Schemas:: ACCOUNT_USAGE

COLUMN_QUERY_PRUNING_HISTORY view¶

Use this Account Usage view to gain a better understanding of data access patterns during query execution, including some column-level details, such as the “access type” and candidate search optimization expressions that are potentially beneficial.

You can use this view in combination with the TABLE_QUERY_PRUNING_HISTORY view. For example, you can identify access to target tables by using the TABLE_QUERY_PRUNING_HISTORY view, then identify frequently used columns on those tables by using the COLUMN_QUERY_PRUNING_HISTORY view.

Each row in this view represents the query pruning history for a specific column within a given time interval. The data is aggregated per column, per table, per interval, and includes metrics such as the number of queries executed, partitions scanned, partitions pruned, rows scanned, rows pruned, and rows matched.

Columns¶

Column Name	Data Type	Description
INTERVAL_START_TIME	TIMESTAMP_LTZ	Start of the time range (on the hour mark) during which the queries were executed and completed.
INTERVAL_END_TIME	TIMESTAMP_LTZ	End of the time range (on the hour mark) during which the queries were executed and completed.
TABLE_ID	NUMBER	Internal/system-generated identifier for the table that was queried.
TABLE_NAME	VARCHAR	Name of the table that was queried.
SCHEMA_ID	NUMBER	Internal/system-generated identifier for the schema that contains the table that was queried.
SCHEMA_NAME	VARCHAR	Name of the schema that contains the table that was queried.
DATABASE_ID	NUMBER	Internal/system-generated identifier for the database that contains the table that was queried.
DATABASE_NAME	VARCHAR	Name of the database that contains the table that was queried.
WAREHOUSE_ID	NUMBER	Internal/system-generated identifier for the warehouse that was used to run the queries.
WAREHOUSE_NAME	VARCHAR	Name of the warehouse that ran the queries.
QUERY_HASH	VARCHAR	The hash value computed based on the canonicalized SQL text.
QUERY_PARAMETERIZED_HASH	VARCHAR	The hash value computed based on the parameterized query.
COLUMN_ID	NUMBER	Internal/system-generated identifier for the column accessed from the table that was queried.
COLUMN_NAME	VARCHAR	Name of the column accessed from the table that was queried.
VARIANT_PATH	VARCHAR	Path to the semi-structured data being accessed (if applicable). NULL if the column accessed does not have a semi-structured data type.
ACCESS_TYPE	VARCHAR	Type of access performed on the column (`WHERE` or `JOIN` condition).
NUM_QUERIES	NUMBER	Number of queries executed in this time range with this specific QUERY_HASH value, using this warehouse, accessing this column (and variant path if applicable) on this table with this type of access.
AGGREGATE_QUERY_ELAPSED_TIME	NUMBER	Total elapsed time (in milliseconds) for queries defined by NUM_QUERIES. This total includes queueing and other time not associated with compilation and execution.
AGGREGATE_QUERY_COMPILATION_TIME	NUMBER	Total compilation time (in milliseconds) for queries defined by NUM_QUERIES.
AGGREGATE_QUERY_EXECUTION_TIME	NUMBER	Total execution time (in milliseconds) for queries defined by NUM_QUERIES.
PARTITIONS_SCANNED	NUMBER	Number of partitions scanned on this table for queries defined by NUM_QUERIES.
PARTITIONS_PRUNED	NUMBER	Number of partitions pruned on this table for queries defined by NUM_QUERIES. These partitions were eliminated during query processing and not scanned, improving the efficiency of the query.
ROWS_SCANNED	NUMBER	Number of rows scanned on this table for queries defined by NUM_QUERIES.
ROWS_PRUNED	NUMBER	Number of rows pruned on this table for queries defined by NUM_QUERIES. These rows were eliminated during query processing and not scanned, improving the efficiency of the query.
ROWS_MATCHED	NUMBER	Number of rows that matched the WHERE clause filters while scanning this table for the queries defined by NUM_QUERIES.
SEARCH_OPTIMIZATION_SUPPORTED_EXPRESSIONS	ARRAY	List of supported search optimization expressions on this column that could potentially speed up scanning this table for the queries defined by NUM_QUERIES.

