A unique id for the current batch of data being processed.
The amount of time taken to perform various operations in milliseconds.
Statistics of event time seen in this batch.
An unique query id that persists across restarts.
The aggregate (across all sources) rate of data arriving.
The compact JSON representation of this progress.
User-specified name of the query, null if not specified.
The aggregate (across all sources) number of records processed in a trigger.
The pretty (i.e.
The aggregate (across all sources) rate at which Spark is processing data.
A query id that is unique for every start/restart.
detailed statistics on data being read from each of the streaming sources.
Information about operators in the query that store state.
Beginning time of the trigger in ISO8601 format, i.e.