, true)
     }
 
-    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+    fn merge_batch(&mut self, states: &[VectorRef]) -> common_query::error::Result<()> {
         self.update(states, false)
     }
 
-    fn evaluate(&mut self) -> Result<ScalarValue> {
+    fn evaluate(&self) -> common_query::error::Result<Value> {
         match &self.product {
-            None => Ok(ScalarValue::Binary(None)),
+            None => Ok(Value::Null),
-            Some(vector) => Ok(ScalarValue::Binary(Some(veclit_to_binlit(
+            Some(vector) => {
-                vector.as_slice(),
+                let v = vector.as_slice();
-            )))),
+                Ok(Value::from(veclit_to_binlit(v)))
+            }
         }
     }
-
-    fn size(&self) -> usize {
-        size_of_val(self)
-    }
 }
 
 #[cfg(test)]
 mod tests {
     use std::sync::Arc;
 
-    use datatypes::scalars::ScalarVector;
+    use datatypes::vectors::{ConstantVector, StringVector};
-    use datatypes::vectors::{ConstantVector, StringVector, Vector};
 
     use super::*;
 
@@ -164,60 +165,59 @@ mod tests {
         vec_product.update_batch(&[]).unwrap();
         assert!(vec_product.product.is_none());
         assert!(!vec_product.has_null);
-        assert_eq!(ScalarValue::Binary(None), vec_product.evaluate().unwrap());
+        assert_eq!(Value::Null, vec_product.evaluate().unwrap());
 
         // test update one not-null value
         let mut vec_product = VectorProduct::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![Some(
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![Some(
             "[1.0,2.0,3.0]".to_string(),
         )]))];
         vec_product.update_batch(&v).unwrap();
         assert_eq!(
-            ScalarValue::Binary(Some(veclit_to_binlit(&[1.0, 2.0, 3.0]))),
+            Value::from(veclit_to_binlit(&[1.0, 2.0, 3.0])),
             vec_product.evaluate().unwrap()
         );
 
         // test update one null value
         let mut vec_product = VectorProduct::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![Option::<String>::None]))];
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![Option::<String>::None]))];
         vec_product.update_batch(&v).unwrap();
-        assert_eq!(ScalarValue::Binary(None), vec_product.evaluate().unwrap());
+        assert_eq!(Value::Null, vec_product.evaluate().unwrap());
 
         // test update no null-value batch
         let mut vec_product = VectorProduct::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![
             Some("[1.0,2.0,3.0]".to_string()),
             Some("[4.0,5.0,6.0]".to_string()),
             Some("[7.0,8.0,9.0]".to_string()),
         ]))];
         vec_product.update_batch(&v).unwrap();
         assert_eq!(
-            ScalarValue::Binary(Some(veclit_to_binlit(&[28.0, 80.0, 162.0]))),
+            Value::from(veclit_to_binlit(&[28.0, 80.0, 162.0])),
             vec_product.evaluate().unwrap()
         );
 
         // test update null-value batch
         let mut vec_product = VectorProduct::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![
             Some("[1.0,2.0,3.0]".to_string()),
             None,
             Some("[7.0,8.0,9.0]".to_string()),
         ]))];
         vec_product.update_batch(&v).unwrap();
-        assert_eq!(ScalarValue::Binary(None), vec_product.evaluate().unwrap());
+        assert_eq!(Value::Null, vec_product.evaluate().unwrap());
 
         // test update with constant vector
         let mut vec_product = VectorProduct::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(ConstantVector::new(
+        let v: Vec<VectorRef> = vec![Arc::new(ConstantVector::new(
             Arc::new(StringVector::from_vec(vec!["[1.0,2.0,3.0]".to_string()])),
             4,
-        ))
+        ))];
-        .to_arrow_array()];
 
         vec_product.update_batch(&v).unwrap();
 
         assert_eq!(
-            ScalarValue::Binary(Some(veclit_to_binlit(&[1.0, 16.0, 81.0]))),
+            Value::from(veclit_to_binlit(&[4.0, 8.0, 12.0])),
             vec_product.evaluate().unwrap()
         );
     }

src/common/function/src/aggrs/vector/sum.rs

@@ -14,18 +14,19 @@
 
 use std::sync::Arc;
 
-use arrow::array::{Array, ArrayRef, AsArray, BinaryArray, StringArray};
+use common_macro::{as_aggr_func_creator, AggrFuncTypeStore};
-use arrow_schema::{DataType, Field};
+use common_query::error::{CreateAccumulatorSnafu, Error, InvalidFuncArgsSnafu};
-use datafusion_common::{Result, ScalarValue};
+use common_query::logical_plan::{
-use datafusion_expr::{
+    create_aggregate_function, Accumulator, AggregateFunctionCreator,
-    Accumulator, AggregateUDF, Signature, SimpleAggregateUDF, TypeSignature, Volatility,
 };
-use datafusion_functions_aggregate_common::accumulator::AccumulatorArgs;
+use common_query::prelude::AccumulatorCreatorFunction;
+use datafusion_expr::AggregateUDF;
+use datatypes::prelude::{ConcreteDataType, Value, *};
+use datatypes::vectors::VectorRef;
 use nalgebra::{Const, DVectorView, Dyn, OVector};
+use snafu::ensure;
 
