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 v3 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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