--- title: "list_var_samp" slug: "dev-database-reference-sql-functions-lists-list-var-samp" updated: 2026-10-30T18:19:06Z published: 2026-10-30T18:19:06Z canonical: "docs.vastdata.com/dev-database-reference-sql-functions-lists-list-var-samp" --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.vastdata.com/llms.txt > Use this file to discover all available pages before exploring further. # list_var_samp *Applies to VAST Cluster 5.5.* *[Functions](/develop/docs/dev-database-reference-sql-functions-index) › [List, struct and map functions](/develop/docs/dev-database-reference-sql-functions-lists-and-structs) › Aggregate a list.* Returns the sample variance of the numbers in a list, ignoring NULL elements. For the variance of a whole population, use [list_var_pop](/develop/docs/dev-database-reference-sql-functions-lists-list-var-pop). ## Syntax ``` list_var_samp(l) ``` | Argument | Type | Description | | --- | --- | --- | | `l` | a list of numbers | The values whose variance is computed. | **Returns:** `DOUBLE`, for a list of integers too. ## Set up the examples The examples connect with the ADBC driver, as in [VAST Query Engine (ADBC)](/develop/docs/dev-database-integrations-adbc), and work in a schema called `docs_sql_fn_lists_list_var_samp`. Set `QE_ENDPOINT`, `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY` and `VASTDB_BUCKET` ([SQL reference](/develop/docs/dev-database-reference-sql-index#example-connect-and-use-a-transaction)), and run the blocks in order in one Python session. Below each block is the output you should see. This block connects, defines the `run()` and `plan()` helpers, and creates a table of five rows of lists: numbers, words, measurements, flags and lists of lists. Row 3 has empty lists and row 4 has no values: ``` import os import re import adbc_driver_manager import adbc_driver_manager.dbapi as dbapi import adbc_driver_vastdb BUCKET = os.environ["VASTDB_BUCKET"] SCHEMA = f'"{BUCKET}/docs_sql_fn_lists_list_var_samp"' conn = dbapi.connect( driver=adbc_driver_vastdb.get_driver_path(), db_kwargs={ "vast.db.endpoint": os.environ["QE_ENDPOINT"], "vast.db.access_key": os.environ["AWS_ACCESS_KEY_ID"], "vast.db.secret_key": os.environ["AWS_SECRET_ACCESS_KEY"], }, autocommit=True, ) def server_message(e): """The server's message in a driver error, without the request ID or the echoed statement.""" text = re.sub(r"\[req=0x[0-9a-f]+\]: ", "", str(e)) found = (re.search(r'message: "(.*?)", request_id', text, re.S) or re.search(r"description: (.*)\)", text, re.S)) message = found.group(1) if found else text.strip().splitlines()[-1] message = re.sub(r"^Plan query: '.*?' failed with: ", "", message, flags=re.S) message = re.split(r"\\n|\n", message)[0].replace('\\"', '"') return message.replace(BUCKET, "") def run(sql): """Run one statement. Print the rows it returns, or the error.""" try: with conn.cursor() as cur: cur.execute(sql) rows = cur.fetchall() if cur.description else [] except (adbc_driver_manager.Error, OSError) as e: print(f"{type(e).__name__}: {server_message(e)}") else: print(rows) def plan(sql): """Print the plan without its ~N Rows lines: the table's row count, which can still be 0 just after an insert.""" with conn.cursor() as cur: cur.execute("EXPLAIN " + sql) steps = cur.fetchall()[0][1] print("\n".join(line for line in steps.splitlines() if "Rows" not in line)) TABLE = f"{SCHEMA}.samples" run(f"CREATE SCHEMA IF NOT EXISTS {SCHEMA}") run(f"CREATE TABLE IF NOT EXISTS {TABLE} (id BIGINT, nums BIGINT[], words VARCHAR[], vals DOUBLE[], " "flags BOOLEAN[], nested