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The Pig Mix Benchmark on Pig, MapReduce, and HPCC Systems

机译:Pig,MapReduce和HPCC系统上的Pig混合基准

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Soon after Google published MapReduce, their paradigm for processing large amounts of data, the open-source world followed with the Hadoop ecosystem. Later on, Lexis Nexis, the company behind the world's largest database of legal documents, open-sourced its Big Data processing platform, called the High-Performance Computing Cluster (HPCC). This paper makes three contributions. First, we describe our additions and improvements to the Pig Mix benchmark, the set of queries originally written for Apache Pig, and the porting of Pig Mix to HPCC. Second, we compare the performance of queries written in Pig, Java MapReduce, and ECL. Last, we draw conclusions and issue recommendations for future system benchmarks and large-scale data-processing platforms.
机译:Google发布了MapReduce(用于处理大量数据的范例)后不久,开源世界紧随Hadoop生态系统之后。后来,全球最大法律文件数据库背后的公司Lexis Nexis将其大数据处理平台称为高性能计算集群(HPCC)开源。本文做出了三点贡献。首先,我们描述对Pig Mix基准的添加和改进,最初为Apache Pig编写的查询集以及Pig Mix向HPCC的移植。其次,我们比较用Pig,Java MapReduce和ECL编写的查询的性能。最后,我们得出结论并针对未来的系统基准测试和大规模数据处理平台提出建议。

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