Oracle International Corporation

Jarod Wen

Nipun Agarwal

Sam Idicula

Thomas Chang

Nitin Kunal

Farhan Tauheed

Shrikumar Hariharasubrahmanian

Gong Zhang

Michael Delorimier

Techniques are described for generating a map of operations to ingest external data. In an embodiment, DBMS receives a query schema that specifies an external data source and client-defined columns to arrange queried data from data fields of the external data source. DBMS generates an ingest schema for the queried data of the external data source such that the ingest schema specifies ingest data fields from the data fields of the external data source to be mapped to the one or more client-defined columns. Additionally, the DBMS identifies surplus data in the external data source, which has not been specified by the ingest schema and is different from the queried data defined by the client-requested query schema. The process not only ingests the ingest data fields from the external data source but also the surplus data from the external data source. In response to receiving a query according to a different query schema, DBMS generates a result set that based on the surplus data of the external data source. The result generation is based on the DBMS generating a map of operations, which when performed, generates a result set for the received query regardless whether the query is based on the different query schema.

Map of operations for ingesting external data

Techniques are provided for scheduling data operations for a given query based upon a query-cost model that analyzes the cost of scheduling data operations based upon their operation cost and the type of resources needed for the operation. In an embodiment, a database server receives a set of operations for a query. The database server determines a set of leaf operation nodes from the set of data operations, where the set of leaf operation nodes includes operation nodes that do not depend on the execution of other nodes within the set of data operations. The database server compares operation costs between the leaf operation nodes to determine which leaf operation node to insert into a scheduled order set. The database server inserts the leaf operation node into the scheduled order set. Then the database server iteratively determines new leaf operation nodes and performs cost analysis on remaining leaf operation nodes to generate a set of scheduled data operations.

Dynamic operation scheduling for distributed data processing

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Hollis, NH, United States of America

Jarod Wen