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Designing and Building Big Data Applications

Designing and Building Big Data Applications

  • 30 Day Money Back Guarantee
  • Completion Certificate
  • 24/7 Technical Support

Highlights

  • Delivered Online

  • 4 days

  • All levels

Description

Duration

4 Days

24 CPD hours

This course is intended for

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

Overview

Skills learned in this course include:Creating a data set with Kite SDKDeveloping custom Flume components for data ingestionManaging a multi-stage workflow with OozieAnalyzing data with CrunchWriting user-defined functions for Hive and ImpalaWriting user-defined functions for Hive and ImpalaIndexing data with Cloudera Search

Cloudera University?s four-day course for designing and building Big Data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH).

IntroductionApplication Architecture

  • Scenario Explanation

  • Understanding the Development Environment

  • Identifying and Collecting Input Data

  • Selecting Tools for Data Processing and Analysis

  • Presenting Results to the Use

Defining & Using Datasets

  • Metadata Management

  • What is Apache Avro?

  • Avro Schemas

  • Avro Schema Evolution

  • Selecting a File Format

  • Performance Considerations

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

Importing Relational Data with Apache Sqoop

  • What is Apache Sqoop?

  • Basic Imports

  • Limiting Results

  • Improving Sqoop?s Performance

  • Sqoop 2

Capturing Data with Apache Flume

  • What is Apache Flume?

  • Basic Flume Architecture

  • Flume Sources

  • Flume Sinks

  • Flume Configuration

  • Logging Application Events to Hadoop

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

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

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

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

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

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

Understanding Cloudera Search

  • What is Cloudera Search?

  • Search Architecture

  • Supported Document Formats

Indexing Data with Cloudera Search

  • Collection and Schema Management

  • Morphlines

  • Indexing Data in Batch Mode

  • Indexing Data in Near Real Time

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

About The Provider

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