--- title: "json_exists" slug: "dev-database-reference-sql-functions-json-json-exists" updated: 2026-10-30T18:19:06Z published: 2026-10-30T18:19:06Z canonical: "docs.vastdata.com/dev-database-reference-sql-functions-json-json-exists" --- > ## 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_exists *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 path exists in a JSON document and false if it doesn't. A key whose value is JSON `null` exists. ## Syntax ``` json_exists(json, path) json_exists(json, paths) ``` | Argument | Type | Description | | --- | --- | --- | | `json` | `VARCHAR` or `JSON` | The JSON document. | | `path` | `VARCHAR` | A [JSON path](/develop/docs/dev-database-reference-sql-functions-json) (`'$.geo.city'`), a JSON pointer (`'/geo/city'`) or a top-level key (`'user'`). It can come from a column. | | `paths` | `VARCHAR[]` | A constant list of paths, to check several in one call. | **Returns:** `BOOLEAN`. A list of paths, or a path with a wildcard, 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_exists`. 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` column: two objects, an array and a NULL. `DOC` is a sample document for the examples that don't read the table: ``` 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_exists"' 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)") run(f"INSERT INTO {TABLE} VALUES " "(1, '{\"user\": \"ada\", \"n\": 3, \"tags\": [\"a\", \"b\"], \"geo\": {\"city\": \"Oslo\", \"lat\": 59.9}}'), " "(2, '{\"user\": \"alan\", \"n\": \"many\", \"tags\": [], \"geo\": null}'), " "(3, '[10, 20, [30, 40]]'), " "(4, NULL)") DOC = """'{"user": "ada", "n": 3, "tags": ["a", "b", "c"], "geo": {"city": "Oslo", "lat": 59.9}, "z": null}'""" ``` ``` [] [] [(4,)] ``` ## What it does `json_exists` follows the path with the same [path forms](/develop/docs/dev-database-reference-sql-functions-json) as [json_extract](/develop/docs/dev-database-reference-sql-functions-json-json-extract), and returns whether it found anything. It looks at the structure, not the value: a key that holds JSON `null` exists. With a wildcard or a list of paths, it returns one boolean per match or per path. ``` run(f"SELECT json_exists({DOC}, '$.user'), json_exists({DOC}, '$.geo.city'), json_exists({DOC}, '$.z'), " f"json_exists({DOC}, '$.missing')") run(f"SELECT json_exists({DOC}, '/geo/city'), json_exists({DOC}, 'user'), json_exists({DOC}, '$.tags[-1]')") run(f"SELECT json_exists({DOC}, '$.tags[*]'), json_exists({DOC}, ['$.user', '$.n', '$.missing'])") ``` ``` [(True, True, True, False)] [(True, True, True)] [([True, True, True], [True, True, False])] ``` ## NULLs and edge cases | Input | Result | | --- | --- | | A NULL document or a NULL path | `NULL` | | A key whose value is JSON `null` (`'$.z'`) | `true` | | `'$'` on any valid document, including `'null'` and `'[]'` | `true` | | An array position past the end (`'$[0]'` on `'[]'`) | `false` | | An empty list of paths, `[]::VARCHAR[]` | `[]` | | `'not json'` | Error: `Malformed JSON at byte 0 of input: invalid literal. Input: not json` | | An integer path, `json_exists(json, 0)` | Error: `No function matches the given name and argument types`; write the position as a path, `'$[0]'` | The same cases, as the cluster returns them: ``` run(f"SELECT json_exists(NULL, '$.user'), json_exists({DOC}, NULL), json_exists({DOC}, '$.z')") run("SELECT json_exists('null', '$'), json_exists('[]', '$'), json_exists('[]', '$[0]'), " "json_exists('[1]', []::VARCHAR[])") run("SELECT json_exists('not json', '$.a')") run(f"SELECT json_exists({DOC}, 0)") ``` ``` [(None, None, True)] [(True, True, False, [])] OSError: Malformed JSON at byte 0 of input: invalid literal. Input: not json InternalError: Binder Error: No function matches the given name and argument types 'json_exists(STRING_LITERAL, INTEGER_LITERAL)'. You might need to add explicit type casts. ``` ## Examples Which events have a `geo` key, and which have a city inside it. Row 2's `geo` is JSON `null`: the key exists, the city doesn't: ``` run(f"SELECT