Designing and Building Big Data Applications

Price
$3,295.00
Duration
 4 Days
Delivery Methods
 VILT    Private Group
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This four-day course prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH).

 

Upcoming Class Dates and Times

This class is not currently scheduled.
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Who Should Attend

This course is best suited to developers, engineers, and architects who want to use use Hadoop and related tools to solve real-world problems.

Course Objectives

    Skills learned in this course include: Creating a data set with Kite SDK Developing custom Flume components for data ingestion Managing a multi-stage workflow with Oozie Analyzing data with Crunch Writing user-defined functions for Hive and Impala Writing user-defined functions for Hive and Impala Indexing data with Cloudera Search

Agenda

1 - Application Architecture
  • Scenario Explanation
  • Understanding the Development Environment
  • Identifying and Collecting Input Data
  • Selecting Tools for Data Processing and Analysis
  • Presenting Results to the User
2 - Defining and Using Data Sets
  • Metadata Management
  • What is Apache Avro?
  • Avro Schemas
  • Avro Schema Evolution
  • Selecting a File Format
  • Performance Considerations
3 - Using the Kite SDK Data Module
  • What is the Kite SDK?
  • Fundamental Data Module Concepts
  • Creating New Data Sets Using the Kite SDK
  • Loading, Accessing, and Deleting a Data Set
4 - Importing Relational Data with Apache Sqoop
  • What is Apache Sqoop?
  • Basic Imports
  • Limiting Results
  • Improving Sqoop's Performance
  • Sqoop 2
5 - Capturing Data with Apache Flume
  • What is Apache Flume?
  • Basic Flume Architecture
  • Flume Sources
  • Flume Sinks
  • Flume Configuration
  • Logging Application Events to Hadoop
6 - Developing Custom Flume Components
  • Flume Data Flow and Common Extension Points
  • Custom Flume Sources
  • Developing a Flume Pollable Source
  • Developing a Flume Event-Driven Source
  • Custom Flume Interceptors
  • Developing a Header-Modifying Flume Interceptor
  • Developing a Filtering Flume Interceptor
  • Writing Avro Objects with a Custom Flume Interceptor
7 - Managing Workflows with Apache Oozie
  • The Need for Workflow Management
  • What is Apache Oozie?
  • Defining an Oozie Workflow
  • Validation, Packaging, and Deployment
  • Running and Tracking Workflows Using the CLI
  • Hue UI for Oozie
8 - Processing Data Pipelines with Apache Crunch
  • What is Apache Crunch?
  • Understanding the Crunch Pipeline
  • Comparing Crunch to Java MapReduce
  • Working with Crunch Projects
  • Reading and Writing Data in Crunch
  • Data Collection API
  • Functions
  • Utility Classes in the Crunch API
9 - Working with Tables in Apache Hive
  • What is Apache Hive?
  • Accessing Hive
  • Basic Query Syntax
  • Creating and Populating Hive Tables
  • How Hive Reads Data
  • Using the RegexSerDe in Hive
10 - Developing User-Defined Functions
  • What are User-Defined Functions?
  • Implementing a User-Defined Function
  • Deploying Custom Libraries in Hive
  • Registering a User-Defined Function in Hive
11 - Executing Interactive Queries with Impala
  • What is Impala?
  • Comparing Hive to Impala
  • Running Queries in Impala
  • Support for User-Defined Functions
  • Data and Metadata Management
12 - Understanding Cloudera Search
  • What is Cloudera Search?
  • Search Architecture
  • Supported Document Formats
13 - Indexing Data with Cloudera Search
  • Collection and Schema Management
  • Morphlines
  • Indexing Data in Batch Mode
  • Indexing Data in Near Real Time
14 - Presenting Results to Users
  • Solr Query Syntax
  • Building a Search UI with Hue
  • Accessing Impala through JDBC
  • Powering a Custom Web Application with Impala and Search
 

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