Query tags

Important

This page describes how to use query tags to group, filter, and attribute costs for SQL workloads on Databricks SQL warehouses.

Query tags are custom key-value pairs (for example, team:marketing or dbt_model_name:some_model_name) that you apply to SQL workloads. These tags appear in the system.query.history table and on the Query History page of the Azure Databricks UI, and are returned in responses to the ListQueries API if non-empty. Query tags allow you to group queries by business context, attribute warehouse costs, and identify sources of long-running queries.

Warning

Tag data is stored as plain text and might be replicated globally. Don't use tag keys or values that contain passwords, personal information, or other sensitive data.

Requirements

Before using query tags, verify the following:

Confirm you can access the system.query.history table, specifically the query_tags column. If not, contact your account admin. See Query history system table reference.
Minimum version requirements based on where you set query tags:
- dbt: dbt-databricks 1.11.0
- Power BI: October 2025 release
- Python Connector: v4.1.3
- Node.js Connector: v1.12.0
- Go Connector: v1.9.0
- JDBC driver (OSS): v3.0.3

Query tag scope

Query tags are scoped to Databricks SQL sessions. You can set them when creating a session as a configuration parameter, or within a session using the SET QUERY_TAGS SQL statement. After you set tags, all subsequent statements in the session are associated with those tags.

Set query tags

You can set query tags using session configuration parameters or SQL statements.

Use session configuration parameters

Set query tags using the query_tags configuration parameter (or ssp_query_tags in some drivers) when creating a session. The value is a serialized set of key-value pairs, with a colon (:) separating keys and values, and a comma (,) separating pairs. This string format is accepted by the client interfaces listed in Set query tags from tools and interfaces. For instructions on configuring sessions in your specific client, see the examples below.

If a colon (:), comma (,), or backslash (\) appears in a value, escape it with a leading backslash (\\:, \\,, or \\\\). Backslash (\) must be escaped in both keys and values.

The following example specifies tags team=eng, cost_center=701, a key-only tag exp, and a metadata tag with a JSON blob:

query_tags = team:eng,cost_center:701,exp,metadata:{"foo"\\:"bar"\\,"baz"\\:1}

Use SQL statements

Use the SET QUERY_TAGS statement to set, read, or remove query tags for the current session.

For syntax, parameters, and examples, see SET QUERY_TAGS.

Set query tags from tools and interfaces

Azure Databricks UI

Use the SET QUERY_TAGS SQL statement anywhere you can submit SQL to a warehouse, including the SQL editor, notebooks, and dashboards. See SET QUERY_TAGS.

dbt

Minimum version: dbt-databricks 1.11.0

The following reserved query tag keys are set automatically for all dbt runs and can't be overridden:

{
  "dbt_model_name": "my_model",
  "dbt_core_version": "1.10.7",
  "dbt_databricks_version": "1.11.0",
  "dbt_materialized": "incremental"
}

Note

Default tags are subject to syntax limitations. Model names that include unescaped colons or commas result in tag_invalid: true in the system table.

You can add custom query tags at both project and model levels. Model configuration takes priority over connection configuration.

Project-level tag (~/.dbt/profiles.yml):

your_profile_name:
  target: dev
  outputs:
    dev:
      query_tags: '{"team": "marketing", "cost_center": "3000"}'

Model-level tag (~/.dbt/dbt_project.yml):

name: 'your_project'
version: '1.0.0'
config-version: 2
models:
  your_model:
    +query_tags: '{"team": "content-marketing"}'

Result with both configurations:

{
  "team": "content-marketing",
  "cost_center": "3000",
  "dbt_model_name": "model.dev.your_model",
  "dbt_core_version": "1.10.7",
  "dbt_databricks_version": "1.11.0",
  "dbt_materialized": "incremental"
}

Power BI

Minimum version: October 2025 release

Configure the connection to the warehouse.
Navigate to the Databricks settings dialog, as shown in the following image.
In the Query tags text box, enter query tags using the session configuration parameter syntax.
Click OK.

Note

Changing query tags and clicking OK starts a new session. Previously set tags are discarded.

Tableau

Configure the connection to the warehouse.
Navigate to the Initial SQL tab.
Enter query tags using the SET QUERY_TAGS. You can include Tableau parameters in the key or value.
Click Sign In to save and authenticate.

Note

Changing the Initial SQL and clicking Sign In starts a new session. Previously set tags are discarded.

Python Connector

Minimum version: v4.1.3

from databricks import sql
import os

with sql.connect(
    server_hostname = os.getenv("DATABRICKS_SERVER_HOSTNAME"),
    http_path       = os.getenv("DATABRICKS_HTTP_PATH"),
    access_token    = os.getenv("DATABRICKS_TOKEN"),
    session_configuration = {
        'query_tags': 'team:engineering,dashboard:abc123'
    }
) as connection:
    with connection.cursor() as cursor:
        cursor.execute("SELECT * FROM samples.nyctaxi.trips LIMIT 10")
        result = cursor.fetchall()

Node.js Connector

Minimum version: v1.12.0

const { DBSQLClient } = require('@databricks/sql');
const client = new DBSQLClient();

client
  .connect({
    host: process.env.DATABRICKS_SERVER_HOSTNAME,
    path: process.env.DATABRICKS_HTTP_PATH,
    token: process.env.DATABRICKS_TOKEN,
  })
  .then(async (client) => {
    const session = await client.openSession({
      configuration: {
        query_tags: 'team:engineering,env:prod',
      },
    });

    const queryOperation = await session.executeStatement('SELECT * FROM samples.nyctaxi.trips LIMIT 10');
    const result = await queryOperation.fetchAll();

    await queryOperation.close();
    await session.close();
    await client.close();
  })
  .catch((error) => {
    console.error(error);
  });

