--- title: "json_contains" slug: "dev-database-reference-sql-functions-json-json-contains" updated: 2026-10-30T18:19:06Z published: 2026-10-30T18:19:06Z canonical: "docs.vastdata.com/dev-database-reference-sql-functions-json-json-contains" --- > ## 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. # json_contains *Applies to VAST Cluster 5.5.* *[Functions](/develop/docs/dev-database-reference-sql-functions-index) › [Parsing and JSON functions](/develop/docs/dev-database-reference-sql-functions-json) › Check and inspect.* Returns true if a JSON document contains another JSON value anywhere inside it: a scalar value, an object's key/value pairs, or an array's elements. ## Syntax ``` json_contains(haystack, needle) ``` | Argument | Type | Description | | --- | --- | --- | | `haystack` | `VARCHAR` or `JSON` | The JSON document to search. | | `needle` | `VARCHAR` or `JSON` | The JSON value to look for, written as JSON text: `'"ada"'` for a string, `'3'` for a number, `'{"city": "Oslo"}'` for an object. | **Returns:** `BOOLEAN`. ## 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_json_json_contains`. 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 four events with a JSON payload stored as `VARCHAR`. Row 3 holds an array, 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_json_json_contains"' 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}.events" run(f"CREATE SCHEMA IF NOT EXISTS {SCHEMA}") run(f"CREATE TABLE IF NOT EXISTS {TABLE} (id BIGINT, payload VARCHAR, user_name VARCHAR)") run(f"INSERT INTO {TABLE} VALUES " "(1, '{\"user\": \"ada\", \"n\": 3, \"tags\": [\"a\", \"b\"], \"geo\": {\"city\": \"Oslo\", \"lat\": 59.9}}', 'ada'), " "(2, '{\"user\": \"alan\", \"n\": 20, \"tags\": [], \"geo\": null}', 'alan'), " "(3, '[10, 20, [30, 40]]', NULL), " "(4, NULL, NULL)") ``` ``` [] [] [(4,)] ``` ## What it does `json_contains` parses both arguments as JSON and looks for the needle at any depth of the haystack: | Needle | Matches when the haystack has… | Example on `{"user": "ada", "n": 3, "tags": ["a", "b", "c"], "geo": {"city": "Oslo", "lat": 59.9}, "z": null}` | Result | | --- | --- | --- | --- | | A string, number, boolean or `null` | an equal value, at any depth | `'"Oslo"'`, `'3'`, `'null'` | `true` | | | a value of another JSON type or spelling | `'"3"'`, `'3.0'` | `false` | | | part of a string only | `'"ad"'` | `false` | | An object | an object, at any depth, with all of the needle's key/value pairs, in any order | `'{"city": "Oslo"}'`, `'{"lat": 59.9, "city": "Oslo"}'`, `'{"geo": {"city": "Oslo"}}'` | `true` | | | the same keys, with a value that differs in case | `'{"city": "oslo"}'` | `false` | | An array | an array with all of the needle's elements, in any order | `'["b", "a"]'` | `true` | | `{}` or `[]` | (the sample document has objects and arrays) | `'{}'`, `'[]'` | `true` | String comparison is exact and case-sensitive. A number matches only a number written the same way: `3` doesn't match `3.0`. ## NULLs and edge cases | Input | Result | | --- | --- | | `NULL` haystack or needle | `NULL` | | `json_contains('[1, 2]', '2')` | `true` | | `json_contains('[[1, 2]]', '[1]')` | `true`: the needle's elements are found in the inner array | | `json_contains('1', '1')` (a scalar document) | `true` | | A needle that isn't JSON, such as `'ada'` without quotes | Error: `Malformed JSON at byte 0 of input: unexpected character. Input: ada` | | A haystack that isn't JSON | Error: `Malformed JSON at byte 0 of input: invalid literal. Input: not json` | | A number as the haystack | Error: `No function matches the given name and argument types 'json_contains(INTEGER_LITERAL, STRING_LITERAL)'` | The cases of both tables, as the cluster returns them. Each line shows the needle and the result. They use the helpers from [Set up the examples](/develop/docs/dev-database-reference-sql-functions-json-json-contains#set-up-the-examples): ``` DOC = '{"user": "ada", "n": 3, "tags": ["a", "b", "c"], "geo": {"city": "Oslo", "lat": 59.9}, "z": null}' for needle in ['"Oslo"', '3', 'null', '"3"', '3.0', '"ad"', '{"city": "Oslo"}', '{"lat": 59.9, "city": "Oslo"}', '{"geo": {"city": "Oslo"}}', '{"city": "oslo"}', '["b", "a"]', '{}', '[]']: run(f"SELECT '{needle}', json_contains('{DOC}', '{needle}')") run("SELECT json_contains(NULL, '1'), json_contains('[1, 2]', NULL), json_contains('[1, 2]', '2'), " "json_contains('[[1, 2]]', '[1]'), json_contains('1', '1')") run(f"SELECT json_contains('{DOC}', 'ada')") run("SELECT json_contains('not json', '1')") run("SELECT json_contains(123, '1')") ``` ``` [('"Oslo"', True)] [('3', True)] [('null', True)] [('"3"', False)] [('3.0', False)] [('"ad"', False)] [('{"city": "Oslo"}', True)] [('{"lat": 59.9, "city": "Oslo"}', True)] [('{"geo": {"city": "Oslo"}}', True)] [('{"city": "oslo"}', False)] [('["b", "a"]', True)] [('{}', True)] [('[]', True)] [(None, None, True, True, True)] OSError: Malformed JSON at byte 0 of input: unexpected character. Input: ada OSError: Malformed JSON at byte 0 of input: invalid literal. Input: not json InternalError: Binder Error: No function matches the given name and argument types 'json_contains(INTEGER_LITERAL, STRING_LITERAL)'. You