Hive Query Language Tutorial

In this video, we are going to discuss the basic Hive Queries.
hive queries in production.
Apache Hive helps with querying and managing large datasets real fast. It is an ETL tool for Hadoop ecosystem. In this tutorial, you will learn important topics of Hive like HQL queries, data extractions, partitions, buckets and so on.


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Hive is developed on top of Hadoop. It is a data warehouse framework for querying and analysis of data that is stored in HDFS. Hive is an open source-software that lets programmers analyze large data sets on Hadoop.

The size of data sets being collected and analyzed in the industry for business intelligence is growing and in a way, it is making traditional data warehousing solutions more expensive. Hadoop with MapReduce framework, is being used as an alternative solution for analyzing data sets with huge size. Though, Hadoop has proved useful for working on huge data sets, its MapReduce framework is very low level and it requires programmers to write custom programs which are hard to maintain and reuse. Hive comes here for rescue of programmers.

Hive evolved as a data warehousing solution built on top of Hadoop Map-Reduce framework.

Hive provides SQL-like declarative language, called HiveQL, which is used for expressing queries. Using Hive-QL users associated with SQL are able to perform data analysis very easily.

Hive engine compiles these queries into Map-Reduce jobs to be executed on Hadoop. In addition, custom Map-Reduce scripts can also be plugged into queries. Hive operates on data stored in tables which consists of primitive data types and collection data types like arrays and maps.

Hive comes with a command-line shell interface which can be used to create tables and execute queries.

Hive query language is similar to SQL wherein it supports subqueries. With Hive query language, it is possible to take a MapReduce joins across Hive tables. It has a support for simple SQL like functions- CONCAT, SUBSTR, ROUND etc., and aggregation functions- SUM, COUNT, MAX etc. It also supports GROUP BY and SORT BY clauses. It is also possible to write user defined functions in Hive query language.