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Jack Ye
19f8f396ec
Ten merges and renames, all in one direction: fewer pages, each covering a whole subject. Table absorbs schema evolution and versioning. Vector search absorbs multi-vector. Explain absorbs explain analyze. Reranking was seven pages -- an overview and six rerankers of a few dozen lines each -- and is now one. The vector index page absorbs quantization, which was only ever a parameter of it. Indexing moves to Manage, where the other catalog objects are. The operational half stays in Operate as one Indexing page, absorbing GPU indexing -- which was filed in sophon despite importing lancedb's snippets and being mostly open-source content with one Enterprise-badged section. Performance was a single page aggregating tips for four unrelated operations, which is hard to keep current. Each section now sits with the operation it is about: ingestion tips on Insert, index tips on Indexing, compaction tips on Compaction, query tips on Search. Data Types leaves Concepts. The type reference belongs in the SQL reference, which already described the same types from the query side; Table now carries a short summary that points there. The multimodal material it had absorbed is its own page again, since storing blobs is a task rather than a type definition. Query becomes Semantic Search, Branches becomes Branch, and the Enterprise Security page becomes Compliance. Redirects cover every moved URL, and 30 files were repointed at the merged anchors.
136 lines
3.7 KiB
Plaintext
136 lines
3.7 KiB
Plaintext
---
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title: "SELECT"
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sidebarTitle: "Select"
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description: "Projection, filtering, ordering, and composing queries out of other queries."
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icon: table-columns
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keywords: ["select", "where", "order by", "limit", "cte", "union", "distinct"]
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---
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<Badge color="red">Enterprise</Badge> [SQL runs on a deployment.](/sql)
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```sql
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[WITH cte AS (...)]
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SELECT [ALL | DISTINCT] select_expr [, ...]
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FROM from_item [[JOIN ...] ON ...]
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[WHERE predicate]
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[GROUP BY expr [, ...]] [HAVING predicate]
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[WINDOW name AS (...)]
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[ORDER BY expr [ASC | DESC] [NULLS FIRST | LAST] [, ...]]
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[LIMIT n] [OFFSET n]
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```
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## Projection {#projection}
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<CodeGroup>
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```sql SQL
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SELECT id, title, identifier FROM documents
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```
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```python Python icon="python"
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tbl.search().select(["id", "title", "identifier"]).to_arrow()
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```
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```typescript TypeScript icon="square-js"
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await tbl.query().select(["id", "title", "identifier"]).toArrow();
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```
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</CodeGroup>
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Projection pushes into the scan in all three -- an unselected column is never
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read off storage. On a table of images or video that is the difference between a
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fast query and a slow one, so **prefer naming columns over `SELECT *`**.
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Row metadata is available as [pseudo-columns](/sql/data-types#pseudo-columns)
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(`_rowid`, `_rowaddr`, `_rowoffset`) but only when named, so they stay out of
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`SELECT *`.
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`DISTINCT` deduplicates the projected rows.
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## Filtering {#filtering}
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<CodeGroup>
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```sql SQL
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SELECT * FROM documents
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WHERE identifier > 0 AND identifier < 1000000
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```
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```python Python icon="python"
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tbl.search().where("identifier > 0 AND identifier < 1000000").to_arrow()
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```
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```typescript TypeScript icon="square-js"
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await tbl.query().where("identifier > 0 AND identifier < 1000000").toArrow();
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```
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</CodeGroup>
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The SDK `where` takes the same expression language, so a predicate moves between
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them unchanged. A predicate on an indexed column becomes a `ScalarIndexQuery`
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rather than a scan -- confirm with [`explain_plan`](/search/explain). See
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[Filtering](/search/filtering) for the operators and their pushdown behaviour.
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## Ordering and limiting {#order-limit}
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```sql
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SELECT id, title FROM documents
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ORDER BY created_at DESC NULLS LAST
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LIMIT 100 OFFSET 200
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```
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`ORDER BY` on a large table is a sort over the whole result, so pair it with a
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`LIMIT` unless you genuinely need every row ordered.
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## Set operations {#set-operations}
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`UNION`, `UNION ALL`, `INTERSECT` and `EXCEPT` combine whole queries:
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```sql
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SELECT id FROM documents WHERE category = 'film'
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UNION ALL
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SELECT id FROM archived_documents WHERE category = 'film'
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```
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`UNION` deduplicates and `UNION ALL` does not, which makes `UNION ALL` the
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cheaper one when you already know the inputs are disjoint.
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## Common table expressions {#ctes}
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```sql
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WITH recent AS (
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SELECT * FROM documents WHERE created_at > now() - INTERVAL '7 days'
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)
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SELECT category, count(*) FROM recent GROUP BY category
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```
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A CTE is scoped to the statement. One you want to keep is a
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[view](/management/view); one whose rows you want stored is a
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[materialized view](/management/materialized-view).
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## Subqueries {#subqueries}
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Subqueries are allowed anywhere an expression or a relation is -- in `FROM`, in
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`WHERE` with `IN` or `EXISTS`, and as a scalar in the select list:
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```sql
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SELECT title
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FROM documents
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WHERE category_id IN (SELECT id FROM categories WHERE active)
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```
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## Namespaced tables {#namespaces}
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A table inside a [namespace](/management/namespace) is written as a dotted path:
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```sql
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SELECT * FROM prod.events.clicks
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```
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## Reading the plan {#plans}
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`EXPLAIN` and `EXPLAIN ANALYZE` work as DataFusion defines them, and produce the
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same operators the SDK methods do:
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```sql
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EXPLAIN ANALYZE SELECT * FROM documents WHERE identifier < 1000
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```
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See [Explain](/search/explain) and [Explain Analyze](/search/explain).
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