Hadoop MapReduce v2 Cookbook.pdf

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What this book covers Chapter 1, Getting Hadoop Up and Running in a Cluster, explains how to install and run Hadoop both as a single node as well as a cluster. Chapter 2, Advanced HDFS, introduces a set of advanced HDFS operations that would be useful when performing large-scale data processing with Hadoop MapReduce as well as with non-MapReduce use cases. Chapter 3, Advanced Hadoop MapReduce Administration, explains how to change con gurations and security of a Hadoop installation and how to debug. Chapter 4, Developing Complex Hadoop MapReduce Applications, introduces you to several advanced Hadoop MapReduce features that will help you to develop highly customized, ef cient MapReduce applications. Chapter 5, Hadoop Ecosystem, introduces the other projects related to Hadoop such HBase, Hive, and Pig. Chapter 6, Analytics, explains how to calculate basic analytics using Hadoop. Chapter 7, Searching and Indexing, introduces you to several tools and techniques that you can use with Apache Hadoop to perform large-scale searching and indexing. Chapter 8, Classi cations, Recommendations, and Finding Relationships, explains how to implement complex algorithms such as classi cations, recommendations, and nding relationships using Hadoop. Chapter 9, Mass Text Data Processing, explains how to use Hadoop and Mahout to process large text datasets, and how to perform data preprocessing and loading operations using Hadoop. Chapter 10, Cloud Deployments: Using Hadoop on Clouds, explains how to use Amazon Elastic MapReduce (EMR) and Apache Whirr to deploy and execute Hadoop MapReduce, Pig, Hive, and HBase computations on cloud infrastructures.
Hadoop MapReduce v2 Cookbook Second edition www.it-ebooks.info Table of contents Hadoop mapreduce v2 Cookbook Second Edition Credits about the author Acknowledgments about the author about the reviewers www.Packtpub.com Support files, eBooks, discount offers, and more Why Subscribe? Free access for packt account holders Preface What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support Downloading the example code Errata piracy Questions 1. Getting Started with Hadoop v2 Introduction Hadoop Distributed File System-HDFS HadOOp YARN Hadoop mapreduce Hadoop installation modes Setting up Hadoop v2 on your local machine Getting ready www.it-ebooks.info How to do it,... How it works Writing a WordCount MapReduce application, bundling it, and running it using the Hadoop local mode Getting ready How to do it How it works There’ s more... See also Adding a combiner step to the Word Count MapReduce program How to do it How it works Theres more Setting Lp hDFs Getting ready how to do it See also Setting up Hadoop yarn in a distributed cluster environment using Hadoop v 2 Getting ready How to do it.. How it works ee also Setting up Hadoop ecosystem in a distributed cluster environment using a Hadoop distribution Getting ready How to do it There's more HDFS command-line file operations Getting read How to do it How it works There's more www.it-ebooks.info Running the word Count program in a distributed cluster environment Getting ready How to do it How it works There's more Benchmarking HDFS using DFSIO Getting ready How to do it How it works There's more.. Benchmarking Hadoop mapReduce using TeraSort Getting ready How to do it How it works 2. Cloud Deployments-Using Hadoop yarn on cloud Environments Introduction Running Hadoop MapReduce v2 computations using Amazon Elastic Map Reduce Getting ready How to do it See also Saving money using Amazon eC2 Spot Instances to execute EMR job flows How to do it ere s more See also Executing a Pig script using EMR How to do it There's more Starting a Pig interactive session Executing a Hive script using EMr How to do it There's more www.it-ebooks.info Starting a Hive interactive session oee aso Creating an Amazon EMR job flow using the AwS Command Line Interface Getting ready How to do it Theres more See also Deploying an apache hBase cluster on amazon eC2 using emr Getting ready How to do it See also Using emr bootstrap actions to configure VMs for the Amazon EMr jobs How to do it There's more Using apache Whit to deploy an apache hadoop cluster in a cloud environment How to do it How it works See also 3. Hadoop Essentials-Configurations, Unit Tests, and Other APIs Introduction Optimizing Hadoop YARN and Map Reduce configurations for cluster deployments Getting ready How to do it.. How it works Theres more Shared user hadoop clusters-using Fair and Capacity schedulers How to do it How it works There's more Setting classpath precedence to user-provided JARs How to do it www.it-ebooks.info How it works Speculative execution of straggling tasks How to do it Theres more Unit testing Hadoop mapReduce applications using MRUnit Getting ready How to do it See also Integration testing Hadoop MapReduce applications using Mini Yarn Cluster Getting ready How to do it See also Adding a new DataNode Getting ready How to do it There's more Rebalancing hdFs See also Decommissioning data nodes How to do it How it works . See also USing multiple disks/volumes and limiting HDES disk usage How to do it Setting the hdfs block size How to do it There's more Setting the file replication factor How to do it How it works www.it-ebooks.info There’ s more oee aso Using the hdFS Java API HI OW tO GO How it works There's more Configuring the File system obiect Retrieving the list of data blocks of a file 4. Developing Complex Hadoop MapReduce Applications Introduction Choosing appropriate Hadoop data types How to do it There's more See also Implementing a custom Hadoop Writable data type How to do it How it works There's more ee aIso Implementing a custom Hadoop key type How to do it.m How it works See also Emitting data of different value types from a Mapper How to do it How it works There's more Choosing a suitable Hadoop Input Format for your input data format How to do it How it works www.it-ebooks.info There’ s more oee aso Adding support for new input data formats-implementing a custom InputFormat HI OW tO GO How it works Theres more See also Formatting the results of map Reduce computations- using Hadoop Output Formats How to do it How it works. Theres more Writing multiple outputs from a Map Reduce computation How to do it How it works Using multiple input data types and multiple mapper implementations in a single maPreduce application See also Hadoop intermediate data partitioning How to do it How it works There’ s more.. TotalOrderPartitioner Key FieldBasedPartitioner Secondary sorting- sorting Reduce input values How to do it How it works See also Broadcasting and distributing shared resources to tasks in a MapReduce job-Hadool Distributed cache How to do it How it works There's more www.it-ebooks.info

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