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Hadoop Programming on the Hortonworks Data Platform for Managers WA2622 - Course Book product photo Front View EL

Delivery Information:

You will receive required software set up for install 48 hours from time of purchase. 

Version 1.0

Product Type: Courseware
Level: Foundation
Duration: 2 Days
Prerequisites: 

Participants should have the general knowledge of programming.


Language: English (en-US)
Delivery Format: eBook

Delivery Information

Delivered as a voucher. You can access the vouchers and assign them from Active Vouchers on myLeapest or you can use Classes function to assign the vouchers to a group of learners.

Product Content

This product contains the following items. Upon purchasing, you will get access to all available version prior to the latest version.

Course Description :

Delivery Information:

You will receive required software set up for install 48 hours from time of purchase. 

Version 1.0


Course Outline :

Chapter 1.

  • MapReduce Overview
  • The Client – Server Processing Pattern
  • Distributed Computing Challenges
  • MapReduce Defined
  • Google's MapReduce
  • The Map Phase of MapReduce
  • The Reduce Phase of MapReduce
  • MapReduce Explained
  • MapReduce Word Count Job
  • MapReduce Shared-Nothing Architecture
  • Similarity with SQL Aggregation Operations
  • Example of Map & Reduce Operations using JavaScript
  • Problems Suitable for Solving with MapReduce
  • Typical MapReduce Jobs
  • Fault-tolerance of MapReduce
  • Distributed Computing Economics
  • MapReduce Systems
  • Summary


Chapter 2.

  • Hadoop Overview
  • Apache Hadoop
  • Apache Hadoop Logo
  • Typical Hadoop Applications
  • Hadoop Clusters
  • Hadoop Design Principles
  • Hadoop Versions
  • Hadoop's Main Components
  • Hadoop Simple Definition
  • Side-by-Side Comparison: Hadoop 1 and Hadoop 2
  • Hadoop-based Systems for Data Analysis
  • Other Hadoop Ecosystem Projects
  • Hadoop Caveats
  • Hadoop Distributions
  • Cloudera Distribution of Hadoop (CDH)
  • Cloudera Distributions
  • Hortonworks Data Platform (HDP)
  • MapR
  • Summary


Chapter 3.

  • Hadoop Distributed File System Overview
  • Hadoop Distributed File System (HDFS)
  • HDFS High Availability
  • HDFS 'Fine Print'Storing
  • Raw Data in HDFS
  • Hadoop Security
  • HDFS Rack-awareness
  • Data Blocks
  • Data Block Replication Example
  • HDFS Name
  • Node Directory Diagram
  • Accessing HDFS
  • Examples of HDFS Commands
  • Other Supported File Systems
  • WebHDFS
  • Examples of WebHDFS Calls
  • Client Interactions with HDFS for the Read Operation
  • Read Operation Sequence Diagram
  • Client Interactions with HDFS for the Write Operation
  • Communication inside HDFS
  • Summary


Chapter 4.

  • Apache Pig Scripting Platform
  • What is Pig?Pig Latin
  • Apache Pig Logo
  • Pig Execution Modes
  • Local Execution Mode
  • MapReduce Execution Mode
  • Running Pig
  • Running Pig in Batch Mode
  • What is Grunt?Pig Latin Statements
  • Pig Programs
  • Pig Latin Script Example
  • SQL Equivalent
  • Differences between Pig and SQL
  • Statement Processing in Pig
  • Comments in Pig
  • Supported Simple Data Types
  • Supported Complex Data Types
  • Arrays
  • Defining Relation's Schema
  • Not Matching the Defined Schema
  • The bytearray Generic Type
  • Using Field Delimiters
  • Loading Data with Text
  • Loader()Referencing Fields in Relations
  • Summary


Chapter 5.

  • Apache Pig HDFS Interface
  • The HDFS InterfaceFS
  • Shell Commands (Short List)
  • Grunt's Old File System Commands
  • Summary


Chapter 6.

  • Apache Pig Relational and Eval Operators
  • Pig Relational Operators
  • Example of Using the JOIN Operator
  • Example of Using the Order By Operator
  • Caveats of Using Relational Operators
  • Pig Eval Functions
  • Caveats of Using Eval Functions (Operators)
  • Example of Using Single-column Eval Operations
  • Example of Using Eval Operators For Global Operations
  • Summary


Chapter 7.

  • HiveWhat is Hive?
  • Apache Hive Logo
  • Hive's Value Proposition
  • Who uses Hive?Hive's Main Sub-Systems
  • Hive Features
  • The 'Classic' Hive Architecture
  • The New Hive Architecture
  • HiveQL
  • Where are the Hive Tables Located?
  • Hive Command-line Interface (CLI)
  • The Beeline Command Shell
  • Summary


Chapter 8.

  • Hive Command-line Interface
  • Hive Command-line Interface (CLI)
  • The Hive Interactive Shell
  • Running Host OS Commands from the Hive Shell
  • Interfacing with HDFS from the Hive Shell
  • The Hive in Unattended Mode
  • The Hive CLI Integration with the OS Shell
  • Executing HiveQL Scripts
  • Comments in Hive Scripts
  • Variables and Properties in Hive CLI
  • Setting Properties in CLI
  • Example of Setting Properties in CLI
  • Hive Namespaces
  • Using the SET Command
  • Setting Properties in the Shell
  • Setting Properties for the New Shell Session
  • Setting Alternative Hive Execution Engines
  • The Beeline Shell
  • Connecting to the Hive Server in Beeline
  • Beeline Command Switches
  • Beeline Internal Commands
  • Summary


Chapter 9.

  • Hive Data Definition Language
  • Hive Data Definition Language
  • Creating Databases in Hive
  • Using Databases
  • Creating Tables in Hive
  • Supported Data Type Categories
  • Common Numeric Types
  • String and Date / Time Types
  • Miscellaneous Types
  • Example of the CREATE TABLE Statement
  • Working with Complex Types
  • Table Partitioning
  • Table Partitioning
  • Table Partitioning on Multiple Columns
  • Viewing Table Partitions
  • Row Format
  • Data Serializers / Deserializers
  • File Format Storage
  • File Compression
  • More on File Formats
  • The ORC Data Format
  • Converting Text to ORC Data Format
  • The EXTERNAL DDL Parameter
  • Example of Using EXTERNAL
  • Creating an Empty Table
  • Dropping a Table
  • Table / Partition(s) Truncation
  • Alter Table/Partition/Column
  • Views
  • Create View Statement
  • Why Use Views?Restricting Amount of Viewable Data
  • Examples of Restricting Amount of Viewable Data
  • Creating and Dropping Indexes
  • Describing Data
  • Summary

Target Audience :

Managers, Business Analysts, and IT Architects.


Hadoop Programming on the Hortonworks Data Platform for Managers WA2622 - Course Book

VP00076643923046
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