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Apache Hive can be used to analyze large data sets stored in the Hadoop Distributed File System (HDFS) and linked file systems like Amazon S3. Querying, agglomerating data, and analysis are the three main functions of Hive. Declarative SQL-like language HiveQL accepts queries and converts them to Spark Jobs, MapReduce, and Apache Tez with ease. All three of the execution engines are operational in Hadoop YARN. It provides indexes, most notably bitmap indexes, which are believed to assist with queries and work well with low cardinality columns. Several storage formats, including plain text, RC Files, and HBase, are among the additional features offered by Hive. The experts providing Apache Hive assignment help online maintain current versions of all the previously stated Apache Hive components.
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