description Apache Hive Overview
Apache Hive is an open source database tool designed for analyzing large datasets. It translates SQL-like queries into MapReduce jobs running on Hadoop clusters. This allows users – primarily data analysts and developers – to process and analyze big data efficiently using familiar query syntax without needing deep Hadoop expertise. It’s commonly used for building data warehouses and performing batch processing tasks.
help Apache Hive FAQ
Is Apache Hive a database or a query layer?
Apache Hive is open-source data warehouse software built around Apache Hadoop, rather than a traditional transactional database server. It lets analysts read, write, and manage large distributed datasets using SQL syntax. [Apache Hive introduction](https://hive.apache.org/docs/latest/introduction-to-apache-hive/)
Does Apache Hive still run queries with MapReduce?
Hive can execute queries through Hadoop MapReduce, Apache Tez, or Apache Spark, depending on the configured execution engine. The SQL statement stays at the Hive layer while the selected engine performs the distributed work. [Hive configuration properties](https://hive.apache.org/docs/latest/user/configuration-properties/)
What kind of data is Apache Hive built to analyze?
Hive can query files in HDFS and can also work with other storage systems such as Apache HBase. That makes it useful for large-scale ETL, reporting, and analysis, but less suited to low-latency app transactions. [Apache Hive introduction](https://hive.apache.org/docs/latest/introduction-to-apache-hive/)
How can I run an Apache Hive query from a terminal?
HiveServer2 prepares a physical plan and submits work to MapReduce, Tez, or Spark on the cluster. Beeline can connect as a JDBC command-line client, while applications can use HiveServer2 client interfaces. [HiveServer2 overview](https://hive.apache.org/docs/latest/user/hiveserver2-overview/)
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