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Processing performance on Apache Pig, Apache Hive and MySQL cluster

机译:在Apache Pig,Apache Hive和MySQL集群上的处理性能

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MySQL Cluster is a famous clustered database that is used to store and manipulate data. The problem with MySQL Cluster is that as the data grows larger, the time required to process the data increases and additional resources may be needed. With Hadoop and Hive and Pig, processing time can be faster than MySQL Cluster. In this paper, three data testers with the same data model will run simple queries and to find out at how many rows Hive or Pig is faster than MySQL Cluster. The data model taken from GroupLens Research Project [12] showed a result that Hive is the most appropriate for this data model in a low-cost hardware environment.
机译:MySQL Cluster是一个著名的集群数据库,用于存储和处理数据。 MySQL Cluster的问题在于,随着数据的增长,处理数据所需的时间也会增加,并且可能需要额外的资源。使用Hadoop,Hive和Pig,处理时间可以比MySQL Cluster更快。在本文中,三个具有相同数据模型的数据测试人员将运行简单的查询,并找出Hive或Pig的行数比MySQL Cluster快多少行。来自GroupLens研究项目[12]的数据模型表明,在低成本的硬件环境中,Hive最适合此数据模型。

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