-use crate::scalars::vector::impl_conv::{
+use crate::scalars::vector::impl_conv::{as_veclit, as_veclit_if_const, veclit_to_binlit};
-    binlit_as_veclit, parse_veclit_from_strlit, veclit_to_binlit,
-};
 
 /// The accumulator for the `vec_sum` aggregate function.
 #[derive(Debug, Default)]
@@ -34,42 +35,57 @@ pub struct VectorSum {
     has_null: bool,
 }
 
+#[as_aggr_func_creator]
+#[derive(Debug, Default, AggrFuncTypeStore)]
+pub struct VectorSumCreator {}
+
+impl AggregateFunctionCreator for VectorSumCreator {
+    fn creator(&self) -> AccumulatorCreatorFunction {
+        let creator: AccumulatorCreatorFunction = Arc::new(move |types: &[ConcreteDataType]| {
+            ensure!(
+                types.len() == 1,
+                InvalidFuncArgsSnafu {
+                    err_msg: format!(
+                        "The length of the args is not correct, expect exactly one, have: {}",
+                        types.len()
+                    )
+                }
+            );
+            let input_type = &types[0];
+            match input_type {
+                ConcreteDataType::String(_) | ConcreteDataType::Binary(_) => {
+                    Ok(Box::new(VectorSum::default()))
+                }
+                _ => {
+                    let err_msg = format!(
+                        "\"VEC_SUM\" aggregate function not support data type {:?}",
+                        input_type.logical_type_id(),
+                    );
+                    CreateAccumulatorSnafu { err_msg }.fail()?
+                }
+            }
+        });
+        creator
+    }
+
+    fn output_type(&self) -> common_query::error::Result<ConcreteDataType> {
+        Ok(ConcreteDataType::binary_datatype())
+    }
+
+    fn state_types(&self) -> common_query::error::Result<Vec<ConcreteDataType>> {
+        Ok(vec![self.output_type()?])
+    }
+}
+
 impl VectorSum {
     /// Create a new `AggregateUDF` for the `vec_sum` aggregate function.
     pub fn uadf_impl() -> AggregateUDF {
-        let signature = Signature::one_of(
+        create_aggregate_function(
-            vec![
+            "vec_sum".to_string(),
-                TypeSignature::Exact(vec![DataType::Utf8]),
+            1,
-                TypeSignature::Exact(vec![DataType::Binary]),
+            Arc::new(VectorSumCreator::default()),
-            ],
+        )
-            Volatility::Immutable,
+        .into()
-        );
-        let udaf = SimpleAggregateUDF::new_with_signature(
-            "vec_sum",
-            signature,
-            DataType::Binary,
-            Arc::new(Self::accumulator),
-            vec![Arc::new(Field::new("x", DataType::Binary, true))],
-        );
-        AggregateUDF::from(udaf)
-    }
-
-    fn accumulator(args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> {
-        if args.schema.fields().len() != 1 {
-            return Err(datafusion_common::DataFusionError::Internal(format!(
-                "expect creating `VEC_SUM` with only one input field, actual {}",
-                args.schema.fields().len()
-            )));
-        }
-
-        let t = args.schema.field(0).data_type();
-        if !matches!(t, DataType::Utf8 | DataType::Binary) {
-            return Err(datafusion_common::DataFusionError::Internal(format!(
-                "unexpected input datatype {t} when creating `VEC_SUM`"
-            )));
-        }
-
-        Ok(Box::new(VectorSum::default()))
     }
 
     fn inner(&mut self, len: usize) -> &mut OVector<f32, Dyn> {
@@ -77,87 +93,62 @@ impl VectorSum {
             .get_or_insert_with(|| OVector::zeros_generic(Dyn(len), Const::<1>))
     }
 
-    fn update(&mut self, values: &[ArrayRef], is_update: bool) -> Result<()> {
+    fn update(&mut self, values: &[VectorRef], is_update: bool) -> Result<(), Error> {
         if values.is_empty() || self.has_null {
             return Ok(());
         };
+        let column = &values[0];
+        let len = column.len();
 