Go Connector

Minimum version: v1.9.0

DSN connection string:

package main

import (
    "database/sql"
    "fmt"
    _ "github.com/databricks/databricks-sql-go"
)

func main() {
    dsn := "token:dapi1234@myworkspace.cloud.databricks.com:443/sql/1.0/endpoints/abc123?query_tags=team:engineering,env:prod"

    db, err := sql.Open("databricks", dsn)
    if err != nil {
        panic(err)
    }
    defer db.Close()

    rows, err := db.Query("SELECT * FROM samples.nyctaxi.trips LIMIT 10")
    if err != nil {
        panic(err)
    }
    defer rows.Close()
}

NewConnector with WithSessionParams:

package main

import (
    "database/sql"
    "os"
    dbsql "github.com/databricks/databricks-sql-go"
)

func main() {
    connector, err := dbsql.NewConnector(
        dbsql.WithAccessToken(os.Getenv("DATABRICKS_ACCESS_TOKEN")),
        dbsql.WithServerHostname(os.Getenv("DATABRICKS_HOST")),
        dbsql.WithPort(443),
        dbsql.WithHTTPPath(os.Getenv("DATABRICKS_HTTP_PATH")),
        dbsql.WithSessionParams(map[string]string{
            "query_tags": "team:engineering,env:prod",
        }),
    )
    if err != nil {
        panic(err)
    }

    db := sql.OpenDB(connector)
    defer db.Close()

    rows, err := db.Query("SELECT * FROM samples.nyctaxi.trips LIMIT 10")
    if err != nil {
        panic(err)
    }
    defer rows.Close()
}

JDBC driver (OSS)

Minimum version: v3.0.3

Connection URL:

String url = "jdbc:databricks://myworkspace.cloud.databricks.com:443/default;" +
             "httpPath=/sql/1.0/endpoints/abc123;" +
             "query_tags=team:engineering,env:prod;" +
             "AuthMech=3;UID=token;PWD=dapi1234";

Connection conn = DriverManager.getConnection(url);
Statement stmt = conn.createStatement();
ResultSet rs = stmt.executeQuery("SELECT * FROM samples.nyctaxi.trips LIMIT 10");

Properties object:

String url = "jdbc:databricks://myworkspace.cloud.databricks.com:443/default";
Properties properties = new Properties();
properties.put("httpPath", "/sql/1.0/endpoints/abc123");
properties.put("query_tags", "team:engineering,env:prod");
properties.put("AuthMech", "3");
properties.put("UID", "token");
properties.put("PWD", "dapi1234");

Connection conn = DriverManager.getConnection(url, properties);
Statement stmt = conn.createStatement();
ResultSet rs = stmt.executeQuery("SELECT * FROM samples.nyctaxi.trips LIMIT 10");

JDBC driver (Simba)

Connection URL:

String url = "jdbc:databricks://myworkspace.cloud.databricks.com:443;" +
             "httpPath=/sql/1.0/endpoints/abc123;" +
             "ssp_query_tags=team:engineering,env:prod;" +
             "AuthMech=3;UID=token;PWD=dapi1234";

Connection conn = DriverManager.getConnection(url);
Statement stmt = conn.createStatement();
ResultSet rs = stmt.executeQuery("SELECT * FROM samples.nyctaxi.trips LIMIT 10");

Properties object:

String url = "jdbc:databricks://myworkspace.cloud.databricks.com:443";
Properties properties = new Properties();
properties.put("httpPath", "/sql/1.0/endpoints/abc123");
properties.put("ssp_query_tags", "team:engineering,env:prod");
properties.put("AuthMech", "3");
properties.put("UID", "token");
properties.put("PWD", "dapi1234");

Connection conn = DriverManager.getConnection(url, properties);
Statement stmt = conn.createStatement();
ResultSet rs = stmt.executeQuery("SELECT * FROM samples.nyctaxi.trips LIMIT 10");

ODBC driver

Include the ssp_query_tags parameter in your ODBC connection configuration.

Limitations

Maximum of 20 user-specified tags per query. When using non-SQL interfaces (session configuration parameters), additional tags are discarded and a sentinel tag tag_truncated: true is added.
Tag keys and values must not exceed 128 characters. When using non-SQL interfaces (session configuration parameters), tags that are not valid are discarded and tag_invalid is added.
Tag keys must not contain the characters ,, :, -, /, =, or .. When using non-SQL interfaces (session configuration parameters), tags that are not valid are discarded and tag_invalid is added. SQL statements with invalid tag keys fail with an error at execution time.
Query tags are only supported for Databricks SQL workloads. The query_tags column is not populated for other compute types.
Azure Databricks may use keys starting with @@ internally. Some connectors already use this prefix. Avoid this prefix to prevent conflicts.

View query tags

Query the system.query.history table to view query tags. You can group and filter by specific keys or key-value pairs.

SELECT statement_id, query_tags, user_name, start_time
FROM system.query.history
WHERE MAP_CONTAINS_KEY(query_tags, 'team')
  AND query_tags['team'] = 'engineering'
ORDER BY start_time DESC
LIMIT 100;

Note

Key-only tags appear with a null value. To filter for them:

WHERE MAP_CONTAINS_KEY(query_tags, 'key') AND query_tags['key'] IS NULL

For more information, see Query history system table reference.

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Last updated on 2026-02-06

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Query tags

Requirements

Query tag scope

Set query tags

Use session configuration parameters

Use SQL statements

Set query tags from tools and interfaces

Azure Databricks UI

dbt

Power BI

Tableau

Python Connector

Node.js Connector

Go Connector

JDBC driver (OSS)

JDBC driver (Simba)

ODBC driver

Limitations

View query tags

Feedback

Additional resources