Change Description
The OmniRuntime OmniOperator operator acceleration feature of the Kunpeng BoostKit for Big Data uses one base to support different engines (such as Spark), reducing repeated optimization work, fully exploring common and heterogeneous computing power, and promoting the Kunpeng ecosystem.
New Features
- Optimized the prerequisites of bloomFilter and subquery broadcast to improve the reuse of subqueries.
- Added support for the greatest/contains expression, and skips the rollback of the filter operators that contain a scalar subquery expression.
- Optimized acceleration for operators TableScan, HashJoin, Shuffle, and RollUp.
- Optimized the OmniOperator deployment method, in which the Yarn resource management model enables the OmniOperator binary software package on which the Spark Executor process depends to be automatically deployed.
Modified Features
None
Removed Features
None
Parent topic: V1.6.0