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Jack Ye
fe651ae003
The function catalogue is now real rather than a pointer. Scalar functions are listed by taxonomy -- math, string, unicode, regex, date/time, array, map, struct, crypto, type -- and the names come from what datafusion-functions 54 actually registers, not from what DataFusion documents on main. Aggregate and window pages gain the same treatment. Two things the audit corrected rather than copied. SHOW TABLES does not work. DataFusion implements it over information_schema, which this session does not enable, so it fails at plan time. It was documented as working here, on the SHOW page and in three Manage tables; all four are fixed, and the SQL overview now lists the absence alongside SHOW COLUMNS. Prepared statements are a Flight SQL protocol feature, not a PREPARE statement. A script carrying PREPARE ... AS SELECT will not run, while the same intent expressed through a client will. The new page says so rather than copying DataFusion's syntax. Every section of the Documentation tab that has a SQL counterpart now links to it -- 27 of 76 non-SQL pages, each pointing at the specific statement rather than at the reference index.
78 lines
2.6 KiB
Plaintext
78 lines
2.6 KiB
Plaintext
---
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title: "Delete rows"
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sidebarTitle: "Delete"
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description: "Remove rows by predicate, and reclaim their space."
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icon: trash
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---
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These examples use the table set up in
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[Ingesting data](/ingestion), and the connection made there.
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import {
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PyDeleteOperation as DeleteOperation,
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PyUpdateOptimizeCleanup as UpdateOptimizeCleanup,
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TsDeleteOperation,
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TsUpdateOptimizeCleanup,
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RsDeleteOperation,
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RsUpdateOptimizeCleanup,
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} from '/snippets/tables.mdx';
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<Note>
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In SQL this is [`DELETE`](/sql/dml#delete).
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</Note>
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## Delete rows {#delete-rows}
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Delete operations **soft delete** rows that match a given condition.
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The underlying data is not immediately removed, but is marked
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for deletion (in the [deletion files](https://lance.org/format/table/#deletion-files) at the Lance format level) and excluded from query results.
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<CodeGroup>
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<CodeBlock filename="Python" language="Python" icon="python">
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{DeleteOperation}
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</CodeBlock>
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<CodeBlock filename="TypeScript" language="TypeScript" icon="square-js">
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{TsDeleteOperation}
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</CodeBlock>
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<CodeBlock filename="Rust" language="Rust" icon="rust">
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{RsDeleteOperation}
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</CodeBlock>
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</CodeGroup>
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Expected table contents:
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| id | name | login_count |
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| --- | --- | --- |
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| 1 | Alice | 10 |
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| 2 | Bob | 20 |
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<Warning>
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**Deleting rows removes them from the index**
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When rows are deleted, those rows are also excluded from the index segments, so indexed queries will not return them either. If ALL the rows are deleted (i.e., the table is emptied), ensure that you recreate the index after ingesting new data.
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</Warning>
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To permanently remove deleted rows, you can optimize the table, which will run compaction and cleans up the soft-deleted rows, which frees up storage space.
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- In LanceDB OSS, compaction and cleanup are manual. Run `table.optimize()` regularly to free up disk space.
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- In LanceDB Enterprise, files aren't cleaned up by default. You can configure automatic compaction and cleanup behavior at cluster setup time to suit your organization's retention policy.
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By default, table cleanup removes data up to 7 days ago. If you need to reclaim space from deleted rows more aggressively, manually call `table.optimize()` use a shorter retention window as follows:
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<CodeGroup>
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<CodeBlock filename="Python" language="Python" icon="python">
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{UpdateOptimizeCleanup}
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</CodeBlock>
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<CodeBlock filename="TypeScript" language="TypeScript" icon="square-js">
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{TsUpdateOptimizeCleanup}
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</CodeBlock>
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<CodeBlock filename="Rust" language="Rust" icon="rust">
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{RsUpdateOptimizeCleanup}
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</CodeBlock>
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</CodeGroup>
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