Data Repository with Sqoop


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level


Overview/Description
Hadoop is an open-source software framework for storing and processing big data in a distributed fashion on large clusters of commodity hardware. Essentially, it accomplishes two tasks: massive data storage and faster processing. This course explains the theory of Sqoop as a tool for dealing with extraction and loading of structured data from a RDBMS. You'll explore an explanation of Hive SQL statements and a demonstration of Hive in action. This learning path can be used as part of the preparation for the Cloudera Certified Administrator for Apache Hadoop (CCA-500) exam.

Target Audience
Technical personnel with a background in Linux, SQL, and programming who intend to join a Hadoop Engineering team in roles such as Hadoop developer, data architect, or data engineer or roles related to technical project management, cluster operations, or data analysis

Prerequisites
None

Expected Duration (hours)
1.4

Lesson Objectives

Data Repository with Sqoop

  • start the course
  • describe MySQL
  • install MySQL
  • create a database in MySQL
  • create MySQL tables and load data
  • describe Sqoop
  • describe Sqoop's architecture
  • recall the dependencies for Sqoop installation
  • install Sqoop
  • recall why it's important for the primary key to be numeric
  • perform a Sqoop import from MySQL into HDFS
  • recall what concerns the developers should be aware of
  • perform a Sqoop export from HDFS into MySQL
  • recall that you must execute a Sqoop import statement for each data element
  • perform a Sqoop import from MySQL into HBase
  • recall how to use chain troubleshooting to resolve Sqoop issues
  • use the log files to identify common Sqoop errors and their resolutions
  • to use Sqoop to extract data from a RDBMS and load the data into HDFS

    • Course Number:
    df_ahec_a05_it_enus

    Expertise Level
    Intermediate