-        match values[0].data_type() {
+        match as_veclit_if_const(column)? {
-            DataType::Utf8 => {
+            Some(column) => {
-                let arr: &StringArray = values[0].as_string();
+                let vec_column = DVectorView::from_slice(&column, column.len()).scale(len as f32);
-                for s in arr.iter() {
+                *self.inner(vec_column.len()) += vec_column;
-                    let Some(s) = s else {
+            }
+            None => {
+                for i in 0..len {
+                    let Some(arg0) = as_veclit(column.get_ref(i))? else {
                         if is_update {
                             self.has_null = true;
                             self.sum = None;
                         }
                         return Ok(());
                     };
-                    let values = parse_veclit_from_strlit(s)?;
+                    let vec_column = DVectorView::from_slice(&arg0, arg0.len());
-                    let vec_column = DVectorView::from_slice(&values, values.len());
                     *self.inner(vec_column.len()) += vec_column;
                 }
             }
-            DataType::Binary => {
-                let arr: &BinaryArray = values[0].as_binary();
-                for b in arr.iter() {
-                    let Some(b) = b else {
-                        if is_update {
-                            self.has_null = true;
-                            self.sum = None;
-                        }
-                        return Ok(());
-                    };
-                    let values = binlit_as_veclit(b)?;
-                    let vec_column = DVectorView::from_slice(&values, values.len());
-                    *self.inner(vec_column.len()) += vec_column;
-                }
-            }
-            _ => {
-                return Err(datafusion_common::DataFusionError::NotImplemented(format!(
-                    "unsupported data type {} for `VEC_SUM`",
-                    values[0].data_type()
-                )))
-            }
         }
         Ok(())
     }
 }
 
 impl Accumulator for VectorSum {
-    fn state(&mut self) -> Result<Vec<ScalarValue>> {
+    fn state(&self) -> common_query::error::Result<Vec<Value>> {
         self.evaluate().map(|v| vec![v])
     }
 
-    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+    fn update_batch(&mut self, values: &[VectorRef]) -> common_query::error::Result<()> {
         self.update(values, true)
     }
 
-    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+    fn merge_batch(&mut self, states: &[VectorRef]) -> common_query::error::Result<()> {
         self.update(states, false)
     }
 
-    fn evaluate(&mut self) -> Result<ScalarValue> {
+    fn evaluate(&self) -> common_query::error::Result<Value> {
         match &self.sum {
-            None => Ok(ScalarValue::Binary(None)),
+            None => Ok(Value::Null),
-            Some(vector) => Ok(ScalarValue::Binary(Some(veclit_to_binlit(
+            Some(vector) => Ok(Value::from(veclit_to_binlit(vector.as_slice()))),
-                vector.as_slice(),
-            )))),
         }
     }
-
-    fn size(&self) -> usize {
-        size_of_val(self)
-    }
 }
 
 #[cfg(test)]
 mod tests {
     use std::sync::Arc;
 
-    use arrow::array::StringArray;
+    use datatypes::vectors::{ConstantVector, StringVector};
-    use datatypes::scalars::ScalarVector;
-    use datatypes::vectors::{ConstantVector, StringVector, Vector};
 
     use super::*;
 
@@ -168,58 +159,57 @@ mod tests {
         vec_sum.update_batch(&[]).unwrap();
         assert!(vec_sum.sum.is_none());
         assert!(!vec_sum.has_null);
-        assert_eq!(ScalarValue::Binary(None), vec_sum.evaluate().unwrap());
+        assert_eq!(Value::Null, vec_sum.evaluate().unwrap());
 
         // test update one not-null value
         let mut vec_sum = VectorSum::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![Some(
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![Some(
             "[1.0,2.0,3.0]".to_string(),
         )]))];
         vec_sum.update_batch(&v).unwrap();
         assert_eq!(
-            ScalarValue::Binary(Some(veclit_to_binlit(&[1.0, 2.0, 3.0]))),
+            Value::from(veclit_to_binlit(&[1.0, 2.0, 3.0])),
             vec_sum.evaluate().unwrap()
         );
 
         // test update one null value
         let mut vec_sum = VectorSum::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![Option::<String>::None]))];
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![Option::<String>::None]))];
         vec_sum.update_batch(&v).unwrap();
-        assert_eq!(ScalarValue::Binary(None), vec_sum.evaluate().unwrap());
+        assert_eq!(Value::Null, vec_sum.evaluate().unwrap());
 
         // test update no null-value batch
         let mut vec_sum = VectorSum::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![
             Some("[1.0,2.0,3.0]".to_string()),
             Some("[4.0,5.0,6.0]".to_string()),
             Some("[7.0,8.0,9.0]".to_string()),
         ]))];
         vec_sum.update_batch(&v).unwrap();
         assert_eq!(
-            ScalarValue::Binary(Some(veclit_to_binlit(&[12.0, 15.0, 18.0]))),
+            Value::from(veclit_to_binlit(&[12.0, 15.0, 18.0])),
             vec_sum.evaluate().unwrap()
         );
 
