Hive

Apache Hive is a data warehouse system for Hadoop that facilitates easy data summarization, ad-hoc queries, and the analysis of large datasets. Its one of the more popular SQL on Hadoop tools and is a key platform component used for data analysis.

Features

• Scalable, extensible and designed for OLAP

• Stores schema in a database and data into HDFS

• Provides SQL dialect (HQL) for querying data

• Supports analysis of large data sets

Overview

Hive is used mainly as a data analysis tool. It provides a SQL-like database query interface called HQL for data stored in HDFS. The tables in Hive are similar to tables in a relational database. Databases are made of tables, which are made up of partitions.

Data sets are defined through tables (that expose type information) in which data can be loaded, selected and transformed through built-in operators or custom/user defined functions (UDFs). Data in the tables is serialized and each table has a corresponding Hadoop Distributed File System (HDFS) directory. Each table can be further subdivided into partitions that determine how data is distributed within sub-directories of the table directory. Data within partitions can be further broken down into buckets.

Hive supports common primitive data formats - BIGINT, BINARY, BOOLEAN, CHAR, DECIMAL, DOUBLE, FLOAT, INT, SMALLINT, STRING, TIMESTAMP, and TINYINT. In addition, primitive data types can be combined to form complex data types, such as structs, maps and arrays.

For additional details, visit the Apache HIVE website