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A broad documentation pass across the areas LanceDB Enterprise and Embedded diverge on most: **Data Curation** -- GPU Function execution, Slurm scheduling (and what Slurm is, for readers new to it), blob late materialization as its own page, joins, aggregation/profiling, sampling, near-duplicate detection, chunking, distributed shuffle, and IVF-partition clustering. **Feature Engineering** -- computed columns and materialized views, restructured to lead with the Function-based path and show the SQL form side by side with Python throughout; a single Auto Refresh page instead of duplicating scheduling details on every refresh page; adaptive execution; checkpointing; GPU and Slurm placement for refresh workers; a Training Cache page for the PyTorch data loader's automatic cache benefit. **Security & Governance** -- an Audit Log reference (schema, access, grants), Secrets promoted to an ordinary catalog object with their own SQL DDL and a vending/rotation guide, and privilege-table fixes verified against the authorization source. **Deployment & Maintenance** -- Horizontal Scaling and OpenTelemetry moved into a real Deployment area; Automated Cleanup folded into Intelligent Auto-Maintenance (every other maintenance decision already lived there); RTE Compaction and Advanced Conflict Resolution documented in depth. **Landing page** -- the Enterprise feature comparison table reorganized (several redundant or stale rows removed, several new areas added), and the "why Enterprise" bullets replaced with ones tied to a concrete page (Performance, Scale, Fault tolerance, Multicloud deployment, Simplify operations) instead of vague promises. Plus a full pass addressing lancedb-gatekeeper's review: a real test-safety bug (a quickstart test could silently overwrite and delete a deployment's own `frames` table), a fabricated SQL statement with no backing implementation, an actual dedup-guarantee bug in `take_row_ids`, and dozens of documentation-accuracy fixes verified against source rather than taken on faith -- each either fixed, or left with an explicit note on why it needs a feature or deployment owner's sign-off instead of being guessed at. 🤖 Generated with [Claude Code](https://claude.com/claude-code) https://claude.ai/code/session_018PXMCbRH6i5w47TsjeEUMT --------- Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
50 lines
1.8 KiB
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50 lines
1.8 KiB
Plaintext
---
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title: "Distributed write"
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sidebarTitle: "Distributed write"
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description: "How LanceDB Enterprise distributes a CTAS import's writes across plan executors."
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icon: upload
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availability:
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embedded: unavailable
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enterprise: available
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---
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Distributed write applies specifically to importing data with `CREATE
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TABLE ... AS SELECT`: the query node that planned the statement partitions
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the source -- Parquet files from a HuggingFace dataset, or row-group
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ranges of an existing Lance dataset in object storage -- across plan
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executors, each of which writes its own uncommitted Lance data files and
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reports back. The query node collects those results and commits them
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together as the new table's first version; no separate coordinator
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service is involved. See [Architecture](/index#architecture).
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```mermaid
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flowchart LR
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S["Source<br/>HuggingFace Parquet, or an<br/>existing Lance dataset in<br/>S3 / GCS / Azure"]
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Q["Query node<br/>plans the CTAS,<br/>commits the result"]
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PE1["Plan executor<br/>writes uncommitted files"]
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PE2["Plan executor<br/>writes uncommitted files"]
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PE3["Plan executor<br/>writes uncommitted files"]
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S --> Q
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Q --> PE1
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Q --> PE2
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Q --> PE3
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PE1 --> Q
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PE2 --> Q
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PE3 --> Q
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```
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An ordinary `INSERT` or `merge_insert`, from SQL or the SDK, does not
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distribute this way -- it runs as a single write, on whichever node or
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process executes it. Only a CTAS import fans the write itself out across
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machines.
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## Write interfaces {#write-interfaces}
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- [Import Datasets](/ingestion/import) for the CTAS syntax this
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distributes.
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- [Insert data](/ingestion/insert) and [Merge](/ingestion/merge-insert)
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for the ordinary, non-distributed write paths.
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- [Storage Integration](/sql/ddl/storage-integration) for configuring
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the source a CTAS import reads from.
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