--- title: "list_product" slug: "dev-database-reference-sql-functions-lists-list-product" updated: 2026-10-30T18:19:06Z published: 2026-10-30T18:19:06Z canonical: "docs.vastdata.com/dev-database-reference-sql-functions-lists-list-product" --- > ## 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_product *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 product of the elements of a list, one value per row, as a `DOUBLE`. NULL elements are skipped. It's the same as `list_aggregate(l, 'product')`. ## Syntax ``` list_product(l) ``` | Argument | Type | Description | | --- | --- | --- | | `l` | a list of numbers | The list to multiply out. | **Returns:** `DOUBLE`, for lists of integers and decimals 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_product`. 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 and measurements. Row 3 has empty lists, row 4 has no values, and row 5 has measurements close to the largest `DOUBLE`: ``` 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_product"' 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[])") run(f"INSERT INTO {TABLE} VALUES " "(1, [1, 2, 3], [0.5, 2.5, -1.0]), " "(2, [3, NULL, 3], [2.0, NULL]), " "(3, [], []), " "(4, NULL, NULL), " "(5, [-5, 0, -5, 10], [1e308, 1e308, -1e-308])") ``` ``` [] [] [(5,)] ``` ## What it does `list_product(l)` multiplies together the elements of `l` that aren't NULL. `list_product([2, 3])` returns `6.0`, and `list_product([NULL, 2])` returns `2.0`. - **The result is always `DOUBLE`.** A list of integers returns `DOUBLE` too, so a large product loses precision instead of overflowing: `list_product([9223372036854775807, 2])` returns `1.8446744073709552e+19`. - **Too large returns `inf`.** `list_product([1e200, 1e200])` returns `inf`, not an error. - **A zero makes the product 0, and a `NaN` makes it `nan`.** ## NULLs and edge cases | Input | Result | | --- | --- | | `list_product(NULL)` | `NULL` | | `list_product(NULL::BIGINT[])` | `NULL` | | `list_product([]::BIGINT[])` | `NULL`, not `1` | | `list_product([NULL, 2])` | `2.0` | | `list_product([2, 3, 0])` | `0.0` | | `list_product([-2, 3])` | `-6.0` | | `list_product([1.5, 2.0])` | `3.0` | | `list_product([9223372036854775807, 2])` | `1.8446744073709552e+19` | | `list_product([1e200, 1e200])` | `inf` | | `list_product(['NaN'::DOUBLE, 1.0])` | `nan` | | `list_product(['a'])` | Error: `Binder Error: No matching aggregate function` | | 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-product#set-up-the-examples): ``` run("SELECT list_product(NULL), list_product(NULL::BIGINT[]), list_product([]::BIGINT[]), list_product([NULL, 2])") run("SELECT list_product([2, 3, 0]), list_product([-2, 3]), list_product([1.5, 2.0]), " "list_product([9223372036854775807, 2]), list_product([1e200, 1e200]), list_product(['NaN'::DOUBLE, 1.0])") run("SELECT list_product(['a'])") run(f"SELECT list_product(123) FROM {TABLE} LIMIT 1") ``` ``` [(None, None, None, 2.0)] [(0.0, -6.0, 3.0, 1.8446744073709552e+19, inf, nan)] InternalError: Binder Error: No matching aggregate function 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 product of each row's numbers and measurements. Row 5's numbers include a 0, and its measurements multiply out to more than the largest `DOUBLE`: ``` run(f"SELECT id, list_product(nums), list_product(vals) FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` [(1, 6.0, -1.25), (2, 9.0, 2.0), (3, None, None), (4, None, None), (5, 0.0, -inf)] ``` The result type, for an integer and a `DOUBLE` list: ``` run("SELECT typeof(list_product([1, 2])), typeof(list_product([1.5::DOUBLE]))") ``` ``` [('DOUBLE', 'DOUBLE')] ``` The rows whose product isn't NULL: ``` run(f"SELECT id FROM {TABLE} WHERE list_product(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_product()` always runs in the Query Engine. It multiplies 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 product 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 product 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_product(nums) IS NOT NULL") ``` ``` ┌───────────────────────────┐ │ PROJECTION │ │ ──────────────────── │ │ #1 │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ FILTER │ │ ──────────────────── │ │ (list_aggr(CAST(nums AS │ │ DOUBLE[]), 'product') 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_product()` 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 product 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 - **Numbers only.** A list of text fails with `No matching aggregate function`. A value that isn't a list fails with an error that names `list_aggr`, the function `list_product` is built on. - **Not exact for large integers.** The result is a `DOUBLE`, which holds about 15 to 17 significant digits. - **An empty list returns NULL.** Use `coalesce(list_product(l), 1)` where you need `1`. - **`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_product(l)` | product of the elements, as `DOUBLE` | `90.0` | | [list_aggregate](/develop/docs/dev-database-reference-sql-functions-lists-list-aggregate)`(l, 'product')` | the same, by name | `90.0` | | [list_sum](/develop/docs/dev-database-reference-sql-functions-lists-list-sum)`(l)` | sum of the elements | `17` | | [list_avg](/develop/docs/dev-database-reference-sql-functions-lists-list-avg)`(l)` | mean of the elements | `4.25` | | [product](/develop/docs/dev-database-reference-sql-functions-aggregate-product) | product over the rows of a table | | ``` run("SELECT list_product(l), list_aggregate(l, 'product'), list_sum(l), list_avg(l) FROM (SELECT [3, 1, NULL, 3, 10] AS l)") ``` ``` [(90.0, 90.0, Decimal('17'), 4.25)] ``` 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. - [product](/develop/docs/dev-database-reference-sql-functions-aggregate-product): the aggregate over rows. - [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.