This view provides a high-level summary profile of all tasks which ran recently on any node in the workspace.

It holds a row per high-level activity H. Each row describes the set of tasks which have run over a recent interval of time and which are either instances of the high level activity H, or else instances of an activity L whose aggregator activity name is the name of H. It reports the sum of the profiling statistics of each task in the set, as collected over the recent interval. Activities can include tasks such as garbage collection and backups, in addition to queries.

The effect of grouping the instances of multiple activities together is mainly to group all tasks associated with a query, across all partitions, into a single row.

mv_activities determines recent resource use by computing the change in mv_activities_cumulative over an interval of time. This interval is controlled by the value of the activities_delta_sleep_s session variable.

mv_activities may only be queried while connected to an aggregator node.

We recommend using this view to begin a performance investigation, as it is the most concise.

However, we recommend against the use of mv_activities to compute the average latency or resource usage of a query. This is because its statistics include the latency and resource usage of currently running tasks, which will skew attempted average calculations. We recommend mv_finished_tasks for this purpose instead.

Column name



The type of the high-level activity.


The name of the high-level activity. This column is often human-readable, but does not include the full query text for query tasks. Join with mv_queries for the query text.


The name of the database associated with the activity, or NULL if none could be assigned.


The number of instances which were running at the end of the interval.


The number of instances which completed successfully during the interval.


The number of instances which completed unsuccessfully during the interval.


This view contains all simplified statistics columns.

Last modified: June 1, 2023

Was this article helpful?