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IBM Open Platform with Apache Hadoop

  • Tuition USD $1,550 GSA  $1,198.99
  • Reviews star_rate star_rate star_rate star_rate star_half 2346 Ratings
  • Course Code DW606G
  • Duration 2 days
  • Available Formats Classroom
This course is available in other formats
Self-Paced
IBM Open Platform with Apache Hadoop (BigInsights V4.0) - SPVC (2W606G-SPVC)

IBM Open Platform (IOP) with Apache Hadoop is the first premiere collaborative platform to enable Big Data solutions to be developed on the common set of Apache Hadoop technologies. The Open Data Platform initiative (ODP) is a shared industry effort focused on promoting and advancing the state of Apache Hadoop and Big Data technologies for the enterprise. The current ecosystem is challenged and slowed by fragmented and duplicated efforts between different groups. The ODP Core will take the guesswork out of the process and accelerate many use cases by running on a common platform. It allows enterprises to focus on building business driven applications.

This module provides an in-depth introduction to the main components of the ODP core --namely Apache Hadoop (inclusive of HDFS, YARN, and MapReduce) and Apache Ambari -- as well as providing a treatment of the main open-source components that are generally made available with the ODP core in a production Hadoop cluster.

Skills Gained

  • List and describe the major components of the open-source Apache Hadoop stack and the approach taken by the Open Data Foundation.
  • Manage and monitor Hadoop clusters with Apache Ambari and related components
  • Explore the Hadoop Distributed File System (HDFS) by running Hadoop commands.
  • Understand the differences between Hadoop 1 (with MapReduce 1) and Hadoop 2 (with YARN and MapReduce 2).
  • Create and run basic MapReduce jobs using command line.
  • Explain how Spark integrates into the Hadoop ecosystem.
  • Execute iterative algorithms using Spark's RDD.
  • Explain the role of coordination, management, and governance in the Hadoop ecosystem using Apache Zookeeper, Apache Slider, and Apache Knox.
  • Explore common methods for performing data movement
    • Configure Flume for data loading of log files
    • Move data into the HDFS from relational databases using Sqoop
  • Understand when to use various data storage formats (flat files, CSV/delimited, Avro/Sequence files, Parquet, etc.).
  • Review the differences between the available open-source programming languages typically used with Hadoop (Pig, Hive) and for Data Science (Python, R)
  • Query data from Hive.
  • Perform random access on data stored in HBase.
  • Explore advanced concepts, including Oozie and Solr

Who Can Benefit

This intermediate training course is for those who want a foundation of IBM BigInsights. This includes: Big data engineers, data scientist, developers or programmers, administrators who are interested in learning about IBM's Open Platform with Apache Hadoop.

Prerequisites

None, however, knowledge of Linux would be beneficial.

Course Details

Unit 1: IBM Open Platform with Apache Hadoop

  • Exercise 1: Exploring the HDFS

Unit 2: Apache Ambari

  • Exercise 2: Managing Hadoop clusters with Apache Ambari

Unit 3: Hadoop Distributed File System

  • Exercise 3: File access and basic commands with HDFS

Unit 4: MapReduce and Yarn

  • Topic 1: Introduction to MapReduce based on MR1
  • Topic 2: Limitations of MR1
  • Topic 3: YARN and MR2
  • Exercise 4: Creating and coding a simple MapReduce job
  • Possibly a more complex second Exercise

Unit 5: Apache Spark

  • Exercise 5: Working with Spark's RDD to a Spark job

Unit 6: Coordination, management, and governance

  • Exercise 6: Apache ZooKeeper, Apache Slider, Apache Knox

Unit 7: Data Movement

  • Exercise 7: Moving data into Hadoop with Flume and Sqoop

Unit 8: Storing and Accessing Data

  • Topic 1: Representing Data: CSV, XML, JSON, and YAML
  • Topic 2: Open Source Programming Languages: Pig, Hive, and Other [R, Python, etc]
  • Topic 3: NoSQL Concepts
  • Topic 4: Accessing Hadoop data using Hive
  • Exercise 8: Performing CRUD operations using the HBase shell
  • Topic 5: Querying Hadoop data using Hive
  • Exercise 9: Using Hive to Access Hadoop / HBase Data

Unit 9: Advanced Topics

  • Topic 1: Controlling job workflows with Oozie
  • Topic 2: Search using Apache Solr
  • No lab exercises

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

Does ExitCertified deliver group training?

Yes, we provide training for groups, individuals, and private on sites. View our group training page for more information.

The courses are very in-depth and useful to get a good idea of everything and get going from there.

Excellent remote class environment and it was a good experience of remote learning.

I really admired his coaching skills and mannerisms and he gave many examples when I asked questions.

Very good course materials. Maybe could have included a bit more on something like FPO but otherwise very good. Very good instructor and environment.

The course was informative and easy to follow, but only skims the surface of the AWS services and usages.

0 options available

There are currently no scheduled dates for this course. If you are interested in this course, request a course date with the links above. We can also contact you when the course is scheduled in your area.

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