OmniRuntime consists of a series of features provided by Kunpeng BoostKit for Big Data in terms of application acceleration. It aims to improve the performance of end-to-end data loading, computing, and exchange through plugins, thereby improving the performance of big data analytics.
OmniRuntime includes the following features: operator pushdown (OmniData), operator acceleration (OmniOperator), shuffle acceleration (OmniShuffle), and materialized view (OmniMV). In the data loading phase, OmniData implements near-data computing to reduce network data traffic. In the data computing phase, OmniOperator replaces native Java operators with high-performance native operators to improve operator execution efficiency. In the data exchange phase, OmniShuffle accelerates data interaction between nodes. In addition, for scenarios where repeated queries or subqueries exist, OmniMV identifies the optimal materialized view through AI algorithms, reducing the overhead of repeated subqueries and thus improving query efficiency.
OmniMV does not have updates in this version of BoostKit. For details, see Kunpeng BoostKit 23.0.RC2 OmniRuntime Feature Guide.
