e375a18011
* refactor: use proc macro to generate conversion between TableMeta and TableMetaBuilder
* chore: format
* fix/partition-key-index:
### Update `TableMeta` and Add Partition and Alter Table Tests
- **`metadata.rs`**: Modified `new_meta_builder` method in `TableMeta` to manually remove `value_indices` by setting it to `None` in the `TableMetaBuilder`.
- **`partition_and_alter.result` & `partition_and_alter.sql`**: Added new test cases for creating, inserting, selecting, altering, and dropping a partitioned table `molestiAe`. These tests verify partitioning on the `sImiLiQUE` column and altering the table with a TTL
setting.
fix/partition-key-index:
### Remove Obsolete TODO Comment in `metadata.rs`
- Removed an outdated TODO comment regarding the `new_meta_builder` function in `src/table/src/metadata.rs`.
chore: check struct name in derive_meta_builder
refactor: Simplify TableMeta struct name check in macro
refactor: Improve ToMetaBuilder derive macro validation and error handling
refactor: Enforce ToMetaBuilder macro for table::metadata::TableMeta struct
* fix/partition-key-index:
Update `partition_and_alter.sql` to modify TTL setting
- Modified the TTL setting for the `molestiAe` table to '1d' in `partition_and_alter.sql`.
* fix: sqlness
* fix/partition-key-index:
### Update `TableMeta` and Test File Structure
- **Enhancement**: Added a note in `metadata.rs` to always use `new_meta_builder` for creating `TableMetaBuilder`.
- **Refactor**: Renamed test result and SQL files for better organization:
- `partition_and_alter.result` to `alter/partition_and_alter.result`
- `partition_and_alter.sql` to `alter/partition_and_alter.sql`
* refactor: Simplify `derive_meta_builder` by initializing fields with `Default::default()`
* fix/partition-key-index:
### Commit Summary
- **Refactor `TableMetaBuilder` Initialization**:
- Replaced `TableMetaBuilder::default()` with `TableMetaBuilder::empty()` across multiple files for initializing `TableMetaBuilder` instances.
- Affected files include:
- `src/catalog/src/system_schema.rs`
- `src/common/meta/src/key/test_utils.rs`
- `src/operator/src/req_convert/insert/fill_impure_default.rs`
- `src/query/src/log_query/planner.rs`
- `src/query/src/promql/planner.rs`
- `src/query/src/range_select/plan_rewrite.rs`
- `src/query/src/sql/show_create_table.rs`
- `src/table/src/test_util/memtable.rs`
- `src/table/src/test_util/table_info.rs`
- **Enhance `TableMetaBuilder`**:
- Added `custom_constructor` to `TableMeta` and implemented an `empty` method for `TableMetaBuilder`.
- Modified `TableMetaBuilder` to include a `new_external_table` method with default values.
- Updated `src/table/src/metadata.rs` to reflect these changes.
- **Add Testing Feature**:
- Introduced a conditional compilation for `test_util` in `src/table/src/lib.rs` to include testing utilities when the `testing` feature is enabled.
- **Update `Cargo.toml`**:
- Enabled the `testing` feature for the `table` module in `src/common/meta/Cargo.toml`.
- **Modify `NumbersTable` Initialization**:
- Replaced `TableMetaBuilder` with direct `TableMeta` struct initialization in `src/table/src/table/numbers.rs`.
- **Test Result Update**:
- Updated test results in `tests/cases/standalone/common/alter/partition_and_alter.result` to reflect changes in table meta handling.
* fix: rename default to empty
* docs: add doc for TableMetaBuilder::empty
* chore: Update src/table/src/metadata.rs
---------
Co-authored-by: Yingwen <realevenyag@gmail.com>
Unified & Cost-Effective Time Series Database for Metrics, Logs, and Events
- Introduction
- Features: Why GreptimeDB
- Architecture
- Try it for free
- Getting Started
- Project Status
- Join the community
- Tools & Extensions
- License
- Acknowledgement
Introduction
GreptimeDB is an open-source unified & cost-effective time-series database for Metrics, Logs, and Events (also Traces in plan). You can gain real-time insights from Edge to Cloud at Any Scale.
Why GreptimeDB
Our core developers have been building time-series data platforms for years. Based on our best practices, GreptimeDB was born to give you:
-
Unified Processing of Metrics, Logs, and Events
GreptimeDB unifies time series data processing by treating all data - whether metrics, logs, or events - as timestamped events with context. Users can analyze this data using either SQL or PromQL and leverage stream processing (Flow) to enable continuous aggregation. Read more.
