About Apache Hive

The purpose of this course is to provide the participant with a solid understanding of Apache Hive, the open-source data warehouse infrastructure built on top of Hadoop. Hive handles petabytes of data, allowing analysis of large data sets and providing indexes to accelerate queries. It structures data and uses an SQL-like language called HiveQL.
An internal compiler translates HQL queries to MapReduce, Apache Tez, and Spark jobs. It uses different storage types, such as ORC, HBase, plain text, and others. It offers built-in user-defined functions to control data-mining tools like dates and strings. Hive is similar to relational databases in query language and storage, except it is structured differently. Apache Hive training program opens the door to Hadoop for those who do not know Java.

Apache Hive training program begins with instructions on installing and configuring Hive. It then moves on to the basic architecture and components of the Hive system, including the meta store, driver, query compiler, thrift server. It also describes the jobs that they perform. It discusses the Hive data units, buckets, partitions, tables, and databases.
It covers the various primitive and complex data types that Hive can handle. It goes into detailed explaining of how to work with tables, load data into them, write queries, insert data, and manage outputs. It then discusses the HQL language and its capabilities beyond SQL, providing examples to clarify the points that are made. It wraps things up with Hive UDFs.

Familiarity with Linux as well as SQL queries is recommended for the course. Basic knowledge of Core Java will also prove helpful in understanding how Hive works. The course does not have any formal prerequisites and registration is open to everyone.