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.
A 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.