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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.

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[su_tab title = “Program Structure”]

• 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.

Fees:

Free

Duration:

5 hours

Part Time/Full Time:

Part Time

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[su_tab title = “Eligibility”]

• Basic understanding of Apache Hadoop and BigData.
• Working knowledge of SQL
• Basic Linux Operating System knowledge

• Hadoop Fundamentals I Version 2

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[su_tab title =”Tools”]

• Hive
• Hadoop
• SQL
• Apache Hadoop
• MapReduce

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[su_tab title = “Contact”]

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