BigData SQL Hive | | Software Development

BigData SQL Hive
This training is aimed at developers and covers the full stack of technical features, architecture and performance tuning. Apache Hive supports analysis of large datasets stored in Hadoop's HDFS and compatible file systems and it provides an SQL-like language with schema on read and transparently converts queries to map/reduce.
8 hours
Online
English
EAS-016
BigData SQL Hive
Sign Up
Duration
8 hours
Location
Online
Language
English
Code
EAS-016
Schedule and prices
€ 300 *
Training for 7-8 or more people? Customize trainings for your specific needs
BigData SQL Hive
Sign Up
Duration
8 hours
Location
Online
Language
English
Code
EAS-016
Schedule and prices
€ 300 *
Training for 7-8 or more people? Customize trainings for your specific needs

Description

This training is aimed at developers and covers the full stack of technical features, architecture and performance tuning. Apache Hive supports analysis of large datasets stored in Hadoop's HDFS and compatible file systems and it provides an SQL-like language with schema on read and transparently converts queries to map/reduce. Other features of Hive include:

  • Indexing to provide acceleration
  • Different storage types such as plain text, RCFile, HBase, ORC, and others.
  • Metadata storage in an RDBMS
  • Operating on compressed data stored into the Hadoop ecosystem
  • Built-in user defined functions (UDFs) to manipulate dates, strings, and other data-mining tools
  • SQL-like queries (HiveQL), which are implicitly converted into MapReduce
After completing the course, a certificate
is issued on the Luxoft Training form

Objectives

  • Developing expertise in the area of Big Data
  • Data modal design in Hive
  • Developing HSQL scripts
  • Practical experience in HSQL queries and performance tuning

Target Audience

  • Developers
  • QA
  • Analysts

Prerequisites

  • Hadoop fundamentals
  • ANSI SQL 92

Roadmap

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  • What is Hive
  • Architecture
  • Hive Authorization Options
  • Transactions
  • Data Types
  • “Select” Queries
  • DML / Export / Import
  • Hive UDFs types
  • Indexes
  • Windowing and Analytics Functions
  • Performance tuning
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