--- title: "json_value" slug: "dev-database-reference-sql-functions-json-json-value" updated: 2026-10-30T18:19:06Z published: 2026-10-30T18:19:06Z canonical: "docs.vastdata.com/dev-database-reference-sql-functions-json-json-value" --- > ## 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_value *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) › Read values.* Returns the scalar value (a string, number, or boolean) at a path in a JSON document, as JSON text: a string keeps its quotes. For an object, an array or JSON `null`, it returns NULL. ## Syntax ``` json_value(json, path) json_value(json, paths) ``` | Argument | Type | Description | | --- | --- | --- | | `json` | `VARCHAR` or `JSON` | The JSON document. | | `path` | `VARCHAR` or an integer | A [JSON path](/develop/docs/dev-database-reference-sql-functions-json) (`'$.geo.city'`), a JSON pointer (`'/geo/city'`), a top-level key (`'user'`), or an array position (`0`). It can come from a column. | | `paths` | `VARCHAR[]` | A constant list of paths, to read several values in one call. | **Returns:** `VARCHAR`, holding JSON text. A list of paths, or a path with a wildcard, returns `VARCHAR[]`. ## 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_value`. 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_value"' 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_value` reads a value 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 it only if it's a scalar: | Value at the path | Result | | --- | --- | | A string, `"ada"` | `'"ada"'`: JSON text, with the quotes | | A number, `3`, or a boolean, `true` | `'3'`, `'true'` | | An object or an array | `NULL` | | JSON `null` | `NULL` | | Nothing (the path isn't in the document) | `NULL` | With a wildcard or a list of paths, the result is a list with one element per match, and NULL for each match that isn't a scalar. ``` run(f"SELECT json_value({DOC}, '$.user'), json_value({DOC}, '$.n'), json_value({DOC}, '$.geo'), " f"json_value({DOC}, '$.tags'), json_value({DOC}, '$.z')") run(f"SELECT json_value({DOC}, '$.*')") ``` ``` [('"ada"', '3', None, None, None)] [(['"ada"', '3', None, None, None],)] ``` ## NULLs and edge cases | Input | Result | | --- | --- | | A NULL document or a NULL path | `NULL` | | The whole document, `'$'`, when it's an object or array | `NULL` | | A bare scalar document, `'42'` or `'"s"'`, with `'$'` | `'42'`, `'"s"'` | | An integer position on an element that is an array (`json_value('[1, [2, 3]]', 1)`) | `NULL` | | An integer position on a scalar element (`json_value('[1, 2, 3]', 1)`) | `'2'` | | `'not json'` | Error: `Malformed JSON at byte 0 of input: invalid literal. Input: not json` | The same cases, as the cluster returns them: ``` run(f"SELECT json_value(NULL, '$.user'), json_value({DOC}, NULL), json_value({DOC}, '$'), " "json_value('42', '$'), json_value('\"s\"', '$')") run("SELECT json_value('[1, [2, 3]]', 1), json_value('[1, 2, 3]', 1)") run("SELECT json_value('not json', '$.a')") ``` ``` [(None, None, None, '42', '"s"')] [(None, '2')] OSError: Malformed JSON at byte 0 of input: invalid literal. Input: not json ``` ## Examples The user, the `geo` object (NULL: it isn't a scalar) and the second element of the array in row 3: ``` run(f"SELECT id, json_value(payload, '$.user'), json_value(payload, '$.geo'), json_value(payload, '$[1]') " f"FROM {TABLE} ORDER BY id LIMIT 10") ``` ``` [(1, '"ada"', None, None), (2, '"alan"', None, None), (3, None, None, '20'), (4, None, None, None)] ``` Compare with a JSON string: the value keeps its quotes, so the constant needs them too: ``` run(f"SELECT id FROM {TABLE} WHERE json_value(payload, '$.user') = '\"ada\"' ORDER BY id LIMIT 10") ``` ``` [(1,)] ``` ## How it runs in VAST The Query Engine runs on the cluster's CNodes, and a query on a table starts with a scan in VAST DataBase (`VAST_SCAN`). VAST DataBase stores a JSON document as text and can't read one field of it, so `json_value` is always computed by the Query Engine: - **In the `SELECT` list,** the scan reads the whole `payload` column and the Query Engine parses each document it returns. - **In `WHERE`,** the scan sends `payload` for every row, and a `FILTER` step in the Query Engine parses each document and keeps the rows that match. No rows are skipped in storage. - **Every document it reads must be valid JSON.