Cloudera Training for Apache HBase

Cloudera Training for Apache HBase Course Description

Duration: 3.00 days (24 hours)

This three-day training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second. Apache HBase is distributed, scalable, NoSQL database built on Apache Hadoop. HBase can store data in massive tables consisting of billions of rows and millions of columns, serve data to many users and applications in real time, and provide fast, random read/write access to users and applications.

Next Class Dates

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Intended Audience for this Cloudera Training for Apache HBase Course

  • » This course is appropriate for developers and administrators who intend to use HBase. Prior experience with databases and data modeling is helpful, but not required. Knowledge of Java is assumed. Prior knowledge of Hadoop is not required, but Cloudera Developer Training for Apache Hadoop provides an excellent foundation for this course.

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Cloudera Training for Apache HBase Course Objectives

  • » Use cases and usage occasions for HBase, Hadoop, and RDBMS
  • » Using the HBase shell to directly manipulate HBase tables
  • » Designing optimal HBase schemas for efficient data storage and recovery
  • » How to connect to HBase using the Java API to insert and retrieve data in real time
  • » Best practices for identifying and resolving performance bottlenecks

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Cloudera Training for Apache HBase Course Outline

      1. Introduction to Hadoop and HBase
        1. What Is Big Data?
        2. Introducing Hadoop
        3. Hadoop Components
        4. What Is HBase?
        5. Why Use HBase?
        6. Strengths of HBase
        7. HBase in Production
        8. Weaknesses of HBase
      2. HBase Tables
        1. HBase Concepts
        2. HBase Table Fundamentals
        3. Thinking About Table Design
      3. The HBase Shell
        1. Creating Tables with the HBase Shell
        2. Working with Tables
        3. Working with Table Data
      4. HBase Architecture Fundamentals
        1. HBase Regions
        2. HBase Cluster Architecture
        3. HBase and HDFS Data Locality
      5. HBase Schema Design
        1. General Design Considerations
        2. Application-Centric Design
        3. Designing HBase Row Keys
        4. Other HBase Table Features
      6. Basic Data Access with the HBase API
        1. Options to Access HBase Data
        2. Creating and Deleting HBase Tables
        3. Retrieving Data with Get
        4. Retrieving Data with Scan
        5. Inserting and Updating Data
        6. Deleting Data
      7. More Advanced HBase API Features
        1. Filtering Scans
        2. Best Practices
        3. HBase Coprocessors
      8. HBase on the Cluster
        1. How HBase Uses HDFS
        2. Compactions and Splits
      9. HBase Reads and Writes
        1. How HBase Writes Data
        2. How HBase Reads Data
        3. Block Caches for Reading
      10. HBase Performance Tuning
        1. Column Family Considerations
        2. Schema Design Considerations
        3. Configuring for Caching
        4. Dealing with Time Series and Sequential Data
        5. Pre-Splitting Regions
      11. HBase Administration and Cluster Management
        1. HBase Daemons
        2. ZooKeeper Considerations
        3. HBase High Availability
        4. Using the HBase Balancer
        5. Fixing Tables with hbck
        6. HBase Security
      12. HBase Replication and Backup
        1. HBase Replication
        2. HBase Backup
        3. MapReduce and HBase Clusters
      13. Using Hive and Impala with HBase
        1. Using Hive and Impala with HBase
      14. Appendix A: Accessing Data with Python and Thrift
        1. Thrift Usage
        2. Working with Tables
        3. Getting and Putting Data
        4. Scanning Data
        5. Deleting Data
        6. Counters
        7. Filters

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Do you have the right background for Cloudera Training for Apache HBase?

Skills Assessment

We ensure your success by asking all students to take a FREE Skill Assessment test. These short, instructor-written tests are an objective measure of your current skills that help us determine whether or not you will be able to meet your goals by attending this course at your current skill level. If we determine that you need additional preparation or training in order to gain the most value from this course, we will recommend cost-effective solutions that you can use to get ready for the course.

Our required skill-assessments ensure that:

  1. All students in the class are at a comparable skill level, so the class can run smoothly without beginners slowing down the class for everyone else.
  2. NetCom students enjoy one of the industry's highest success rates, and pass rates when a certification exam is involved.
  3. We stay committed to providing you real value. Again, your success is paramount; we will register you only if you have the skills to succeed.
This assessment is for your benefit and best taken without any preparation or reference materials, so your skills can be objectively measured.

Take your FREE Skill Assessment test »

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Award winning, world-class Instructors

Jose P.
Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University. He has a great skill set in analyzing data, specifically using Python and a variety of modules and libraries. He hopes to use his experience in teaching and data science to help other people learn the power of the Python programming language and its ability to analyze data, as well as present the data in clear and beautiful visualizations. He is the creator of some of most popular Python Udemy courses including "Learning Python for Data Analysis and Visualization" and "The Complete Python Bootcamp". With almost 30,000 enrollments Jose has been able to teach Python and its Data Science libraries to thousands of students. Jose is also a published author, having recently written "NumPy Succintly" for Syncfusion's series of e-books.

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