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QueryInsightsResponse

Source code in docs_src/capo_timestream_query/types/query_insights_response.py 
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class QueryInsightsResponse(TypedDict, closed=True):
    query_spatial_coverage: NotRequired[
        "capo_timestream_query.types.query_spatial_coverage.QuerySpatialCoverage"
    ]
    """<p>Provides insights into the spatial coverage of the query, including the table with sub-optimal (max) spatial pruning. This information can help you identify areas for improvement in your partitioning strategy to enhance spatial pruning. </p>"""
    query_temporal_range: NotRequired[
        "capo_timestream_query.types.query_temporal_range.QueryTemporalRange"
    ]
    """<p>Provides insights into the temporal range of the query, including the table with the largest (max) time range. Following are some of the potential options for optimizing time-based pruning:</p> <ul> <li> <p>Add missing time-predicates.</p> </li> <li> <p>Remove functions around the time predicates.</p> </li> <li> <p>Add time predicates to all the sub-queries.</p> </li> </ul>"""
    query_table_count: NotRequired["capo_timestream_query.types.long.Long"]
    """<p>Indicates the number of tables in the query.</p>"""
    output_rows: NotRequired["capo_timestream_query.types.long.Long"]
    """<p>Indicates the total number of rows returned as part of the query result set. You can use this data to validate if the number of rows in the result set have changed as part of the query tuning exercise.</p>"""
    output_bytes: NotRequired["capo_timestream_query.types.long.Long"]
    """<p>Indicates the size of query result set in bytes. You can use this data to validate if the result set has changed as part of the query tuning exercise.</p>"""
    unload_partition_count: NotRequired["capo_timestream_query.types.long.Long"]
    """<p>Indicates the partitions created by the <code>Unload</code> operation.</p>"""
    unload_written_rows: NotRequired["capo_timestream_query.types.long.Long"]
    """<p>Indicates the rows written by the <code>Unload</code> query.</p>"""
    unload_written_bytes: NotRequired["capo_timestream_query.types.long.Long"]
    """<p>Indicates the size, in bytes, written by the <code>Unload</code> operation.</p>"""

output_bytes instance-attribute 

output_bytes: NotRequired[Long]

Indicates the size of query result set in bytes. You can use this data to validate if the result set has changed as part of the query tuning exercise.

output_rows instance-attribute 

output_rows: NotRequired[Long]

Indicates the total number of rows returned as part of the query result set. You can use this data to validate if the number of rows in the result set have changed as part of the query tuning exercise.

query_spatial_coverage instance-attribute 

query_spatial_coverage: NotRequired[QuerySpatialCoverage]

Provides insights into the spatial coverage of the query, including the table with sub-optimal (max) spatial pruning. This information can help you identify areas for improvement in your partitioning strategy to enhance spatial pruning.

query_table_count instance-attribute 

query_table_count: NotRequired[Long]

Indicates the number of tables in the query.

query_temporal_range instance-attribute 

query_temporal_range: NotRequired[QueryTemporalRange]

Provides insights into the temporal range of the query, including the table with the largest (max) time range. Following are some of the potential options for optimizing time-based pruning:

  • Add missing time-predicates.

  • Remove functions around the time predicates.

  • Add time predicates to all the sub-queries.

unload_partition_count instance-attribute 

unload_partition_count: NotRequired[Long]

Indicates the partitions created by the Unload operation.

unload_written_bytes instance-attribute 

unload_written_bytes: NotRequired[Long]

Indicates the size, in bytes, written by the Unload operation.

unload_written_rows instance-attribute 

unload_written_rows: NotRequired[Long]

Indicates the rows written by the Unload query.