mirror of
https://github.com/lancedb/lancedb.git
synced 2026-11-13 14:16:54 +00:00
Jack YeandClaude Sonnet 5
de95ed3f6d
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>
89 lines
2.6 KiB
Plaintext
89 lines
2.6 KiB
Plaintext
---
|
|
title: "Subqueries"
|
|
sidebarTitle: "Subqueries"
|
|
description: "Queries inside queries: scalar, IN, EXISTS, correlated, and derived tables."
|
|
icon: code-branch
|
|
keywords: ["subquery", "exists", "in", "correlated", "derived table", "lateral"]
|
|
availability:
|
|
embedded: unavailable
|
|
enterprise: available
|
|
---
|
|
|
|
A subquery is allowed anywhere an expression or a relation is.
|
|
|
|
## As a relation {#derived}
|
|
|
|
<CodeGroup>
|
|
```sql SQL icon="database"
|
|
SELECT * FROM (
|
|
SELECT category, count(*) AS n FROM documents GROUP BY category
|
|
) AS counts
|
|
WHERE n > 100
|
|
```
|
|
</CodeGroup>
|
|
|
|
A derived table needs an alias. Its result cannot be
|
|
[sampled](/sql/dql/sampling); sample the table inside it instead:
|
|
|
|
<CodeGroup>
|
|
```sql SQL icon="database"
|
|
SELECT * FROM (SELECT * FROM documents TABLESAMPLE (10)) d
|
|
```
|
|
</CodeGroup>
|
|
|
|
## As a scalar {#scalar}
|
|
|
|
<CodeGroup>
|
|
```sql SQL icon="database"
|
|
SELECT title, (SELECT count(*) FROM revisions r WHERE r.doc_id = d.id) AS revisions
|
|
FROM documents AS d
|
|
```
|
|
</CodeGroup>
|
|
|
|
A scalar subquery returns one column and at most one row. No rows produces
|
|
`NULL`; more than one row is an error.
|
|
|
|
## IN and EXISTS {#in-exists}
|
|
|
|
<CodeGroup>
|
|
```sql SQL icon="database"
|
|
SELECT title FROM documents
|
|
WHERE category_id IN (SELECT id FROM categories WHERE active)
|
|
|
|
SELECT title FROM documents AS d
|
|
WHERE EXISTS (SELECT 1 FROM revisions r WHERE r.doc_id = d.id)
|
|
```
|
|
</CodeGroup>
|
|
|
|
Use `EXISTS` to test whether a matching row exists and `IN` to test membership
|
|
in a set of values. The optimizer may rewrite either into a join; inspect
|
|
`EXPLAIN` before choosing one for performance reasons.
|
|
|
|
`NOT IN` and `NOT EXISTS` differ on nulls: `NOT IN` against a set containing a
|
|
null yields no rows, because the comparison is unknown rather than false. Prefer
|
|
`NOT EXISTS` unless you have ruled nulls out.
|
|
|
|
## Correlated subqueries {#correlated}
|
|
|
|
A subquery referencing a column from the enclosing query, such as `d.id` above,
|
|
is correlated, and is conceptually evaluated per outer row. The planner usually
|
|
rewrites it into a join.
|
|
|
|
<Note>
|
|
Check with [`EXPLAIN`](/sql/dql/explain) when a correlated subquery is slow. A plan
|
|
showing a join has been optimized; one showing a repeated scan has not, and
|
|
rewriting it as an explicit [join](/sql/dql/join) is the fix.
|
|
</Note>
|
|
|
|
## CTEs as an alternative {#ctes}
|
|
|
|
A [CTE](/sql/dql/select#ctes) is a named subquery, and is usually more readable when
|
|
the same subquery appears twice or when nesting gets deep.
|
|
|
|
<CodeGroup>
|
|
```sql SQL icon="database"
|
|
WITH active AS (SELECT id FROM categories WHERE active)
|
|
SELECT title FROM documents WHERE category_id IN (SELECT id FROM active)
|
|
```
|
|
</CodeGroup>
|