Vertex-centric Parallel Computation of SQL Queries
Pages 1664 - 1677
Abstract
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.
Supplementary Material
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. The algorithm matches the theoretical communication and computation complexity of the state-of-the-art parallel join algorithms. When run on top of the TigerGraph database engine, it is competitive with (and often outperforms) reference RDBMSs on the TPC benchmarks they are traditionally tuned for.
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Published In
June 2021
2969 pages
ISBN:9781450383431
DOI:10.1145/3448016
- General Chairs:
- Guoliang Li,
- Zhanhuai Li,
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- Divesh Srivastava
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Published: 18 June 2021
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