The graph algorithm library running on Kunpeng processors is an acceleration library that provides a rich set of high-level tools for graph algorithms. It is developed based on original APIs of Apache Spark 3.3.1. The acceleration library greatly improves the computing power in big data scenarios. Additionally, it provides multiple APIs in addition to the original APIs if the Apache Spark graph library.
The library provides 4 graph algorithms: maximal clique enumeration (MCE), Multiple Source shortest path(MSSP), PageRank and Betweenness. You can find the latest documentation on the project web page. This README file contains only basic setup instructions.
cd Spark-graph-algo-lib/
mvn package
Obtain "boostkit-graph-acc_2.12-3.0.0-spark3.3.1.jar" from the "Spark-graph-algo-lib/graph-accelerator/target/" directory
Obtain "boostkit-graph-core_2.12-3.0.0-Spark3.3.1.jar" from the "Spark-graph-algo-lib/graph-core/target/" directory
Obtain "boostkit-graph-kernel-clinet_2.12-3.0.0-Spark3.3.1.jar" from the "Spark-graph-algo-lib/graph-kernel/target/" directory
Track the bugs and feature requests via GitHub issues.
For further assistance, send an email to kunpengcompute@huawei.com
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