BIGINT[][])") run(f"INSERT INTO {TABLE} VALUES " "(1, [1, 2, 3], ['a', 'b', 'c'], [0.5, 2.5, -1.0], [true, false, true], [[1, 2], [3]]), " "(2, [3, NULL, 3], ['b', NULL, 'B'], [2.0, NULL], [NULL, true], [[], NULL, [4]]), " "(3, [], [], [], [], []), " "(4, NULL, NULL, NULL, NULL, NULL), " "(5, [-5, 0, -5, 10], ['\u00e9', 'Zo\u00eb', '\U0001F1EB\U0001F1F7', ''], [1e308, 1e308, -1e-308], " "[false, false], [[5, NULL], [], [6, 7, 8]])") ``` ``` [] [] [(5,)] ``` ## What it does `list_var_samp(l)` computes the sample variance of the non-NULL elements of `l`: the sum of the squared differences from their mean, divided by one less than the number of values. It's the square of [list_stddev_samp](/develop/docs/dev-database-reference-sql-functions-lists-list-stddev-samp). Use it when the list holds a sample of a larger set of values. - `list_var_samp([1.0, 2.0, 3.0])` is `1.0`, and `list_var_samp([1.0, 2.0, 3.0, 10.0])` is `16.666666666666668`. - Equal values give `0.0`: `list_var_samp([5, 5, 5, 5])`. - It needs at least two values: a list of one value returns NULL. So do an empty list, a list of only NULLs and a NULL list. - `NaN`, infinity, or values near the `DOUBLE` limit such as `1e308`, fail the query with `VARSAMP is out of range!`. ## NULLs and edge cases | Input | Result | | --- | --- | | `NULL` | `NULL` | | `[]` | `NULL` | | `[NULL, NULL]` | `NULL` | | `[1.0]` | `NULL` | | `[1.0, 2.0]` | `0.5` | | `[5, 5, 5, 5]` | `0.0` | | A list holding `NaN` or `inf`, or `[1e308, -1e308, 1e308]` | Error: `VARSAMP is out of range!` | | A number, string, `BLOB`, date or boolean | Error: `No function matches the given name and argument types`, for example `'list_aggr(INTEGER_LITERAL, STRING_LITERAL)'` | The same cases, as the cluster returns them. They use the helpers from [Set up the examples](/develop/docs/dev-database-reference-sql-functions-lists-list-var-samp#set-up-the-examples): ``` run("SELECT list_var_samp(NULL::BIGINT[]), list_var_samp([]::DOUBLE[]), " "list_var_samp([NULL, NULL]::DOUBLE[]), list_var_samp([1.0])") run("SELECT list_var_samp([1.0, 2.0]), list_var_samp([5, 5, 5, 5])") run("SELECT list_var_samp(['NaN'::DOUBLE, 1.0, 2.0])") run("SELECT list_var_samp([1e308, -1e308, 1e308])") run("SELECT list_var_samp(123)") ``` ``` [(None, None, None, None)] [(0.5, 0.0)] OSError: VARSAMP is out of range! OSError: VARSAMP is out of range! InternalError: Binder Error: No function matches the given name and argument types 'list_aggr(INTEGER_LITERAL, STRING_LITERAL)'. You might need to add explicit type casts. ``` ## Examples The sample variance of each row's numbers. Row 2's NULL is ignored, which leaves two equal values and a result of `0.0`; rows 3 and 4 return NULL: ``` run(f"SELECT id, nums, list_var_samp(nums) FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` [(1, [1, 2, 3], 1.0), (2, [3, None, 3], 0.0), (3, [], None), (4, None, None), (5, [-5, 0, -5, 10], 50.0)] ``` The rows whose numbers vary by more than a threshold: ``` run(f"SELECT id, nums FROM {TABLE} WHERE list_var_samp(nums) > 0.5 ORDER BY id LIMIT 10") ``` ``` [(1, [1, 2, 3]), (5, [-5, 0, -5, 10])] ``` ## How it runs in VAST The Query Engine runs on the cluster's CNodes, and a query on a table starts with a scan in VAST DataBase (`VAST_SCAN`). The scan reads a list column whole, and `list_var_samp()` always runs in the Query Engine: - **In the `SELECT` list,** a projection step computes `list_var_samp()` for each row the scan returns. - **In `WHERE`,** the scan sends the list for every row, and a `FILTER` step computes `list_var_samp()` and