what does apache hive do?
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Apache Hive is an open source data warehouse software for reading, writing and managing large data set files that are stored directly in either the Apache Hadoop Distributed File System (HDFS) or other data storage systems such as Apache HBase.
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Apache Spark is an open-source distributed general-purpose cluster-computing framework. ... Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since.
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['Integral Types (TINYINT, SMALLINT, INT/INTEGER, BIGINT)', '1.2.2.', 'Strings.', 'Varchar.', 'Char.', 'Timestamps. Casting Dates.', 'Intervals.', 'Decimals. Decimal Literals. Decimal Type Incompatibilities between Hive 0.12.0 and 0.13.0. Upgrading Pre-Hive 0.13.0 Decimal Columns.']
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***Hive Prefab no longer seems to be in business. ... *** Hive Modular designs high-end modern modular homes. Hive's architects have created a number of prefab home designs that can be used as a “starting point” for individual customization or Hive can work with the client to create a fully custom design.
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Apache Hadoop has two core components such as HDFS and the MapReduce parallel processing. Both of these are inspired by the technologies created inside Google. Apache Hadoop's HDFS was inspired by Google File Systems and Hadoop's MapReduce was inspired by Google's MapReduce.
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Embedded Metastore: By default Derby database is there which supports one one user, so only one shell you can open. ... In Local mode, the Hive metastore service runs in the same process as the main HiveServer process, but the metastore database runs in a separate process, and can be on a separate host.
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User Defined Functions, also known as UDF, allow you to create custom functions to process records or groups of records. Hive comes with a comprehensive library of functions. There are however some omissions, and some specific cases for which UDFs are the solution.
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Hive embeds Tez so that it can translate complex SQL statements into highly optimized, purpose-built data processing graphs that strike the right balance between performance, throughput, and scalability.
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Sqoop distributes the input data among the mappers equally to get high performance. Then each mapper creates connection with the database using JDBC and fetches the part of data assigned by Sqoop and writes it into HDFS or Hive or HBase based on the option provided in the command line.
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Apache HBase is built on top of Hadoop for its MapReduce and distributed file system implementation. All these projects are open-source and part of the Apache Software Foundation. ... However, being developed in Java, both projects are fully portable across platforms and, hence, also to the Windows operating system.
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Azure HDInsight is a managed Apache Hadoop service that lets you run Apache Spark, Apache Hive, Apache Kafka, Apache HBase, and more in the cloud.
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The MSCK REPAIR TABLE command scans a file system such as Amazon S3 for Hive compatible partitions that were added to or removed from the file system after the table was created. ... To update the metadata, you run MSCK REPAIR TABLE on the table. This enables you to query the data in the new partitions from Athena.
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Partitioned Tables: Hive supports table partitioning as a means of separating data for faster writes and queries. Partitions are independent of ACID. Large tables in Hive are almost always partitioned. Large ACID tables should be partitioned for optimal performance.
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['$ cat /app/hadoop/workspace/horf/hql_in_spark.hql.', 'Now Enter this Launch Command in your shell:']
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Apache Airflow is an open-source Python-based workflow automation tool used for setting up and maintaining data pipelines. An important thing to remember here is that Airflow isn't an ETL tool. Instead, it helps you manage, structure, and organize your ETL pipelines using Directed Acyclic Graphs (DAGs).
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Reload Apache You need to reload or restart Apache whenever you make changes to its configuration. On reload, the main apache process shuts down the child processes, loads the new configuration, and starts new child processes.
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Perhaps the most influential and established tool for analyzing big data is known as Apache Hadoop. Apache Hadoop is a framework for storing and processing data at a large scale, and it is completely open source.