![]() Stage and load processing time (in milli-seconds) for SQL queries.INFO 02:53:57.000980 - Time spent flushing aggregated operations : INFO 02:53:57.000980 - Time spent aggregating operations : INFO 02:53:57.000980 - Number of update operations merged into an existing update operation: Operation aggregation time (in milli-seconds) in-memory:.Diagnostic information on the apply process is logged onto the handler log file.This may not always be the case on all the customer deployments. Oracle have revealed that operation aggregation in memory delivers better apply ![]() Mutually exclusive and only one of them should be enabled at a time. Requires more SQL processing on the Redshift database. ( gg.aggregagte.operations=true) is memory intensive where as Therefore, RedshiftĪpply will ABEND if the target table is missing. The column metadata in the trail file may not be always correct. Primary keys, sort keys, partition distribution key columns.
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