Documentation

Retrieve system information for a query

Learn how to retrieve system information for a query in InfluxDB Cloud Dedicated.

In addition to the SQL standard information_schema, InfluxDB Cloud Dedicated contains system tables that provide access to InfluxDB-specific information. The information in each system table is scoped to the namespace you’re querying; you can only retrieve system information for that particular instance.

To get information about queries you’ve run on the current instance, use SQL to query the system.queries table, which contains information from the Querier instance currently handling queries.

The system.queries table is an InfluxDB 3 debug feature. To enable the feature and query system.queries, include an "iox-debug" header set to "true" and use SQL to query the table–for example:

from influxdb_client_3 import InfluxDBClient3
import secrets
import pandas

def get_query_information():
  print('# Get query information')

  client = InfluxDBClient3(token = f"
DATABASE_TOKEN
"
,
host = f"cluster-id.a.influxdb.io", database = f"
DATABASE_NAME
"
)
sql = "SELECT * FROM home WHERE time >= now() - INTERVAL '30 days'" try: client.query(sql) client.close() except Exception as e: print("Query error: ", e) client = InfluxDBClient3(token = f"
DATABASE_TOKEN
"
,
host = f"cluster-id.a.influxdb.io", database = f"
DATABASE_NAME
"
)
import time df = pandas.DataFrame() for i in range(0, 5): time.sleep(1) # Use SQL # To retrieve data about your query from the system.queries table, pass the following: # - the iox-debug: true request header # - an SQL query for system.queries reader = client.query(f'''SELECT compute_duration, query_type, query_text, success FROM system.queries WHERE issue_time >= now() - INTERVAL '1 day' ORDER BY issue_time DESC ''', headers=[(b"iox-debug", b"true")], mode="reader") df = reader.read_all().to_pandas() if df.shape[0]: break # Adjust pandas display options to avoid truncating the output # Filter the DataFrame to get rows where the column contains the query text filtered_df = df[df['query_text'] == sql] assert filtered_df.shape[0] > 0, "filtered_df should have at least 1 row" # Specify system.queries columns to output columns_to_output = ['compute_duration', 'query_text'] # Print row values for the specified columns print(filtered_df[columns_to_output]) get_query_information()

The output is similar to the following:

# Get query information
            compute_duration                                         query_text
3            0 days  SELECT * FROM home WHERE time >= now() - INTER...
4            0 days  SELECT * FROM home WHERE time >= now() - INTER...

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New in InfluxDB 3.5

Key enhancements in InfluxDB 3.5 and the InfluxDB 3 Explorer 1.3.

See the Blog Post

InfluxDB 3.5 is now available for both Core and Enterprise, introducing custom plugin repository support, enhanced operational visibility with queryable CLI parameters and manual node management, stronger security controls, and general performance improvements.

InfluxDB 3 Explorer 1.3 brings powerful new capabilities including Dashboards (beta) for saving and organizing your favorite queries, and cache querying for instant access to Last Value and Distinct Value caches—making Explorer a more comprehensive workspace for time series monitoring and analysis.

For more information, check out:

InfluxDB Docker latest tag changing to InfluxDB 3 Core

On November 3, 2025, the latest tag for InfluxDB Docker images will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments.

If using Docker to install and run InfluxDB, the latest tag will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments. For example, if using Docker to run InfluxDB v2, replace the latest version tag with a specific version tag in your Docker pull command–for example:

docker pull influxdb:2