Change Description
The OmniOperator operator acceleration feature of 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 memory for OmniOperator to support big wide table queries. The optimizations cover aggregate state memory usage, HashAggregator serialization memory usage, unified aggregator and operator memory allocation, and HashAggregator Spill sorting.
- Added the Not expression and the AnsiCast expression in the Spark inset scenario.
- Added support for the Hive engine. No exception occurs when Hive Extension executes 99 TPC-DS SQL statements. When vectorization is enabled, the performance for the ORC format is improved by 20% compared with that of the native Hive engine.
- Added support for more operators in Hive Extension, including Filter, Select, GroupBy, MapJoin, MergeJoin, PTF, Sort and TableScan.
- Added security clusters for ORC files in Hive Extension.
Modified Features
None
Removed Features
None
Parent topic: V1.5.0