         // test update null-value batch
         let mut vec_sum = VectorSum::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(StringArray::from(vec![
+        let v: Vec<VectorRef> = vec![Arc::new(StringVector::from(vec![
             Some("[1.0,2.0,3.0]".to_string()),
             None,
             Some("[7.0,8.0,9.0]".to_string()),
         ]))];
         vec_sum.update_batch(&v).unwrap();
-        assert_eq!(ScalarValue::Binary(None), vec_sum.evaluate().unwrap());
+        assert_eq!(Value::Null, vec_sum.evaluate().unwrap());
 
         // test update with constant vector
         let mut vec_sum = VectorSum::default();
-        let v: Vec<ArrayRef> = vec![Arc::new(ConstantVector::new(
+        let v: Vec<VectorRef> = vec![Arc::new(ConstantVector::new(
             Arc::new(StringVector::from_vec(vec!["[1.0,2.0,3.0]".to_string()])),
             4,
-        ))
+        ))];
-        .to_arrow_array()];
         vec_sum.update_batch(&v).unwrap();
         assert_eq!(
-            ScalarValue::Binary(Some(veclit_to_binlit(&[4.0, 8.0, 12.0]))),
+            Value::from(veclit_to_binlit(&[4.0, 8.0, 12.0])),
             vec_sum.evaluate().unwrap()
         );
     }

src/common/function/src/flush_flow.rs

@@ -12,24 +12,28 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-use arrow::datatypes::DataType as ArrowDataType;
 use common_error::ext::BoxedError;
 use common_macro::admin_fn;
 use common_query::error::{
     ExecuteSnafu, InvalidFuncArgsSnafu, MissingFlowServiceHandlerSnafu, Result,
     UnsupportedInputDataTypeSnafu,
 };
-use datafusion_expr::{Signature, Volatility};
+use common_query::prelude::Signature;
+use datafusion::logical_expr::Volatility;
 use datatypes::value::{Value, ValueRef};
 use session::context::QueryContextRef;
 use snafu::{ensure, ResultExt};
-use sql::ast::ObjectNamePartExt;
 use sql::parser::ParserContext;
+use store_api::storage::ConcreteDataType;
 
 use crate::handlers::FlowServiceHandlerRef;
 
 fn flush_signature() -> Signature {
-    Signature::uniform(1, vec![ArrowDataType::Utf8], Volatility::Immutable)
+    Signature::uniform(
+        1,
+        vec![ConcreteDataType::string_datatype()],
+        Volatility::Immutable,
+    )
 }
 
 #[admin_fn(
@@ -81,9 +85,9 @@ fn parse_flush_flow(
     let (catalog_name, flow_name) = match &obj_name.0[..] {
         [flow_name] => (
             query_ctx.current_catalog().to_string(),
-            flow_name.to_string_unquoted(),
+            flow_name.value.clone(),
         ),
-        [catalog, flow_name] => (catalog.to_string_unquoted(), flow_name.to_string_unquoted()),
+        [catalog, flow_name] => (catalog.value.clone(), flow_name.value.clone()),
         _ => {
             return InvalidFuncArgsSnafu {
                 err_msg: format!(
@@ -101,55 +105,44 @@ fn parse_flush_flow(
 mod test {
     use std::sync::Arc;
 
+    use datatypes::scalars::ScalarVector;
+    use datatypes::vectors::StringVector;
     use session::context::QueryContext;
 
     use super::*;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[test]
     fn test_flush_flow_metadata() {
-        let factory: ScalarFunctionFactory = FlushFlowFunction::factory().into();
+        let f = FlushFlowFunction;
-        let f = factory.provide(FunctionContext::mock());
         assert_eq!("flush_flow", f.name());
-        assert_eq!(ArrowDataType::UInt64, f.return_type(&[]).unwrap());
+        assert_eq!(
-        let expected_signature = datafusion_expr::Signature::uniform(
+            ConcreteDataType::uint64_datatype(),
-            1,
+            f.return_type(&[]).unwrap()
-            vec![ArrowDataType::Utf8],
+        );
-            datafusion_expr::Volatility::Immutable,
+        assert_eq!(
+            f.signature(),
+            Signature::uniform(
+                1,
+                vec![ConcreteDataType::string_datatype()],
+                Volatility::Immutable,
+            )
         );
-        assert_eq!(*f.signature(), expected_signature);
     }
 
     #[tokio::test]
     async fn test_missing_flow_service() {
-        let factory: ScalarFunctionFactory = FlushFlowFunction::factory().into();
+        let f = FlushFlowFunction;
-        let binding = factory.provide(FunctionContext::default());
-        let f = binding.as_async().unwrap();
 
-        let flow_name_array = Arc::new(arrow::array::StringArray::from(vec!["flow_name"]));
+        let args = vec!["flow_name"];
+        let args = args
+            .into_iter()
+            .map(|arg| Arc::new(StringVector::from_slice(&[arg])) as _)
+            .collect::<Vec<_>>();
 
