--- title: "list_median" slug: "dev-database-reference-sql-functions-lists-list-median" updated: 2026-10-30T18:19:11Z published: 2026-10-30T18:19:11Z canonical: "docs.vastdata.com/dev-database-reference-sql-functions-lists-list-median" --- > ## 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_median *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 middle value of the elements of a list, one value per row. NULL elements are skipped. It's the same as `list_aggregate(l, 'median')`, and it works although the `median` aggregate over rows isn't available. ## Syntax ``` list_median(l) ``` | Argument | Type | Description | | --- | --- | --- | | `l` | a list of numbers, text or dates | The list whose middle value you want. | **Returns:** `DOUBLE` for a list of numbers; the element type for a list of text; `TIMESTAMP` for a list of dates. ## 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_median`. 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 of numbers, measurements and words. 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_median"' 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[], vals DOUBLE[], words VARCHAR[])") run(f"INSERT INTO {TABLE} VALUES " "(1, [1, 2, 3], [0.5, 2.5, -1.0], ['a', 'b', 'c']), " "(2, [3, NULL, 3], [2.0, NULL], ['b', NULL, 'B']), " "(3, [], [], []), " "(4, NULL, NULL, NULL), " "(5, [-5, 0, -5, 10], [1e308, 1e308, -1e-308], ['\u00e9', 'Zo\u00eb', '\U0001F1EB\U0001F1F7', ''])") ``` ``` [] [] [(5,)] ``` ## What it does `list_median(l)` sorts the elements of `l` that aren't NULL and returns the one in the middle. `list_median([1, 3, 2])` returns `2.0`. - **An even count of numbers gives the mean of the two middle values.** `list_median([1, 2, 3, 4])` returns `2.5`. - **An even count of text values gives the lower of the two.** Text can't be averaged, so `list_median(['a', 'b'])` returns `'a'`, and `list_median(['a', 'b', 'c', 'd'])` returns `'b'`. In the example table, row 2's words `'b'` and `'B'` have the median `'B'`. - **Dates give a `TIMESTAMP`.** The median of `DATE '2026-10-16'` and `DATE '2026-10-18'` is `2026-10-17 00:00:00`. - **The result for numbers is `DOUBLE`,** for integer lists too. ## NULLs and edge cases | Input | Result | | --- | --- | | `list_median(NULL)` | `NULL` | | `list_median(NULL::BIGINT[])` | `NULL` | | `list_median([]::BIGINT[])` | `NULL` | | `list_median([NULL, 1, NULL])` | `1.0` | | `list_median([1, 2])` | `1.5` | | `list_median(['a', 'b'])` | `'a'` | | `list_median([DATE '2026-10-16', DATE '2026-10-18'])` | `2026-10-17 00:00:00` (`TIMESTAMP`) | | `list_median([9223372036854775807, 9223372036854775806])` | `9.223372036854776e+18` | | `list_median(['NaN'::DOUBLE, 1.0, 2.0])` | `1.0` | | A number, string, date or other non-list | Error: `Binder 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 table and helpers from [Set up the examples](/develop/docs/dev-database-reference-sql-functions-lists-list-median#set-up-the-examples): ``` run("SELECT list_median(NULL), list_median(NULL::BIGINT[]), list_median([]::BIGINT[]), " "list_median([NULL, 1, NULL]), list_median([1, 2]), list_median(['a', 'b'])") run("SELECT list_median([DATE '2026-10-16', DATE '2026-10-18']), " "list_median([9223372036854775807, 9223372036854775806]), list_median(['NaN'::DOUBLE, 1.0, 2.0])") run(f"SELECT list_median(123) FROM {TABLE} LIMIT 1") ``` ``` [(None, None, None, 1.0, 1.5, 'a')] [(datetime.datetime(2026, 10, 17, 0, 0), 9.223372036854776e+18, 1.0)] 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 middle value of each row's numbers, measurements and words: ``` run(f"SELECT id, list_median(nums), list_median(vals), list_median(words) FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` [(1, 2.0, 0.5, 'b'), (2, 3.0, 2.0, 'B'), (3, None, None, None), (4, None, None, None), (5, -2.5, 1e+308, 'Zoë')] ``` Odd and even counts, for numbers and text: ``` run("SELECT list_median([1, 3, 2]), list_median([1, 2, 3, 4]), list_median(['a', 'b', 'c', 'd'])") ``` ``` [(2.0, 2.5, 'b')] ``` The rows that have a median: ``` run(f"SELECT id FROM {TABLE} WHERE list_median(nums) IS NOT NULL ORDER BY id LIMIT 10") ``` ``` [(1,), (2,), (5,)] ``` ## 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_median()` always runs in the Query Engine. It works within each row's list, so it's a scalar function: it returns one value per row and needs no `GROUP BY`. - **In the `SELECT` list,** a projection step computes the median of each row's list after the scan. The plan has no `FILTER` step. - **In `WHERE`,** the scan sends the list for every row, and a `FILTER` step computes the median and keeps the rows that match. No rows are skipped in storage. The plan of the `WHERE` example shows the `FILTER` step above the scan: ``` plan(f"SELECT id FROM {TABLE} WHERE list_median(nums) IS NOT NULL") ``` ``` ┌───────────────────────────┐ │ PROJECTION │ │ ──────────────────── │ │ #1 │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ FILTER │ │ ──────────────────── │ │ (list_aggr(nums, 'median')│ │ 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_median()` 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 median if you filter on it often.** Compute it when you write the rows and keep it in its own column, where a comparison with a constant is pushed down. ## Limitations and errors - **Lists only.** A value that isn't a list fails with an error that names `list_aggr`, the function `list_median` is built on. - **No median over rows.** The `median` aggregate over a table's rows isn't [available](/develop/docs/dev-database-reference-sql-functions-aggregate). `list_median` works on one row's list. - **`ORDER BY` needs a `LIMIT`.** Without one, the query fails with `The operator 'ORDER_BY' type=1 is currently not supported for this usage`. ## Similar functions | Function | What it does | Result for `[3, 1, NULL, 3, 10]` | | --- | --- | --- | | `list_median(l)` | middle value | `3.0` | | [list_aggregate](/develop/docs/dev-database-reference-sql-functions-lists-list-aggregate)`(l, 'median')` | the same, by name | `3.0` | | [list_aggregate](/develop/docs/dev-database-reference-sql-functions-lists-list-aggregate)`(l, 'quantile_cont', 0.5)` | the 0.5 quantile, which is the median; other fractions give other quantiles | `3.0` | | [list_avg](/develop/docs/dev-database-reference-sql-functions-lists-list-avg)`(l)` | mean | `4.25` | | [list_mode](/develop/docs/dev-database-reference-sql-functions-lists-list-mode)`(l)` | most frequent value | `3` | ``` run("SELECT list_median(l), list_aggregate(l, 'median'), list_aggregate(l, 'quantile_cont', 0.5), list_avg(l), list_mode(l) " "FROM (SELECT [3, 1, NULL, 3, 10] AS l)") ``` ``` [(3.0, 3.0, 3.0, 4.25, 3)] ``` 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#aggregate-a-list): all the list aggregates. - [Aggregate functions](/develop/docs/dev-database-reference-sql-functions-aggregate): aggregates over the rows of a table. - [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.