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Writing map/reduce programs to analyze your Big Data can get complex. Hive can help make querying your data much easier. Apache Hive, first created at Facebook, is a data warehouse system for Hadoop that facilitates easy data summarization, ad-hoc queries, and the analysis of large datasets stored in Hadoop compatible file systems. Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL.

Course Syllabus:
  • Understand what Apache Hive is, the Hive architecture, and Hive use cases.
  • Make basic configuration changes in a Hive installation.
  • Use DDL to create new Hive databases and tables with a variety of different data types.
  • Create partitioned tables that are optimized for hadoop.
  • Create and run a variety of useful DML queries against Hive.
  • Use built in Hive operators and functions to get work done.
  • Create your own user defined functions in Hive.
  • Use a variety of different file formats and records formats with Hive.




5 hours

Part Time/Full Time:

Part Time

  • Basic understanding of Apache Hadoop and BigData.
  • Working knowledge of SQL
  • Basic Linux Operating System knowledge
  • Hadoop Fundamentals I Version 2
  • Hive
  • Hadoop
  • SQL
  • Apache Hadoop
  • MapReduce
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