keeps the rows that match. No rows are skipped in storage. The plan of a `WHERE` condition on `list_var_samp()` shows the `FILTER` step above the scan: ``` plan(f"SELECT id FROM {TABLE} WHERE list_var_samp(nums) IS NOT NULL") ``` ``` ┌───────────────────────────┐ │ PROJECTION │ │ ──────────────────── │ │ #1 │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ FILTER │ │ ──────────────────── │ │ (list_aggr(CAST(nums AS │ │ DOUBLE[]), 'var_samp') IS│ │ NOT NULL) │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ VAST_SCAN │ │ ──────────────────── │ │ Function: VAST_SCAN │ │ │ │ Projections: │ │ nums │ │ id │ │ │ └───────────────────────────┘ ``` ## Make it faster - **Add a condition on a plain column.** A comparison of a column with a constant, such as `id > 1`, is evaluated in VAST DataBase, so `list_var_samp()` runs only on the rows that pass it. The plan for `id > 1` alone has no `FILTER` step: ``` plan(f"SELECT id FROM {TABLE} WHERE id > 1") ``` ``` ┌───────────────────────────┐ │ VAST_SCAN │ │ ──────────────────── │ │ Function: VAST_SCAN │ │ Projections: id │ │ │ └───────────────────────────┘ ``` - **Store the result if you filter on it often.** Compute it when you write the rows and keep it in its own column: `variance > 0.5` is pushed down, `list_var_samp(nums) > 0.5` isn't. ## Limitations and errors - **One out-of-range list fails the whole query.** Row 5's measurements hold `1e308`, so `list_var_samp(vals)` over the table fails with `VARSAMP is out of range!` and returns no rows. Keep `NaN`, infinities and values near the `DOUBLE` limit out of the lists you pass. - **Lists only.** Any argument that isn't a list fails with `No function matches the given name and argument types`; the error names `list_aggr`, the function `list_var_samp` calls. - **`ORDER BY` needs a `LIMIT`.** Without one, the query fails with `The operator 'ORDER_BY' type=1 is currently not supported for this usage`. ``` run(f"SELECT id, list_var_samp(vals) FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` OSError: VARSAMP is out of range! ``` ## Similar functions | Function | What it returns | Result for `[1.0, 2.0, 3.0, 10.0]` | | --- | --- | --- | | `list_var_samp` | sample variance (divides by n - 1) | `16.666666666666668` | | [list_var_pop](/develop/docs/dev-database-reference-sql-functions-lists-list-var-pop) | population variance (divides by n) | `12.5` | | [list_stddev_samp](/develop/docs/dev-database-reference-sql-functions-lists-list-stddev-samp) | sample standard deviation: the square root of `list_var_samp` | `4.08248290463863` | | [list_stddev_pop](/develop/docs/dev-database-reference-sql-functions-lists-list-stddev-pop) | population standard deviation | `3.5355339059327378` | ``` run("SELECT list_var_samp(l), list_var_pop(l), list_stddev_samp(l), list_stddev_pop(l) " "FROM (SELECT [1.0, 2.0, 3.0, 10.0]::DOUBLE[] AS l)") ``` ``` [(16.666666666666668, 12.5, 4.08248290463863, 3.5355339059327378)] ``` Clean up: ``` run(f"DROP TABLE IF EXISTS {TABLE}") run(f"DROP SCHEMA IF EXISTS {SCHEMA}") conn.close() ``` ``` [] [] ``` ## See also - [List, struct and map functions](/develop/docs/dev-database-reference-sql-functions-lists-and-structs): all the list functions. - [list_avg](/develop/docs/dev-database-reference-sql-functions-lists-list-avg): the mean of a list. - [Where filters run](/develop/docs/dev-database-reference-sql-select#where-filters-run) and [pushdowns](/develop/docs/dev-database-reference-pushdowns). - [EXPLAIN](/develop/docs/dev-database-reference-sql-explain): how to read a plan.