-        let columnar_args = vec![datafusion_expr::ColumnarValue::Array(flow_name_array as _)];
+        let result = f.eval(FunctionContext::default(), &args).await.unwrap_err();
-
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
-            args: columnar_args,
-            arg_fields: vec![Arc::new(arrow::datatypes::Field::new(
-                "arg_0",
-                ArrowDataType::Utf8,
-                false,
-            ))],
-            return_field: Arc::new(arrow::datatypes::Field::new(
-                "result",
-                ArrowDataType::UInt64,
-                true,
-            )),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-
-        let result = f.invoke_async_with_args(func_args).await.unwrap_err();
         assert_eq!(
-            "Execution error: Handler error: Missing FlowServiceHandler, not expected",
+            "Missing FlowServiceHandler, not expected",
             result.to_string()
         );
     }

src/common/function/src/function.rs

@@ -41,12 +41,6 @@ impl FunctionContext {
     }
 }
 
-impl std::fmt::Display for FunctionContext {
-    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
-        write!(f, "FunctionContext {{ query_ctx: {} }}", self.query_ctx)
-    }
-}
-
 impl Default for FunctionContext {
     fn default() -> Self {
         Self {
@@ -73,3 +67,22 @@ pub trait Function: fmt::Display + Sync + Send {
 }
 
 pub type FunctionRef = Arc<dyn Function>;
+
+/// Async Scalar function trait
+#[async_trait::async_trait]
+pub trait AsyncFunction: fmt::Display + Sync + Send {
+    /// Returns the name of the function, should be unique.
+    fn name(&self) -> &str;
+
+    /// The returned data type of function execution.
+    fn return_type(&self, input_types: &[ConcreteDataType]) -> Result<ConcreteDataType>;
+
+    /// The signature of function.
+    fn signature(&self) -> Signature;
+
+    /// Evaluate the function, e.g. run/execute the function.
+    /// TODO(dennis): simplify the signature and refactor all the admin functions.
+    async fn eval(&self, _func_ctx: FunctionContext, _columns: &[VectorRef]) -> Result<VectorRef>;
+}
+
+pub type AsyncFunctionRef = Arc<dyn AsyncFunction>;

src/common/function/src/function_factory.rs

@@ -22,8 +22,8 @@ use crate::scalars::udf::create_udf;
 /// A factory for creating `ScalarUDF` that require a function context.
 #[derive(Clone)]
 pub struct ScalarFunctionFactory {
-    pub name: String,
+    name: String,
-    pub factory: Arc<dyn Fn(FunctionContext) -> ScalarUDF + Send + Sync>,
+    factory: Arc<dyn Fn(FunctionContext) -> ScalarUDF + Send + Sync>,
 }
 
 impl ScalarFunctionFactory {

src/common/function/src/function_registry.rs

@@ -24,7 +24,7 @@ use crate::aggrs::aggr_wrapper::StateMergeHelper;
 use crate::aggrs::approximate::ApproximateFunction;
 use crate::aggrs::count_hash::CountHash;
 use crate::aggrs::vector::VectorFunction as VectorAggrFunction;
-use crate::function::{Function, FunctionRef};
+use crate::function::{AsyncFunctionRef, Function, FunctionRef};
 use crate::function_factory::ScalarFunctionFactory;
 use crate::scalars::date::DateFunction;
 use crate::scalars::expression::ExpressionFunction;
@@ -42,18 +42,11 @@ use crate::system::SystemFunction;
 #[derive(Default)]
 pub struct FunctionRegistry {
     functions: RwLock<HashMap<String, ScalarFunctionFactory>>,
+    async_functions: RwLock<HashMap<String, AsyncFunctionRef>>,
     aggregate_functions: RwLock<HashMap<String, AggregateUDF>>,
 }
 
 impl FunctionRegistry {
-    /// Register a function in the registry by converting it into a `ScalarFunctionFactory`.
-    ///
-    /// # Arguments
-    ///
-    /// * `func` - An object that can be converted into a `ScalarFunctionFactory`.
-    ///
-    /// The function is inserted into the internal function map, keyed by its name.
-    /// If a function with the same name already exists, it will be replaced.
     pub fn register(&self, func: impl Into<ScalarFunctionFactory>) {
         let func = func.into();
         let _ = self
@@ -63,12 +56,18 @@ impl FunctionRegistry {
             .insert(func.name().to_string(), func);
     }
 
-    /// Register a scalar function in the registry.
     pub fn register_scalar(&self, func: impl Function + 'static) {
         self.register(Arc::new(func) as FunctionRef);
     }
 