id, json_exists(payload, '$.geo'), json_exists(payload, '$.geo.city') FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` [(1, True, True), (2, True, False), (3, False, False), (4, None, None)] ``` Keep the events that have a `geo` key: ``` run(f"SELECT id FROM {TABLE} WHERE json_exists(payload, '$.geo') ORDER BY id LIMIT 10") ``` ``` [(1,), (2,)] ``` ## 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 a JSON document as text and can't look inside it, so `json_exists` is always computed by the Query Engine: - **In the `SELECT` list,** the scan reads the whole `payload` column and the Query Engine parses each document it returns. - **In `WHERE`,** the scan sends `payload` for every row, and a `FILTER` step in the Query Engine parses each document and keeps the rows that match. No rows are skipped in storage. - **Every document it reads must be valid JSON.** The first invalid one stops the query with `Malformed JSON ...` (see [invalid JSON in a column](/develop/docs/dev-database-reference-sql-functions-json)). The plan of the `WHERE` example shows the `FILTER` step above the scan: ``` plan(f"SELECT id FROM {TABLE} WHERE json_exists(payload, '$.geo')") ``` ``` ┌───────────────────────────┐ │ PROJECTION │ │ ──────────────────── │ │ #1 │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ FILTER │ │ ──────────────────── │ │ json_exists(payload, '$ │ │ .geo') │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ VAST_SCAN │ │ ──────────────────── │ │ Function: VAST_SCAN │ │ │ │ Projections: │ │ payload │ │ id │ │ │ └───────────────────────────┘ ``` ## Make it faster - **Store a flag if you filter on it often.** A `BOOLEAN` column such as `has_geo`, set when you write the row, is evaluated in VAST DataBase; `json_exists(payload, '$.geo')` parses every row in the Query Engine. - **Narrow the rows with a pushed-down condition.** A condition such as `id = 1` is evaluated in VAST DataBase, so a query that fails on the whole table because of one invalid document can still run on the rows it keeps. ## Limitations and errors - **Paths are text.** There's no integer form; write an array position as `'$[0]'`. - **No SQL-standard path modes.** `'strict $.a'` isn't read as a path mode: `json_exists('{"a": 1}', 'strict $.a')` returns `false`. Use a plain path. - **Invalid JSON stops the query.** A pushed-down condition that leaves out the invalid rows lets the query run. - **A list of paths must be constant.** A list from a column fails with `List of paths must be constant`; a list can't contain NULL (`JSON path cannot be NULL`) or a wildcard. - **The document must be text.** A number fails with `No function matches the given name and argument types`; a `BLOB` fails with `Malformed JSON ...`. ``` run("SELECT json_exists('{\"a\": 1}', 'strict $.a'), json_exists('{\"a\": 1}', '$.a')") run(f"SELECT json_exists({DOC}, ['$.user', NULL])") ``` ``` [(False, True)] InternalError: Binder Error: JSON path cannot be NULL ``` ## Similar functions Three ways to test for `'$.z'`, a key whose value is JSON `null`: | Test | Result | | --- | --- | | `json_exists(json, '$.z')` | `true`: the key is there | | [json_extract](/develop/docs/dev-database-reference-sql-functions-json-json-extract)`(json, '$.z') IS NOT NULL` | `true`: it returns the text `'null'` | | [json_extract_string](/develop/docs/dev-database-reference-sql-functions-json-json-extract-string)`(json, '$.z') IS NOT NULL` | `false`: it returns SQL NULL for JSON `null` | ``` run(f"SELECT json_exists({DOC}, '$.z'), json_extract({DOC}, '$.z') IS NOT NULL, " f"json_extract_string({DOC}, '$.z') IS NOT NULL") ``` ``` [(True, True, False)] ``` To test whether a value occurs anywhere in a document, use [json_contains](/develop/docs/dev-database-reference-sql-functions-json-json-contains). To list an object's keys, use [json_keys](/develop/docs/dev-database-reference-sql-functions-json-json-keys). 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, and [JSON paths](/develop/docs/dev-database-reference-sql-functions-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.