Abstract: A storage system communicatively coupled to a database management system (DBMS performs storage-side scanning of data sources that are not stored in native database storage format of the DBMS. Data sources for external tables are accessible in a storage system referred to as a distributed data access system (DDAS), e.g. a Hadoop Distributed File System. To execute a query that references an external table, a DBMS first generates an execution plan. The DDAS supplies the DBMS with information that specifies each portion of the data source, and specifies which data node to use to access the portion. The DBMS sends a request for each portion to the respective data node, requesting that the data node generate rows from data in the portion. The request may specify scanning criteria, specifying one or more columns to project and/or filter on, and code modules for the data node to execute to generate records.

Abstract: An approach, referred to herein as parallelized-external-table access, generates rows from a single external table in parallel for a given query. Under parallelized-external-table access, an execution plan generated for the query includes multiple work granules that generate rows for a single external table from a data source. Such work granules are referred to herein as external work granules. Each external work granule of the execution plan may be assigned to a slave process, which executes the external work granule in parallel with another slave process executing another external work granule. External tables are accessible on a cluster of data nodes in a distributed data access system (e.g. Hadoop Distributed File System) connected to a DBMS.

Abstract: A storage system communicatively coupled to a DBMS performs storage-side scanning of data sources that are not stored in the native database storage format of the DBMS. Data sources for external tables are accessible in a storage system referred to herein as a distributed data access system, e.g. a Hadoop Distributed File System. To execute a query that references an external table, a DBMS first generates an execution plan. The distributed data access system supplies the DBMS with information that specifies each portion of the data source, and specifies which data node to use to access the portion. The DBMS sends a request for each portion to the respective data node, the request requesting that the data node generate rows from data in the portion. The request may specify scanning criteria, specifying one or more columns to project and/or filter on. The request may also specify code modules for the data node to execute to generate rows or records and columns.

Abstract: An approach, referred to herein as parallelized-external-table access, generates rows from a single external table in parallel for a given query. Under parallelized-external-table access, an execution plan generated for the query includes multiple work granules that generate rows for a single external table from a data source. Such work granules are referred to herein as external work granules. Each external work granule of the execution plan may be assigned to a slave process, which executes the external work granule in parallel with another slave process executing another external work granule. External tables are accessible on a cluster of data nodes in a distributed data access system (e.g. Hadoop Distributed File System) connected to a DBMS.