-    /// Register an aggregate function in the registry.
+    pub fn register_async(&self, func: AsyncFunctionRef) {
+        let _ = self
+            .async_functions
+            .write()
+            .unwrap()
+            .insert(func.name().to_string(), func);
+    }
+
     pub fn register_aggr(&self, func: AggregateUDF) {
         let _ = self
             .aggregate_functions
@@ -77,16 +76,28 @@ impl FunctionRegistry {
             .insert(func.name().to_string(), func);
     }
 
+    pub fn get_async_function(&self, name: &str) -> Option<AsyncFunctionRef> {
+        self.async_functions.read().unwrap().get(name).cloned()
+    }
+
+    pub fn async_functions(&self) -> Vec<AsyncFunctionRef> {
+        self.async_functions
+            .read()
+            .unwrap()
+            .values()
+            .cloned()
+            .collect()
+    }
+
+    #[cfg(test)]
     pub fn get_function(&self, name: &str) -> Option<ScalarFunctionFactory> {
         self.functions.read().unwrap().get(name).cloned()
     }
 
-    /// Returns a list of all scalar functions registered in the registry.
     pub fn scalar_functions(&self) -> Vec<ScalarFunctionFactory> {
         self.functions.read().unwrap().values().cloned().collect()
     }
 
-    /// Returns a list of all aggregate functions registered in the registry.
     pub fn aggregate_functions(&self) -> Vec<AggregateUDF> {
         self.aggregate_functions
             .read()
@@ -96,7 +107,6 @@ impl FunctionRegistry {
             .collect()
     }
 
-    /// Returns true if an aggregate function with the given name exists in the registry.
     pub fn is_aggr_func_exist(&self, name: &str) -> bool {
         self.aggregate_functions.read().unwrap().contains_key(name)
     }

src/common/function/src/scalars/math/clamp.rs

@@ -34,33 +34,6 @@ pub struct ClampFunction;
 
 const CLAMP_NAME: &str = "clamp";
 
-/// Ensure the vector is constant and not empty (i.e., all values are identical)
-fn ensure_constant_vector(vector: &VectorRef) -> Result<()> {
-    ensure!(
-        !vector.is_empty(),
-        InvalidFuncArgsSnafu {
-            err_msg: "Expect at least one value",
-        }
-    );
-
-    if vector.is_const() {
-        return Ok(());
-    }
-
-    let first = vector.get_ref(0);
-    for i in 1..vector.len() {
-        let v = vector.get_ref(i);
-        if first != v {
-            return InvalidFuncArgsSnafu {
-                err_msg: "All values in min/max argument must be identical",
-            }
-            .fail();
-        }
-    }
-
-    Ok(())
-}
-
 impl Function for ClampFunction {
     fn name(&self) -> &str {
         CLAMP_NAME
@@ -107,9 +80,16 @@ impl Function for ClampFunction {
                 ),
             }
         );
-
+        ensure!(
-        ensure_constant_vector(&columns[1])?;
+            (columns[1].len() == 1 || columns[1].is_const())
-        ensure_constant_vector(&columns[2])?;
+                && (columns[2].len() == 1 || columns[2].is_const()),
+            InvalidFuncArgsSnafu {
+                err_msg: format!(
+                    "The second and third args should be scalar, have: {:?}, {:?}",
+                    columns[1], columns[2]
+                ),
+            }
+        );
 
         with_match_primitive_type_id!(columns[0].data_type().logical_type_id(), |$S| {
             let input_array = columns[0].to_arrow_array();
@@ -224,8 +204,15 @@ impl Function for ClampMinFunction {
                 ),
             }
         );
-
+        ensure!(
-        ensure_constant_vector(&columns[1])?;
+            columns[1].len() == 1 || columns[1].is_const(),
+            InvalidFuncArgsSnafu {
+                err_msg: format!(
+                    "The second arg (min) should be scalar, have: {:?}",
+                    columns[1]
+                ),
+            }
+        );
 
         with_match_primitive_type_id!(columns[0].data_type().logical_type_id(), |$S| {
             let input_array = columns[0].to_arrow_array();
@@ -305,8 +292,15 @@ impl Function for ClampMaxFunction {
                 ),
             }
         );
-
+        ensure!(
-        ensure_constant_vector(&columns[1])?;
+            columns[1].len() == 1 || columns[1].is_const(),
+            InvalidFuncArgsSnafu {
+                err_msg: format!(
+                    "The second arg (max) should be scalar, have: {:?}",
+                    columns[1]
+                ),
+            }
+        );
 
         with_match_primitive_type_id!(columns[0].data_type().logical_type_id(), |$S| {
             let input_array = columns[0].to_arrow_array();
@@ -543,8 +537,8 @@ mod test {
         let func = ClampFunction;
         let args = [
             Arc::new(Float64Vector::from(input)) as _,
-            Arc::new(Float64Vector::from_vec(vec![min, max])) as _,
+            Arc::new(Float64Vector::from_vec(vec![min, min])) as _,
-            Arc::new(Float64Vector::from_vec(vec![max, min])) as _,
+            Arc::new(Float64Vector::from_vec(vec![max])) as _,
         ];
         let result = func.eval(&FunctionContext::default(), args.as_slice());
         assert!(result.is_err());

src/common/function/src/scalars/udf.rs

@@ -16,12 +16,15 @@ use std::any::Any;
 use std::fmt::{Debug, Formatter};
 use std::sync::Arc;
 