** The first invalid one stops the query with `Malformed JSON ...` (see [invalid JSON in a column](/develop/docs/dev-database-reference-sql-functions-json)). The plan of the `WHERE` example shows the `FILTER` step above the scan: ``` plan(f"SELECT id FROM {TABLE} WHERE json_value(payload, '$.user') = '\"ada\"'") ``` ``` ┌───────────────────────────┐ │ PROJECTION │ │ ──────────────────── │ │ #1 │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ FILTER │ │ ──────────────────── │ │ (json_value(payload, '$ │ │ .user') = '"ada"') │ │ │ └─────────────┬─────────────┘ ┌─────────────┴─────────────┐ │ VAST_SCAN │ │ ──────────────────── │ │ Function: VAST_SCAN │ │ │ │ Projections: │ │ payload │ │ id │ │ │ └───────────────────────────┘ ``` ## Make it faster - **Store the fields you filter on in their own columns.** A comparison of a column with a constant is pushed down to VAST DataBase; the same comparison on a field inside JSON 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 - **Scalars only.** To read an object or an array, use [json_extract](/develop/docs/dev-database-reference-sql-functions-json-json-extract). - **Strings keep their quotes.** For plain text, use [json_extract_string](/develop/docs/dev-database-reference-sql-functions-json-json-extract-string). - **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 or a wildcard. - **The document must be text.** A number fails with `No function matches the given name and argument types`, for example `'json_value(INTEGER_LITERAL, STRING_LITERAL)'`; a date, a boolean or a list returns `NULL`, and a `BLOB` fails with `Malformed JSON ...`. - **The SQL-standard `RETURNING` clause isn't available.** `JSON_VALUE(json, path RETURNING BIGINT)` is a syntax error. Cast the result instead, or use `TRY_CAST(json_extract_string(...) AS BIGINT)`. - **Other SQL dialects' names aren't available.** `json_extract_scalar` fails with `Scalar Function with name json_extract_scalar does not exist!`. ``` run("SELECT json_value(123, '$.a')") run("SELECT json_extract_scalar('{\"a\": 1}', '$.a')") run("SELECT TRY_CAST(json_extract_string('{\"a\": 1}', '$.a') AS BIGINT)") ``` ``` InternalError: Binder Error: No function matches the given name and argument types 'json_value(INTEGER_LITERAL, STRING_LITERAL)'. You might need to add explicit type casts. InternalError: Catalog Error: Scalar Function with name json_extract_scalar does not exist! [(1,)] ``` ## Similar functions | Function | `'$.user'` | `'$.geo'` (an object) | `'$.tags'` (an array) | `'$.z'` (JSON `null`) | | --- | --- | --- | --- | --- | | `json_value` | `'"ada"'` | `NULL` | `NULL` | `NULL` | | [json_extract](/develop/docs/dev-database-reference-sql-functions-json-json-extract) | `'"ada"'` | `'{"city":"Oslo","lat":59.9}'` | `'["a","b","c"]'` | `'null'` | | [json_extract_string](/develop/docs/dev-database-reference-sql-functions-json-json-extract-string) | `'ada'` | `'{"city":"Oslo","lat":59.9}'` | `'["a","b","c"]'` | `NULL` | ``` run(f"SELECT json_value({DOC}, '$.user'), json_value({DOC}, '$.geo'), json_value({DOC}, '$.tags'), " f"json_value({DOC}, '$.z')") run(f"SELECT json_extract({DOC}, '$.user'), json_extract({DOC}, '$.geo'), json_extract({DOC}, '$.tags'), " f"json_extract({DOC}, '$.z')") run(f"SELECT json_extract_string({DOC}, '$.user'), json_extract_string({DOC}, '$.geo'), " f"json_extract_string({DOC}, '$.tags'), json_extract_string({DOC}, '$.z')") ``` ``` [('"ada"', None, None, None)] [('"ada"', '{"city":"Oslo","lat":59.9}', '["a","b","c"]', 'null')] [('ada', '{"city":"Oslo","lat":59.9}', '["a","b","c"]', 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, 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.