We present a scheme for parallel execution of SQL queries on top of any vertex-centric BSP graph processing engine. The scheme comprises a graph encoding of relational instances and a vertex program specification of our algorithm called TAG-join, which matches the theoretical communication and computation complexity of state-of-the-art join algorithms. When run on top of the vertex-centric TigerGraph database engine on a single multi-core server, TAG-join exploits thread parallelism and is competitive with (and often outperforms) reference RDBMSs on the TPC benchmarks they are traditionally tuned for. In a distributed cluster, TAG-join outperforms the popular Spark SQL engine.
翻译:在任何顶端中心 BSP 图形处理引擎之上,我们提出了一个平行执行 SQL 查询的计划。 这个计划包括关系实例的图形编码和我们的算法的顶点程序规格TAG-join, 它与最新联合算法的理论通信和计算复杂性相匹配。 当运行在单个多核心服务器的顶端以顶端为顶端的顶端的顶端, TAG-join 开发了线性平行关系, 并且与( 并且往往超过) TPC 基准上的参考 RDBMS 具有竞争力。 在分布式组中, TAG- join 超越了流行的 Spoint SQL 引擎 。