might need to add explicit type casts. ``` ## Examples Which events mention the user `ada`, a city of Oslo, or the number 20. Row 2 has `"n": 20`, and row 3 is an array with `20` as one of its elements: ``` run("SELECT id, json_contains(payload, '\"ada\"'), json_contains(payload, '{\"city\": \"Oslo\"}'), " f"json_contains(payload, '20') FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` [(1, True, True, False), (2, False, False, True), (3, False, False, True), (4, None, None, None)] ``` Keep the events that have an object with `"city": "Oslo"`: ``` run("SELECT id FROM " + TABLE + " WHERE json_contains(payload, '{\"city\": \"Oslo\"}') ORDER BY id LIMIT 10") ``` ``` [(1,)] ``` ## 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`). VAST DataBase stores the payload as text and can't look inside it, so `json_contains` always runs in the Query Engine and parses the document of every row it gets: - **In the `SELECT` list,** the scan reads the column and the Query Engine computes `json_contains` for each row it returns. - **In `WHERE`,** the scan sends the column for every row, and a `FILTER` step in the Query Engine parses each document and keeps the rows that match. The plan of a `WHERE` condition shows the `FILTER` step above the scan: ``` plan(f"SELECT id FROM {TABLE} WHERE json_contains(payload, '\"ada\"')") ``` ``` ┌───────────────────────────┐ │ PROJECTION │ │ ──────────────────── │ │ #1 │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ FILTER │ │ ──────────────────── │ │ json_contains(payload, ' │ │ "ada"') │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ VAST_SCAN │ │ ──────────────────── │ │ Function: VAST_SCAN │ │ │ │ Projections: │ │ payload │ │ id │ │ │ └───────────────────────────┘ ``` ## Make it faster - **Keep the values you search for in their own columns.** A comparison of a plain column with a constant is pushed down to VAST DataBase, so rows that don't match never leave storage. The plan for `user_name = 'ada'` has no `FILTER` step: ``` plan(f"SELECT id FROM {TABLE} WHERE user_name = 'ada'") ``` ``` ┌───────────────────────────┐ │ VAST_SCAN │ │ ──────────────────── │ │ Function: VAST_SCAN │ │ Projections: id │ │ │ └───────────────────────────┘ ``` - **Compare the whole document when you can.** `payload = '[]'` is pushed down too; `payload LIKE '%ada%'` isn't, and runs in a `FILTER` step like `json_contains`. - **Write each document once, valid.** Every row is parsed on every query; see [Make JSON queries faster](/develop/docs/dev-database-reference-sql-functions-json). ## Limitations and errors - **The needle is JSON, not a plain value.** Write a string with its double quotes, `'"ada"'`. Without them the needle isn't valid JSON and the query fails with `Malformed JSON at byte 0 of input: unexpected character.` [to_json](/develop/docs/dev-database-reference-sql-functions-json-to-json) turns a SQL value into JSON text: `to_json('ada')` returns `"ada"`. - **One invalid document fails the query.** If any row the function reads isn't valid JSON, the query stops with `Malformed JSON at byte ...`. Keep such rows out with a pushed-down condition: see [invalid JSON in a column](/develop/docs/dev-database-reference-sql-functions-json). - **Text or JSON arguments.** A number fails with `No function matches the given name and argument types`; cast it, or write it as text. - **It doesn't say where the value is.** To test one path, use [json_extract_string](/develop/docs/dev-database-reference-sql-functions-json-json-extract-string) or [json_exists](/develop/docs/dev-database-reference-sql-functions-json-json-exists). ## Similar functions | Function | Tests | Example | | --- | --- | --- | | [json_exists](/develop/docs/dev-database-reference-sql-functions-json-json-exists) | a path exists, whatever its value | `json_exists(payload, '$.geo')` | | [json_keys](/develop/docs/dev-database-reference-sql-functions-json-json-keys) with [list_contains](/develop/docs/dev-database-reference-sql-functions-lists-list-contains) | a top-level key exists | `list_contains(json_keys(payload), 'geo')` | | [json_extract_string](/develop/docs/dev-database-reference-sql-functions-json-json-extract-string) | the value at one path | `json_extract_string(payload, '$.user') = 'ada'` | | `LIKE` | the text of the document, keys and partial words included | `payload LIKE '%ada%'` | The four tests and `json_contains` on each row: ``` run("SELECT id, json_contains(payload, '\"ada\"'), json_exists(payload, '$.geo'), " "list_contains(json_keys(payload), 'geo'), json_extract_string(payload, '$.user') = 'ada', " f"payload LIKE '%ada%' FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` [(1, True, True, True, True, True), (2, False, True, True, False, False), (3, False, False, False, None, False), (4, None, None, None, None, None)] ``` Clean up: ``` run(f"DROP TABLE IF EXISTS {TABLE}") run(f"DROP SCHEMA IF EXISTS {SCHEMA}") conn.close() ``` ``` [] [] ``` ## See also - [Parsing and JSON functions](/develop/docs/dev-database-reference-sql-functions-json): all the JSON functions, JSON paths and invalid JSON. - [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.