+use common_query::error::FromScalarValueSnafu;
 use common_query::prelude::ColumnarValue;
 use datafusion::logical_expr::{ScalarFunctionArgs, ScalarUDFImpl};
 use datafusion_expr::ScalarUDF;
 use datatypes::data_type::DataType;
 use datatypes::prelude::*;
+use datatypes::vectors::Helper;
 use session::context::QueryContextRef;
+use snafu::ResultExt;
 
 use crate::function::{FunctionContext, FunctionRef};
 use crate::state::FunctionState;
@@ -73,7 +76,13 @@ impl ScalarUDFImpl for ScalarUdf {
         let columns = args
             .args
             .iter()
-            .map(|x| ColumnarValue::try_from(x).and_then(|y| y.try_into_vector(args.number_rows)))
+            .map(|x| {
+                ColumnarValue::try_from(x).and_then(|y| match y {
+                    ColumnarValue::Vector(z) => Ok(z),
+                    ColumnarValue::Scalar(z) => Helper::try_from_scalar_value(z, args.number_rows)
+                        .context(FromScalarValueSnafu),
+                })
+            })
             .collect::<common_query::error::Result<Vec<_>>>()?;
         let v = self
             .function
@@ -104,8 +113,6 @@ mod tests {
 
     use common_query::prelude::ScalarValue;
     use datafusion::arrow::array::BooleanArray;
-    use datafusion_common::config::ConfigOptions;
-    use datatypes::arrow::datatypes::Field;
     use datatypes::data_type::ConcreteDataType;
     use datatypes::prelude::VectorRef;
     use datatypes::vectors::{BooleanVector, ConstantVector};
@@ -155,21 +162,10 @@ mod tests {
             ]))),
         ];
 
-        let arg_fields = vec![
-            Arc::new(Field::new("a", args[0].data_type(), false)),
-            Arc::new(Field::new("b", args[1].data_type(), false)),
-        ];
-        let return_field = Arc::new(Field::new(
-            "x",
-            ConcreteDataType::boolean_datatype().as_arrow_type(),
-            false,
-        ));
         let args = ScalarFunctionArgs {
             args,
-            arg_fields,
             number_rows: 4,
-            return_field,
+            return_type: &ConcreteDataType::boolean_datatype().as_arrow_type(),
-            config_options: Arc::new(ConfigOptions::default()),
         };
         match udf.invoke_with_args(args).unwrap() {
             datafusion_expr::ColumnarValue::Array(x) => {

src/common/function/src/system.rs

@@ -19,6 +19,8 @@ mod procedure_state;
 mod timezone;
 mod version;
 
+use std::sync::Arc;
+
 use build::BuildFunction;
 use database::{
     ConnectionIdFunction, CurrentSchemaFunction, DatabaseFunction, PgBackendPidFunction,
@@ -44,7 +46,7 @@ impl SystemFunction {
         registry.register_scalar(PgBackendPidFunction);
         registry.register_scalar(ConnectionIdFunction);
         registry.register_scalar(TimezoneFunction);
-        registry.register(ProcedureStateFunction::factory());
+        registry.register_async(Arc::new(ProcedureStateFunction));
         PGCatalogFunction::register(registry);
     }
 }

src/common/function/src/system/procedure_state.rs

@@ -13,14 +13,13 @@
 // limitations under the License.
 
 use api::v1::meta::ProcedureStatus;
-use arrow::datatypes::DataType as ArrowDataType;
 use common_macro::admin_fn;
 use common_meta::rpc::procedure::ProcedureStateResponse;
 use common_query::error::{
     InvalidFuncArgsSnafu, MissingProcedureServiceHandlerSnafu, Result,
     UnsupportedInputDataTypeSnafu,
 };
-use datafusion_expr::{Signature, Volatility};
+use common_query::prelude::{Signature, Volatility};
 use datatypes::prelude::*;
 use serde::Serialize;
 use session::context::QueryContextRef;
@@ -82,86 +81,73 @@ pub(crate) async fn procedure_state(
 }
 
 fn signature() -> Signature {
-    Signature::uniform(1, vec![ArrowDataType::Utf8], Volatility::Immutable)
+    Signature::uniform(
+        1,
+        vec![ConcreteDataType::string_datatype()],
+        Volatility::Immutable,
+    )
 }
 
 #[cfg(test)]
 mod tests {
     use std::sync::Arc;
 
