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.
Cite
@article{arxiv.2103.14120,
title = {Vertex-centric Parallel Computation of SQL Queries},
author = {Ainur Smagulova and Alin Deutsch},
journal= {arXiv preprint arXiv:2103.14120},
year = {2021}
}
Comments
50 pages, LaTeX; added examples in Section 6.4; corrected figure in Section 8.6