When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
This IBM Self-Paced Virtual Class (SPVC) includes:
- PDF course guide available to attendee during and after course
- Lab environment where students can work through demonstrations and exercises at their own pace
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.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
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
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.
How do I find an ExitCertified training location?
We have training locations across the United States and Canada. View a full list of classroom training locations.
Which delivery formats are available?
At ExitCertified we offer training that is Instructor-Led, Online, Virtual and Self-Paced.
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.
Excellent facilities, excellent staff.. and the coffee is good too! Thanks for helping to advance my career and the career of my colleagues!
I took the AWS Technical Essentials and it was taught very well. It was very comprehensive and the instructor was fantastic. Already having familiarity with AWS, it was still taught at a level where I felt like it was worth taking before doing taking the AWS Developer course.
Well organized, but the training should have included lab times as well, labs won't be done during breaks.
very good... also gave relevant examples to our current business requirements.
Very good training. Remote mode makes it a little bit harder at the beginning. All went well after warm-up
