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## What Renames the MemWAL surface in two passes, across Rust, Python, TypeScript, and Java, including the wire format. ### 1. MemWAL APIs drop "LSM" The write path these APIs drive is Lance's MemWAL; "LSM" described its shape rather than naming it. Turning it on and off now reads as enabling a feature rather than installing a spec. | Before | After | |---|---| | `set_lsm_write_spec` | `enable_memwal` | | `unset_lsm_write_spec` | `disable_memwal` | | `get_lsm_write_spec` | `get_memwal_spec` | | `flush_lsm` / `compact_lsm` / `checkpoint_lsm` | `flush_memwal` / `compact_memwal` / `checkpoint_memwal` | | `get_lsm_stats` | `get_memwal_stats` | | `close_lsm_writers` | `close_memwal_writers` | | `use_lsm` (query, merge insert) | `use_memwal` | | `LsmWriteSpec` / `LsmStats` | `MemWalWriteSpec` / `MemWalStats` | | Java `LanceDbTableLsm` | `LanceDbTableMemWal` | TypeScript and Java use camelCase (`enableMemWal`, `getMemWalStats`, ...); the napi methods set `js_name` so the generated names keep the `MemWal` casing. flush/compact/checkpoint keep a `_memwal` suffix so `compact_memwal` is not confused with `compact_files` / `optimize`, which compact the base table. Internal names (`LsmMode`, `LsmScanner`, the `merge::lsm` / `query::lsm` modules) are unchanged. ### 2. Stats use SSTable and table shard Aligns the stats surface with the MemWAL naming settled upstream in lance-format/lance#7943 and #7957, where the persisted unit became an **SSTable**. **Generation → SSTable.** A `GenerationStats` describes one flushed MemTable, which is an SSTable. The generation *number* is kept — an SSTable is identified by its generation — so only the noun moved. **Bucket → table shard.** Each entry is one MemWAL shard. "Bucket" names only the hash sharding *transform*, so it was already wrong for `identity` and `year` sharding, which produce shards and no buckets at all. | Before | After | |---|---| | `GenerationStats` | `SsTableStats` | | `BucketStats` | `TableShardStats` | | `stats.buckets` | `stats.table_shards` | | `BucketStats.generations` | `TableShardStats.sstables` | | `include_generation_rows` | `include_sstable_rows` | | `newest_generation` | `newest_sstable_generation` | | `outstanding_generations` | `outstanding_sstables` | Docs and comments follow suit: "seal" → "freeze", "L0" / "flushed generations" → SSTables, "bucket" (meaning a shard) → table shard. `MemWalWriteSpec::bucket`, `num_buckets`, and the `"Sealed"` shard status value are **unchanged** — those name the sharding transform or a server value, not the shard. ## Compatibility Breaking, for an experimental API. The wire format changes with the SDKs, so this must roll out together with the matching server change: - Routes: `/set_lsm_write_spec/` → `/enable_memwal/`, `/unset_lsm_write_spec/` → `/disable_memwal/`, `/get_lsm_write_spec/` → `/get_memwal_spec/`, `/flush_lsm/` → `/flush_memwal/`, `/compact_lsm/` → `/compact_memwal/`, `/get_lsm_stats/` → `/get_memwal_stats/` - Response keys: `lsm_write_spec` → `memwal_spec`, `lsm_stats` → `memwal_stats`, `buckets` → `table_shards`, `generations` → `sstables` - Request fields: `include_generation_rows` → `include_sstable_rows`; `use_lsm` → `use_memwal` on query and merge-insert bodies ## Validation - Rust: `cargo test --features remote -p lancedb --lib --tests` — 1467 lib tests and all integration test targets pass; `cargo clippy` clean - Python: rebuilt the extension; `test_remote_db`, `test_memwal_spec`, `test_merge_insert_lsm`, `test_query`, `test_permutation`, `test_table` — 655 passed; `ruff format` / `ruff check` clean - TypeScript: `pnpm build`; `table`, `merge`, `query` tests — 593 passed; `biome check` clean; `docs/src/js` regenerated with `npm run docs` - Java: `mvn test` — 37 passed (Spotless applied with JDK 11; the pinned google-java-format does not run on JDK 21) 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
187 lines
5.9 KiB
Plaintext
187 lines
5.9 KiB
Plaintext
---
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title: "Table"
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sidebarTitle: "Table"
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description: "CREATE, DESCRIBE, ALTER, CLONE and DROP TABLE."
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icon: table
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keywords: ["create table", "alter table", "drop table", "describe", "clone", "ddl"]
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---
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<Badge color="red">Enterprise</Badge> [SQL runs in LanceDB Enterprise.](/sql)
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## CREATE TABLE {#create}
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```sql
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CREATE TABLE documents (id BIGINT, title VARCHAR, created_at TIMESTAMP)
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CREATE TABLE recent AS SELECT * FROM documents WHERE created_at > now() - INTERVAL '7 days'
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```
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Column types are Arrow types under SQL names -- see [Data types](/sql/data-types).
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A table inside a [namespace](/sql/ddl/namespace) is written as a dotted path:
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`prod.events.clicks`.
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## DESCRIBE {#describe}
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```sql
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DESCRIBE documents
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```
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The table's columns and types, without a plan -- the SQL counterpart of
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`table.schema`.
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## ALTER TABLE {#alter}
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What `ALTER TABLE ... ADD COLUMN` does depends on what follows the column
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name.
