--- title: "Random sampling" sidebarTitle: "Sampling" description: "TABLESAMPLE: draw a random subset of a table, by rows or by fragments." icon: dice keywords: ["tablesample", "sampling", "bernoulli", "system", "repeatable", "random"] --- Enterprise [SQL runs in LanceDB Enterprise.](/sql) Use `TABLESAMPLE` to explore a subset of a table or estimate aggregate statistics. The sampling method determines how much data is read and whether the table's physical layout influences the sample. ```sql SELECT * FROM documents TABLESAMPLE (10) -- 10 percent SELECT * FROM documents TABLESAMPLE (500 ROWS) -- 500 rows ``` A bare number is a **percentage**. Add `ROWS` for a count instead. ## Rows or fragments {#methods} The standard calls these two methods of one clause. They are different operations, and the difference matters on Lance: ```sql SELECT * FROM documents TABLESAMPLE BERNOULLI (10) SELECT * FROM documents TABLESAMPLE SYSTEM (10) ``` | Method | Aliases | What it picks | | --- | --- | --- | | `BERNOULLI` | `ROW` | rows, each considered independently | | `SYSTEM` | `BLOCK` | **Lance fragments**, and takes whatever rows they hold | `BERNOULLI` gives a genuinely uniform sample and reads across the whole table to get it. `SYSTEM` reads far less (it skips entire fragments), but the sample is only as uniform as the data's layout. If rows were written in an order that correlates with what you are measuring, a fragment sample inherits that correlation. Use `SYSTEM` for a quick look at the data and `BERNOULLI` when you need independent row sampling. Omitting the method gives `BERNOULLI`. ## Repeatability {#repeatable} Without a seed, every execution resamples: running the same query twice gives different rows. `REPEATABLE` fixes the draw: ```sql SELECT * FROM documents TABLESAMPLE (10) REPEATABLE (42) ``` Use the same seed and table snapshot to reproduce a sampling run. For a fixed evaluation set, save the selected row IDs or materialize the sample and retain its version. A seed alone does not preserve membership after source changes or changes to the physical layout. ## Where the clause can go {#placement} It attaches to a table in `FROM`, including inside a subquery, a CTE, or either side of a join: ```sql SELECT * FROM (SELECT * FROM documents TABLESAMPLE (10)) d SELECT * FROM a TABLESAMPLE (5 ROWS) JOIN b ON a.id = b.id SELECT * FROM t a TABLESAMPLE (10) JOIN t b TABLESAMPLE (10) ON a.id = b.id ``` Each side of a join samples independently. Sampling both sides of a join shrinks the *result* far more than either fraction suggests, because a row only survives if both its sides were drawn. ## Unsupported sampling forms {#refused} Sampling is semantics, not a hint. A clause that were read and then not applied would be a wrong answer rather than a missing feature, so anything that cannot be honoured exactly is an error: | | | | --- | --- | | `TABLESAMPLE (101)` | a percentage outside `0..=100` is refused, not clamped | | `TABLESAMPLE (1.5 ROWS)` | a row count must be whole | | `TABLESAMPLE (BUCKET 1 OUT OF 4)` | bucket sampling is not supported | | `(SELECT ...) d TABLESAMPLE (10)` | a subquery's result cannot be sampled; sample the table inside it | | the `SAMPLE` spelling | use `TABLESAMPLE` | | the `OFFSET` modifier | not supported | `TABLESAMPLE` is also refused on a WAL-backed table, where the rows a sample would draw from are not all in the fragments yet. ## Sampling outside SQL {#sdk} For a training loop rather than a query, the SDKs read a table in a shuffled order without going through SQL at all. See [Training](/training/data-loading), where a permutation drives the data loader.