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Jack Ye
ddb318567a
## Summary - Complete the SQL reference: `ATTACH DATABASE`, the `CHANGES` clause, and `dedupe()`/`duplicate_pairs()` (verified against current sophon source; these were recently renamed from `vector_dedup`/`vector_duplicate_pairs`). Fix the blob-column default-projection claim and add the previously undocumented `blob_descriptor()`. - Enrich the gated Functions draft (still `.mintignore`'d, pre-release): chained Functions over blob outputs, GPU-produced blobs, Secrets, multi-input/output binding, `code=[module]` packaging. - Upgrade the materialized-view and computed-column auto-refresh drafts with precise, verified catch-up semantics, and add the missing `ALTER MATERIALIZED VIEW` / `CREATE ... WITH(...)` sections (also gated — the automatic-refresh scheduler is still dev/staging-only). - Thread one running example (video frames → GPU extract/caption → dedup → auto-refreshing materialized view) through Functions, materialized views, and the LeRobotDataset integration guide instead of a separate tutorial. - Rename "LanceDB OSS"/"OSS" to "LanceDB Embedded"/"Embedded" throughout (52 files); activate the existing availability-comparison mechanism on `basics/offerings.mdx` for a full feature-by-feature comparison table.
55 lines
2.0 KiB
Plaintext
55 lines
2.0 KiB
Plaintext
---
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title: "Explain"
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sidebarTitle: "Explain"
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description: "EXPLAIN, EXPLAIN ANALYZE and EXPLAIN VERBOSE: reading and measuring a plan from SQL."
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icon: map
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keywords: ["explain", "explain analyze", "explain verbose", "query plan"]
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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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```sql
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EXPLAIN SELECT * FROM documents WHERE identifier < 1000
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EXPLAIN ANALYZE SELECT * FROM documents WHERE identifier < 1000
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```
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| Statement | What it returns |
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| --- | --- |
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| `EXPLAIN <query>` | Logical and physical plan, without executing the query. |
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| `EXPLAIN ANALYZE <query>` | Executes the query and annotates each operator with runtime metrics (rows, timing). |
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| `EXPLAIN VERBOSE <query>` | Adds intermediate optimizer plans on top of `EXPLAIN`. |
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The result is a small relation with `plan_type` and `plan` columns, read
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through the same client you use for regular queries. See
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[Connecting](/sql#connecting).
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SQL plans and the SDK's
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[`explain_plan` and `analyze_plan`](/search/explain) output share scan and index
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operators. Use the same approach to inspect index coverage and filter pushdown;
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SQL can also add joins, aggregates and other operators:
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<CardGroup cols={2}>
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<Card title="What it shows" icon="map" href="/search/explain#inspect-a-query-plan">
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Reading a plan: operators, pushdown, index usage.
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</Card>
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<Card title="What it measures" icon="gauge" href="/search/explain#analyze-a-query-plan">
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Reading the metrics, and a worked before/after.
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</Card>
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</CardGroup>
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## What to look for {#what-to-look-for}
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| Sign | Means |
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| --- | --- |
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| `ScalarIndexQuery` | the predicate used a scalar index |
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| `LanceScan` with high `bytes_read` | inspect the selected columns, filter pushdown and index use |
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| `FilterExec` above a search | the filter ran after search rather than pushing into it |
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| `ANNSubIndex` / `ANNIvfPartition` | the vector index was used |
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A `LanceScan` feeding a join is the common one worth acting on. See
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[Joins](/sql/dql/join#performance).
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For a table's columns and types without a plan, see
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[`DESCRIBE`](/sql/ddl/table#describe).
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