International Business Machines Corporation

Cloudera, Inc.

Arcadia Data Inc.

Teradata Us, Inc.

Anjali Betawadkar-Norwood

Shant Hovsepian

Priyank Patel

David Everett Simmen

Edison Lao Ting

Tuong Chanh Truong

Tian Zhang

Mayank Pradhan

Douglas James Cameron

Normen Seemann

Radhika Reddy

Eileen Tien Lin

Sushil Thomas

Tam Minh Dai Tran

Hamid Pirahesh

Tongxin Bai

Rachit Agarwal

Aditi Subodh Pandit

Derrick Poo-Ray Kondo

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 and method for determining optimal query plans within distributed database system employing table operators for performing analytic operations for storing and processing multi-structured data. The optimization of a query plan proceeds through a collaborative exchange between a database system optimizer, or planner, and a table operator, wherein multiple communications between said optimizer and said table operator are conducted to exchange input and output information relevant to optimizing execution of the query and table operator.

Collaborative planning for accelerating analytic queries

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.

Apparatus and method for recommending and maintaining analytical views

A system includes a distributed database with database partitions distributed across worker nodes connected by a network. An analytical view module defines an analytical view comprising dimensions and aggregates defined prior to receipt of a query and maintained as a data unit separate from the distributed database. The analytical view module includes instructions executed by a processor to form analytical view partitions. The query is evaluated to identify implicated fresh analytical view partitions and implicated stale analytical view partitions. The implicated fresh analytical view partitions are accessed to obtain analytical view results. Database results corresponding to the implicated stale analytical view partitions are obtained. A response to the query is supplied based upon the analytical view results and the database results.

Apparatus and method for query processing using analytical view partitions and database partitions

A system has worker machines connected by a network. Each worker machine stores at least one partition of a distributed database and a partial function module to initialize a database dimension, increment an aggregate of the database dimension in response to a data change and to serialize a last aggregate of the database dimension in response to a refresh operation to form partial results of an analytical view. An analytical view machine connected to the network responds to a query without accessing a partition of the distributed database. The analytical view machine merges partial results from the worker machines to produce a final result to the query.

Apparatus and method for allowing complex aggregates in analytical views in a distributed database

Embodiments are included for methods, systems, and computer program products in which evaluating operations using an electronic computing device are presented including: receiving the operation on a first database partition in a shared nothing parallelism system, where the operation is non-collocated, reference based operation; generating a correlation sequence, where the correlation sequence includes a sequence of references pointing to input data required for the operation; receiving one of the references on a first table queue operator on a second database partition, where the second database partition includes input data corresponding with the received reference, and where the table queue operator is configured for providing communication between the first database partition and the second database partition; and processing the input data on the second database partition corresponding with the operation.

Evaluating reference based operations in shared nothing parallelism systems

Embodiments are included for methods, systems, and computer program products for evaluating operations in a shared nothing parallelism system using an electronic computing device are presented, the methods and computer program products including: causing the electronic computing device to receive the operation, where the operation is non-collocated, reference based operation, and where the operation is configured for execution on a first partition in the shared nothing parallelism system; causing the electronic computing device to insert a table queue operator on a second partition, where the second partition includes a reference to input data, causing the electronic computing device to place the reference to the input data on the first partition by the table queue operator; and causing the electronic computing device to execute the operation on the reference to the input data on the first partition.

Techniques are described for optimizing a multi-fact star schema query to retrieve data from two or more fact tables of a database. The optimization techniques may include internally transforming a received multi-fact star schema query into a group of single-fact sub-queries, thereby reducing or eliminating certain constraints during query processing. The group of sub-queries may be enumerated to determine a query execution plan. The multi-fact star schema query may be executed according to the query execution plan to retrieve the data from the two or more fact tables of the database.

Multi-fact query processing in data processing system

Methods and apparatus, including computer program products, implementing and using techniques for processing a federated query in a federated database system. A federated query is received at a federated database server. A federated query execution plan is generated based on the received federated query. The federated query execution plan defines one or more source servers of the federated database and a unique subquery to be executed on each of the source servers. The subqueries are distributed to the source servers in accordance with the federated query execution plan. The respective subqueries are executed asynchronously at the source servers. The subquery results are passed to a first designated source server defined in the federated query execution plan. The subquery results are joined and aggregated at the first designated source server into a final query result. The final query result is returned to the federated database server.

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Campbell, CA, United States of America

Anjali Betawadkar-Norwood