Usage notes¶

Latency for the view may be up to 4 hours.
Data is retained for 1 year.
This view does not include pruning information for hybrid tables.
Users and roles that have been granted the USAGE_VIEWER database role can access this view. For more information, see SNOWFLAKE database roles.
The ACCESS_TYPE column contains one of the following values:
- WHERE: The column is used in a filter condition in the WHERE clause.
- JOIN: The column is used in a condition for a JOIN operation.
The access behavior shown in this view reflects the actual query plan that was executed, which might be different from the original query text. For example, if a HAVING clause does not reference aggregated results produced by the GROUP BY clause, it might be optimized and rewritten as a WHERE clause, and the ACCESS_TYPE value will be WHERE.
For complex filtering conditions that can’t benefit from a pushdown optimization, rows might not be filtered out during the table scan operation, even if they do not match the filtering condition. Therefore, these rows are counted in the ROWS_MATCHED value.
Currently, the SEARCH_OPTIMIZATION_SUPPORTED_EXPRESSIONS column only suggests the EQUALITY and SUBSTRING search methods.
This view retains data for the 1,000 longest-running table scans per query. Only extremely complex queries exceed this number of scans so data is rarely omitted.

Example¶

For a given day, return column-level pruning history for queries against a specific table:

SELECT interval_start_time, table_name, column_name, access_type, num_queries,
    rows_scanned, rows_pruned, rows_matched,
    search_optimization_supported_expressions::VARCHAR as search_optim
  FROM SNOWFLAKE.ACCOUNT_USAGE.COLUMN_QUERY_PRUNING_HISTORY
  WHERE interval_start_time like '2025-04-24%' AND table_name='SENSOR_DATA_TS'
  ORDER BY 3, 1;

Copy

+-------------------------------+----------------+-------------+-------------+-------------+--------------+-------------+--------------+-----------------------------+
| INTERVAL_START_TIME           | TABLE_NAME     | COLUMN_NAME | ACCESS_TYPE | NUM_QUERIES | ROWS_SCANNED | ROWS_PRUNED | ROWS_MATCHED | SEARCH_OPTIM                |
|-------------------------------+----------------+-------------+-------------+-------------+--------------+-------------+--------------+-----------------------------|
| 2025-04-24 14:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |            5 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 14:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |            5 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 15:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |      2678400 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 15:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |      2678400 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 15:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |            5 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 15:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |      2678400 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |      2678400 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |      2678400 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 19:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |      2678400 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 19:00:00.000 -0700 | SENSOR_DATA_TS | DEVICE_ID   | WHERE       |           1 |      2678400 |     2678400 |      2678400 | ["EQUALITY(\"DEVICE_ID\")"] |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      5356800 |           0 |      3262387 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      2678400 |     2678400 |       394106 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      5356800 |           0 |      1227686 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      2678400 |     2678400 |       216642 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      2678400 |     2678400 |       216642 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      5356800 |           0 |      1227686 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      5356800 |           0 |       820272 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      5356800 |           0 |      3262387 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      5356800 |           0 |      3262387 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      5356800 |           0 |      1227686 | NULL                        |
| 2025-04-24 17:00:00.000 -0700 | SENSOR_DATA_TS | TEMPERATURE | WHERE       |           1 |      2678400 |     2678400 |       216642 | NULL                        |
+-------------------------------+----------------+-------------+-------------+-------------+--------------+-------------+--------------+-----------------------------+

The sensor_data_ts table in this query contains 5356800 rows of synthetic time-series data. Exactly half of the rows in the table (2678400) were pruned for a number of queries that filtered the device_id and temperature columns in WHERE clause conditions.

The device_id column is suggested as a target for a search optimization that uses the EQUALITY search method. Table scans might benefit from the addition of this search optimization.

Tip

You can use the ARRAY_TO_STRING function to convert the SEARCH_OPTIMIZATION_SUPPORTED_EXPRESSIONS column to a string for easier readability. For example:

ARRAY_TO_STRING(search_optimization_supported_expressions, ', ')

Copy