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### A plain column {#plain-column}
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SQL `ADD COLUMN` requires an `AS` binding, so a plain column such as
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`ALTER TABLE t ADD COLUMN c INT` is rejected. Add an empty, nullable column
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with the SDK instead -- see
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[Add nullable columns](/management/table#schema-add-nullable-columns).
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### A computed column {#computed-column}
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```sql
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ALTER TABLE t ADD COLUMN doubled AS value * 2
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```
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`AS <expression>` declares a [computed column](/feature-engineering/add-computed-column).
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The column is committed empty and the expression is stored, not evaluated --
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declaring one on a billion-row table costs what declaring one on an empty table
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costs. [`REFRESH COLUMN`](/sql/dml/refresh) fills it.
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{/*
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Draft for the Functions release.
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### A function column {#function-column}
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```sql
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ALTER TABLE t ADD COLUMN embedded AS embed(name) WITH (version = 'fv_1')
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```
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When the expression calls a [registered function](/sql/ddl/function), the
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column is filled by running that function on workers. `version` pins which
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immutable function version fills it, so a later registration does not silently
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change what the column means.
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Several modifiers narrow what gets computed:
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| --- | --- |
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| `FILTER (WHERE pred)` | only rows matching `pred` are computed |
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| `IGNORE NULLS` | rows with null inputs are skipped |
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| `OVER (PARTITION BY col)` | the function sees rows grouped by `col` |
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A function returning several values fills several columns at once:
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```sql
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ALTER TABLE t ADD COLUMN (label, score) AS classify(text) WITH (version = 'fv_1')
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```
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```sql
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ALTER TABLE t ADD COLUMN c AS f(x) FILTER (WHERE keep) WITH (version = 'fv_1')
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ALTER TABLE t ADD COLUMN c AS f(x) WITH (num_workers = '2')
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```
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<Note>
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`WITH` on a plain computed column accepts only `version`. Resource options such
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as `num_workers` apply to function columns, where there are workers to size.
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</Note>
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*/}
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### Table properties {#properties}
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```sql
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ALTER TABLE t SET UNENFORCED PRIMARY KEY (id)
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```
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Records which column identifies a row. **Unenforced** is not a hedge in the
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naming: uniqueness is not checked on write, and declaring it does not make
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duplicates impossible. It tells the planner what to assume. The column must be
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declared `NOT NULL`.
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```sql
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ALTER TABLE t SET MEMWAL
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ALTER TABLE t SET MEMWAL WITH (sharding = 'bucket', column = 'id', buckets = 4)
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ALTER TABLE t SET MEMWAL WITH (maintained_indexes = '')
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ALTER TABLE t UNSET MEMWAL
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```
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A write-ahead log makes small frequent writes cheap by batching them out of the
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commit path. `sharding` and `buckets` spread the log so concurrent writers do
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not contend on one place; `bucket` sharding names its `column`, which must be
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the table's unenforced primary key, and inserts into the table then need a
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scalar index on that key. `maintained_indexes` chooses which indexes are kept
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current against WAL rows. A table with a computed column cannot take a
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write-ahead log. See
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[Background jobs](/maintenance/background-jobs#wal) for how the log gets
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folded back into the table.
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<Warning>
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[`TABLESAMPLE`](/sql/dql/sampling) is refused on a WAL-backed table, because
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rows a sample would draw from are not all in the fragments yet.
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</Warning>
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**Errors and limits**
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| --- | --- |
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| `ALTER TABLE ... DROP COLUMN` | not supported |
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Dropping, renaming, or retyping a column is an SDK operation --
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[`drop_columns`](/management/table#schema) and
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[`alter_columns`](/management/table#schema) -- not a SQL statement.
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## CLONE {#clone}
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```sql
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CREATE TABLE docs_snapshot CLONE documents
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CREATE TABLE docs_at_v42 CLONE documents AT 42
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CREATE TABLE docs_at_release CLONE documents AT TAG 'release-1'
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CREATE TABLE docs_yesterday CLONE documents AT TIMESTAMP '2026-09-01T00:00:00Z'
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```
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A **shallow clone**: the new table shares the source's data files rather than
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copying them, so it costs one metadata commit regardless of the source's size.
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`AT` pins the point in the source's history to clone. A bare integer is a
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version and a bare quoted string is a timestamp; `VERSION`, `TAG` and
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`TIMESTAMP` say so explicitly, and a tag always needs its keyword -- a bare
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quoted string cannot be both a tag name and a timestamp.
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<Warning>
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The clone depends on the source's files continuing to exist. If the source is
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[compacted](/maintenance/cleanup) past the retention window, the version the
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clone points at can be pruned. The SDK's
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[`clone_table`](/management/table#rename-clone) also offers a deep clone for
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when the copy has to outlive the source's history.
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</Warning>
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## DROP TABLE {#drop}
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```sql
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DROP TABLE documents
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```
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<Warning>
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Removes the table and every version of it. There is no undrop.
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</Warning>
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<Note>
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**Enterprise job type:** `drop_table` or `drop_object`, depending on how the
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deployment stores its catalog. See
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[Background jobs](/maintenance/background-jobs#teardown).
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</Note>
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## What to read next {#next}
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<CardGroup cols={2}>
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<Card title="Table" icon="table" href="/management/table">
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The SDK equivalent, and what a table carries.
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</Card>
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<Card title="Schema evolution" icon="boxes-stacked" href="/management/table#schema">
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Renaming, retyping and dropping columns from the SDK.
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</Card>
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</CardGroup>
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