Cloudera, Inc.

Priyank Patel

Anjali Betawadkar-Norwood

Sushil Thomas

Douglas James Cameron

Shant Hovsepian

A system comprises a computer network and worker machines connected to the computer network. The worker machines store partitions of a distributed database. A master machine is connected to the computer network. The master machine includes a query processor to identify a star query that references a fact table and related dimension tables that characterize attributes of facts in the fact table. Eager aggregation is applied to a query plan associated with the star query. The eager aggregation alters the query plan by moving an aggregation operation before a join operation to form an eager aggregated query plan. An analytical view with data responsive to the eager aggregated query plan is identified. The eager aggregated query plan is revised to form a final query plan. The final query plan references the analytical view. The final query plan is executed to produce query results.

Apparatus and method for accelerated query processing using eager aggregation and analytical view matching

A system has a distributed database with database partitions distributed across worker nodes connected by a network. An analytical view recommendation engine defines an analytical view comprising attributes and measures defined prior to the receipt of a query. The analytical view is maintained as a data unit separate from the distributed database. The analytical view recommendation engine includes instructions executed by a processor to identify a poorly performing report, evaluate queries associated with the poorly performing report, create a recommended analytical view to enhance the performance of the poorly performing report, and deploy the recommended analytical view.

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Fremont, CA, United States of America

Priyank Patel