Modern big data applications usually involve heterogeneous data sources and analytical functions, leading to increasing demand for polystore systems, especially analytical polystore systems. This paper presents AWESOME system along with a domain-specific language ADIL. ADIL is a powerful language which supports 1) native heterogeneous data models such as Corpus, Graph, and Relation; 2) a rich set of analytical functions; and 3) clear and rigorous semantics. AWESOME is an efficient tri-store middle-ware which 1) is built on the top of three heterogeneous DBMSs (Postgres, Solr, and Neo4j) and is easy to be extended to incorporate other systems; 2) supports the in-memory query engines and is equipped with analytical capability; 3) applies a cost model to efficiently execute workloads written in ADIL; 4) fully exploits machine resources to improve scalability. A set of experiments on real workloads demonstrate the capability, efficiency, and scalability of AWESOME.
翻译:现代大数据应用通常涉及多种数据来源和分析功能,导致对多层系统的需求增加,特别是分析多层系统,本文介绍了AWESOME系统以及一个特定域语言ADIL。ADIL是一种强大的语言,支持:(1) 本地多层数据模型,如Corpus、Great和Relation;(2) 一套丰富的分析功能;(3) 清晰而严格的语义。AWESOME是一个高效的三层中继器,1)建在三个不同DBMS系统(Postgres、Solr和Neo4j)的顶部,易于扩展,以纳入其他系统;(2) 支持模拟查询引擎,并配备分析能力;(3) 应用成本模型,高效率地完成ADIL中写的工作量;(4) 充分利用机器资源提高可缩放性。一套关于实际工作量的实验表明AWESOME的能力、效率和可缩放性。