-    use arrow::array::StringArray;
+    use common_query::prelude::TypeSignature;
-    use arrow::datatypes::{DataType, Field};
+    use datatypes::vectors::StringVector;
-    use datafusion_expr::ColumnarValue;
 
     use super::*;
-    use crate::function::FunctionContext;
+    use crate::function::{AsyncFunction, FunctionContext};
-    use crate::function_factory::ScalarFunctionFactory;
 
     #[test]
     fn test_procedure_state_misc() {
-        let factory: ScalarFunctionFactory = ProcedureStateFunction::factory().into();
+        let f = ProcedureStateFunction;
-        let f = factory.provide(FunctionContext::mock());
         assert_eq!("procedure_state", f.name());
-        assert_eq!(DataType::Utf8, f.return_type(&[]).unwrap());
+        assert_eq!(
+            ConcreteDataType::string_datatype(),
+            f.return_type(&[]).unwrap()
+        );
         assert!(matches!(f.signature(),
-                         datafusion_expr::Signature {
+                         Signature {
-                             type_signature: datafusion_expr::TypeSignature::Uniform(1, valid_types),
+                             type_signature: TypeSignature::Uniform(1, valid_types),
-                             volatility: datafusion_expr::Volatility::Immutable
+                             volatility: Volatility::Immutable
-                         } if valid_types == &vec![ArrowDataType::Utf8]));
+                         } if valid_types == vec![ConcreteDataType::string_datatype()]
+        ));
     }
 
     #[tokio::test]
     async fn test_missing_procedure_service() {
-        let factory: ScalarFunctionFactory = ProcedureStateFunction::factory().into();
+        let f = ProcedureStateFunction;
-        let binding = factory.provide(FunctionContext::default());
-        let f = binding.as_async().unwrap();
 
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        let args = vec!["pid"];
-            args: vec![ColumnarValue::Array(Arc::new(StringArray::from(vec![
+
-                "pid",
+        let args = args
-            ])))],
+            .into_iter()
-            arg_fields: vec![Arc::new(Field::new("arg_0", DataType::Utf8, false))],
+            .map(|arg| Arc::new(StringVector::from_slice(&[arg])) as _)
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
+            .collect::<Vec<_>>();
-            number_rows: 1,
+
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
+        let result = f.eval(FunctionContext::default(), &args).await.unwrap_err();
-        };
+        assert_eq!(
-        let result = f.invoke_async_with_args(func_args).await;
+            "Missing ProcedureServiceHandler, not expected",
-        assert!(result.is_err());
+            result.to_string()
+        );
     }
 
     #[tokio::test]
     async fn test_procedure_state() {
-        let factory: ScalarFunctionFactory = ProcedureStateFunction::factory().into();
+        let f = ProcedureStateFunction;
-        let provider = factory.provide(FunctionContext::mock());
-        let f = provider.as_async().unwrap();
 
-        let func_args = datafusion::logical_expr::ScalarFunctionArgs {
+        let args = vec!["pid"];
-            args: vec![ColumnarValue::Array(Arc::new(StringArray::from(vec![
-                "pid",
-            ])))],
-            arg_fields: vec![Arc::new(Field::new("arg_0", DataType::Utf8, false))],
-            return_field: Arc::new(Field::new("result", DataType::Utf8, true)),
-            number_rows: 1,
-            config_options: Arc::new(datafusion_common::config::ConfigOptions::default()),
-        };
-        let result = f.invoke_async_with_args(func_args).await.unwrap();
 
-        match result {
+        let args = args
-            ColumnarValue::Array(array) => {
+            .into_iter()
-                let result_array = array.as_any().downcast_ref::<StringArray>().unwrap();
+            .map(|arg| Arc::new(StringVector::from_slice(&[arg])) as _)
-                assert_eq!(
+            .collect::<Vec<_>>();
-                    result_array.value(0),
+
-                    "{\"status\":\"Done\",\"error\":\"OK\"}"
+        let result = f.eval(FunctionContext::mock(), &args).await.unwrap();
-                );
+
-            }
+        let expect: VectorRef = Arc::new(StringVector::from(vec![
-            ColumnarValue::Scalar(scalar) => {
+            "{\"status\":\"Done\",\"error\":\"OK\"}",
-                assert_eq!(
+        ]));
-                    scalar,
+        assert_eq!(expect, result);
-                    datafusion_common::ScalarValue::Utf8(Some(
-                        "{\"status\":\"Done\",\"error\":\"OK\"}".to_string()
-                    ))
-                );
-            }
-        }
     }
 }

src/common/grpc/Cargo.toml

@@ -20,7 +20,7 @@ common-telemetry.workspace = true
 common-time.workspace = true
 dashmap.workspace = true
 datatypes.workspace = true
-flatbuffers = "25.2"
+flatbuffers = "24"
 hyper.workspace = true
 lazy_static.workspace = true
 prost.workspace = true