-
Cloud-native Distributed Database
Built for Kubernetes. GreptimeDB achieves seamless scalability with its cloud-native architecture of separated compute and storage, built on object storage (AWS S3, Azure Blob Storage, etc.) while enabling cross-cloud deployment through a unified data access layer.
-
Performance and Cost-effective
Written in pure Rust for superior performance and reliability. GreptimeDB features a distributed query engine with intelligent indexing to handle high cardinality data efficiently. Its optimized columnar storage achieves 50x cost efficiency on cloud object storage through advanced compression. Benchmark reports.
-
Cloud-Edge Collaboration
GreptimeDB seamlessly operates across cloud and edge (ARM/Android/Linux), providing consistent APIs and control plane for unified data management and efficient synchronization. Learn how to run on Android.
-
Multi-protocol Ingestion, SQL & PromQL Ready
Widely adopted database protocols and APIs, including MySQL, PostgreSQL, InfluxDB, OpenTelemetry, Loki and Prometheus, etc. Effortless Adoption & Seamless Migration. Supported Protocols Overview.
For more detailed info please read Why GreptimeDB.
Try GreptimeDB
1. Live Demo
Try out the features of GreptimeDB right from your browser.
2. GreptimeCloud
Start instantly with a free cluster.
3. Docker Image
To install GreptimeDB locally, the recommended way is via Docker:
docker pull greptime/greptimedb
Start a GreptimeDB container with:
docker run -p 127.0.0.1:4000-4003:4000-4003 \
-v "$(pwd)/greptimedb:/tmp/greptimedb" \
--name greptime --rm \
greptime/greptimedb:latest standalone start \
--http-addr 0.0.0.0:4000 \
--rpc-bind-addr 0.0.0.0:4001 \
--mysql-addr 0.0.0.0:4002 \
--postgres-addr 0.0.0.0:4003
Access the dashboard via http://localhost:4000/dashboard.
Read more about Installation on docs.
Getting Started
Build
Check the prerequisite:
- Rust toolchain (nightly)
- Protobuf compiler (>= 3.15)
- C/C++ building essentials, including
gcc/g++/autoconfand glibc library (eg.libc6-devon Ubuntu andglibc-develon Fedora) - Python toolchain (optional): Required only if using some test scripts.
Build GreptimeDB binary:
make
Run a standalone server:
cargo run -- standalone start
Tools & Extensions
Kubernetes
Dashboard
SDK
- GreptimeDB Go Ingester
- GreptimeDB Java Ingester
- GreptimeDB C++ Ingester
- GreptimeDB Erlang Ingester
- GreptimeDB Rust Ingester
- GreptimeDB JavaScript Ingester
Grafana Dashboard
Our official Grafana dashboard for monitoring GreptimeDB is available at grafana directory.
Project Status
GreptimeDB is currently in Beta. We are targeting GA (General Availability) with v1.0 release by Early 2025.
While in Beta, GreptimeDB is already:
- Being used in production by early adopters
- Actively maintained with regular releases, about version number
- Suitable for testing and evaluation
For production use, we recommend using the latest stable release.
Community
Our core team is thrilled to see you participate in any ways you like. When you are stuck, try to ask for help by filling an issue with a detailed description of what you were trying to do and what went wrong. If you have any questions or if you would like to get involved in our community, please check out:
- GreptimeDB Community on Slack
- GreptimeDB GitHub Discussions forum
- Greptime official website
In addition, you may:
Commercial Support
If you are running GreptimeDB OSS in your organization, we offer additional enterprise add-ons, installation services, training, and consulting. Contact us and we will reach out to you with more detail of our commercial license.
License
GreptimeDB uses the Apache License 2.0 to strike a balance between open contributions and allowing you to use the software however you want.
Contributing
Please refer to contribution guidelines and internal concepts docs for more information.
Acknowledgement
Special thanks to all the contributors who have propelled GreptimeDB forward. For a complete list of contributors, please refer to AUTHOR.md.
- GreptimeDB uses Apache Arrow™ as the memory model and Apache Parquet™ as the persistent file format.
- GreptimeDB's query engine is powered by Apache Arrow DataFusion™.
- Apache OpenDAL™ gives GreptimeDB a very general and elegant data access abstraction layer.
- GreptimeDB's meta service is based on etcd.