Taming the Expressiveness and Programmability of Graph Analytical Queries
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Graph database has enjoyed a boom in the last decade, and graph queries accordingly gain a lot of attentions from both the academia and industry. We focus on analytical queries in this paper. While analyzing existing domain-specific languages (DSLs) for analytical queries regarding the perspectives of completeness, expressiveness and programmability, we find out that none of existing work has achieved a satisfactory coverage of these perspectives. Motivated by this, we propose the DSL, which is named after the three primitive operators Filter, LocAl and PuSH. We prove that is Turing complete (completeness), and show that it achieves both good expressiveness and programmability for analytical queries. We provide an implementation of based on code generation, and compare it with native C++ codes and existing DSL using representative queries. The experiment results demonstrate 's expressiveness, and its capability of programming complex algorithms that achieve satisfactory runtime.
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