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Active partitioned DMLs statistics | Spanner

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Active partitioned Data Manipulation Language (DML) provides real time progress for the partitioned DMLs that are active in your database.

Spanner provides a built-in table, SPANNER_SYS.ACTIVE_PARTITIONED_DMLS, that lists running partitioned DMLs and the progress made on them.

This page describes the table in detail, show some example queries that use this table and, finally, demonstrate how to use these queries to help mitigate issues caused by active partitioned DMLs. The information on this page is applicable to GoogleSQL-dialect databases and PostgreSQL-dialect databases.

Spanner provides the active partitioned DML statistics in the SPANNER_SYS schema. You can use the following ways to access SPANNER_SYS data:

• A database's Spanner Studio page in the Google Cloud console.

• The gcloud spanner databases execute-sql command.

• The executeSql or the executeStreamingSql method.

The following single read methods that Spanner provides don't support SPANNER_SYS:

• Performing a strong read from a single row or multiple rows in a table.
• Performing a stale read from a single row or multiple rows in a table.
• Reading from a single row or multiple rows in a secondary index.

SPANNER_SYS.ACTIVE_PARTITIONED_DMLS returns a list of active partitioned DMLs sorted by their start time.

The following shows the table schema for SPANNER_SYS.ACTIVE_PARTITIONED_DMLS.

You can run the following example SQL statements using the client libraries, the Google Cloud CLI, or the Google Cloud console.

The following query returns a list of running partitioned DMLs sorted by the start time of the query.

SELECT text,
       session_id,
       num_partitions_total,
       num_partitions_complete,
       num_trivial_partitions_complete,
       progress,
       rows_processed,
       start_timestamp,
       last_update_timestamp
FROM spanner_sys.active_partitioned_dmls
ORDER BY start_timestamp ASC;

Using the SPANNER_SYS.ACTIVE_PARTITIONED_DMLS table has the following limitations:

• PROGRESS, ROWS_PROCESSED, and LAST_UPDATE_TIMESTAMP results are incremented at completed partition boundaries so the partitioned DML might keep updating rows while the values in these three fields stay the same.

• If there are millions of partitions in a partitioned DML, the value in the PROGRESS column might not capture all incremental progress. Use NUM_PARTITIONS_COMPLETE and NUM_TRIVIAL_PARTITIONS_COMPLETE to refer finer granularity progress.

• If you cancel a partitioned DML using an RPC request, the cancelled partitioned DML might still appear in the table. If you cancel a partitioned DML using session deletion, it's removed from the table immediately. For more information, see Deleting the session ID.

Query statistics and transaction statistics provide useful information when troubleshooting latency in a Spanner database. These tools provide information about the queries that have already completed. However, sometimes it's necessary to know what is running in the system. For example, consider the scenario when CPU utilization is high and you want to answer the following questions.

• How many partitioned DMLs are running at the moment?
• What are these partitioned DMLs?
• How many of those partitioned DMLs are running for a long time?
• Which session is running the query?

If you have answers for the preceding questions, you can decide to take the following action.

• Delete the session executing the query for an immediate resolution.
• Reduce the frequency of a partitioned DML.

In the following walkthrough, we examine active partitioned DMLs and determine what action, if any, to take.

In our example scenario, we notice higher than normal CPU usage, so we decide to run the following query to return the count of active partitioned DMLs.

SELECT count(*) as active_count
FROM spanner_sys.active_partitioned_dmls;

The query yields the following result.

We can then run a query to find more information about the top 2 oldest running partitioned DMLs sorted by the start time of the partitioned DML.

SELECT text,
       session_id,
       num_partitions_total,
       num_partitions_complete,
       num_trivial_partitions_complete,
       progress,
       rows_processed,
       start_timestamp,
       last_update_timestamp
FROM spanner_sys.active_partitioned_dmls
ORDER BY start_timestamp ASC LIMIT 2;

We found a partitioned DML that has been running for days and isn't making progress. We can therefore run the following gcloud spanner databases sessions delete command to delete the session using the session ID which cancels the partitioned DML.

gcloud spanner databases sessions delete\
   5bd37a99-200c-5d2e-9021-15d0dbbd97e6 \
    --database=singer_db --instance=test-instance

• Learn about other Introspection tools.
• Learn about other information Spanner stores for each database in the database's information schema tables.
• Learn more about SQL best practices for Spanner.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

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