了得網計算機/網絡_Hadoop MapReduce v2參考手冊第2版（影印版）

	[ 收藏 ] [ 简体中文 ]
臺灣貨到付款、ATM、超商、信用卡PAYPAL付款，4-7個工作日送達，999元臺幣免運費　　　在線留言商品價格為新臺幣

商品搜索

类别：

关键字：

商品分类

Hadoop MapReduce v2參考手冊第2版（影印版）
該商品所屬分類：計算機/網絡 -> 程序設計
【市場價】	707-1024元
【優惠價】	442-640元
【作者】	（美）岡納拉森　著，
【所屬類別】	圖書計算機/網絡程序設計其他
【出版社】	東南大學出版社
【ISBN】	9787564160890
【折扣說明】	一次購物滿999元台幣免運費+贈品一次購物滿2000元台幣95折+免運費+贈品一次購物滿3000元台幣92折+免運費+贈品一次購物滿4000元台幣88折+免運費+贈品
【本期贈品】	①優質無紡布環保袋，做工棒！②品牌簽字筆 ③品牌手帕紙巾

版本	正版全新電子版PDF檔
您已选择：	正版全新
溫馨提示：如果有多種選項，請先選擇再點擊加入購物車。 . 電子圖書價格是0.69折，例如了得網價格是100元，電子書pdf的價格則是69元。 . 購買電子書不支持貨到付款，購買時選擇atm或者超商、PayPal付款。付款後1-24小時內通過郵件傳輸給您。 *. 如果收到的電子書不滿意，可以聯絡我們退款。謝謝。

內容介紹

開本：16開

紙張：膠版紙

包裝：平裝

國際標準書號ISBN：9787564160890

作者：（美）岡納拉森著，

出版社：東南大學出版社

出版時間：2016年01月

內容簡介

《Hadoop MapReduce V2參考手冊(第2版)(影印版)(英文版)》開篇介紹了Hadoop YARN、MapReduce、HDFs以及其他Hadoop生態繫統組件的安裝。在《Hadoop MapReduce V2參考手冊(第2版)(影印版)(英文版)》的指引下，你很快就會學習到很多激動人心的主題，例如MapReduce模式，使用Hadoop處理分析、歸類、在線銷售、推薦、數據索引及搜索。你還會學習到如何使用包括Hive、HBase、Pig、Mahout、Nutch～BGi raph在內的Hadoop生態繫統項目以及如何在雲環境下進行部署。

Preface
Chapter 1：Getting Started with Hadooo v2
IntrOductiOn
Setting up Hadoop v2 on your local machine
Writing a WordCount MapReduce application，bundling it
and running it using the Hadoop local mode
Adding a combiner step to the WordCount MapReduce program
Setting up HDFS
Setting up Hadoop YARN in a distributed cluster environment
using Hadoop v2
Setting up Hadoop ecosystem in a distributed cluster environment
using a Hadoop distribution
HDFS command—line file operations
Running the WordCount program in a distributed cluster environmentPreface

Chapter 1：Getting Started with Hadooo v2

IntrOductiOn

Setting up Hadoop v2 on your local machine

Writing a WordCount MapReduce application，bundling it

and running it using the Hadoop local mode

Adding a combiner step to the WordCount MapReduce program

Setting up HDFS

Setting up Hadoop YARN in a distributed cluster environment

using Hadoop v2

Setting up Hadoop ecosystem in a distributed cluster environment

using a Hadoop distribution

HDFS command—line file operations

Running the WordCount program in a distributed cluster environment

Benchmarking HDFS using DFSIO

Benchmarking Hadoop MapReduce using TeraSort

Chapter 2：Cloud Deployments—Using Hadoop YARN on

Cloud Environments

Introduction

Running Hadoop MapReduce v2 computations using Amazon

Elastic MapReduce

Saving money using Amazon EC2 Spot Instances to execute EMR job flows

Executing a Pig script using EMR

Executing a Hive script using EMR

Creating an Amazon EMR job flow using the AWS Command Line Interface

Deploying an Apache HBase cluster on Amazon EC2 using EMR

Using EMR bootstrap actions to configure VMs for the Amazon EMR jobs

Using Apache Whirr to deploy an Apache Hadoop cluster in a

cloud environment

Chapter 3：Hadoop Essentials—C0nfigurations，Unit Tests，and Other APIs

Introduction

Optimizing Hadoop YARN and MapReduce cOnfiguratiOns for

cluster deployments

Shared user Hadoop clusters——using Fair and Capacity schedulers

Setting classpath precedence to user—provided JARs

Speculative execution of straggling tasks

Unit testing Hadoop MapReduce applications using MRUnit

Integration testing Hadoop MapReduce applications using

MiniYarnCluster

Adding a new DataNode

Decommissioning DataNodes

Using multiple disks／volumes and limiting HDFS disk usage

Setting the HDFS block size

Setting the file replication factor

Using the HDFs Java API

Chapter 4：Develooin～ComDlex Hadooo MaoReduce Aoolications

IntrOductiOn

Choosing appropriate Hadoop data types

Implementing a custom Hadoop Writable data type

Implementing a custom Hadoop key type

Emitting data of different value types from a Mapper

Choosing a suitable Hadoop InputFormat for your input data format

Adding support for new input data formats——implementing

a custom InputFormat

Formatting the results of MapReduce computations——using

Hadoop OutputFormats

Writing multiple outputs from a MapReduce computation

Hadoop intermediate data partitioning

Secondary sorting——sorting Reduce input values

BrOadcasting and distributing shared resources to tasks in a

MapReduce job—Hadoop DistributedCache

Using Hadoop with legacy applications——Hadoop streaming

Adding dependencies between MapReduce jobs

Hadoop counters to report custom metrics

Chapter5：Analvtics

Introduction

Simple analytics using MapReduce

Performing GROUP BY using MapReduce

Calculating frequency distributions and sorting using MapReduce

Plotting the Hadoop MapReduce results using gnuplot

Calculating histograms using MapReduce

Calculating Scatter plots using MapReduce

Parsing a complex dataset with Hadoop

Joining two datasets using MapReduce

Chapter6：Hadooo Ecosystem—Apache Hive

Introduction

Getting started with Apache Hive

Creating databases and tables using Hive CLI

Simple SQL—style data querying using Apache Hive

Creating and populating Hive tables and views using Hive query results

Utilizing different storage formats in Hive.storing table data

using ORC files

Using Hive built—in functions

Hive batch mode—using a query file

Performing a join with Hive

Creating partitioned Hive tables

Writing Hive User·defined Functions（UDF）

HCatalog—·performing Java MapReduce computations on

data mapped to Hive tables

HCatalog——writing data to Hive tables from Java

MapReduce computations

Chapter7：HadooD Ecosystem II—Pig.HBase.Mahout.and Sannn

Introduction

Getting started with Apache Pig

Joining two datasets using Pig

Accessing a Hive table data in Pig using HCatalog

Getting started with Apache HBase

Data random access using Java client APIs

Running MapReduce jobs on HBase

Using Hive to insert data into HBase tables

Getting started with Apache Mahout

Running K—means with Mahout

Importing data to HDFS from a relational database using Apache Sqoop

Exporting data from HDFs to a relational database using Apache Sqoop

Tahie OrContencs

Chapter8：Searching and Indexine

Introduction

Generating an inverted index using Hadoop MapReduce

Intradomain web crawling using Apache Nutch

Indexing and searching web documents using Apache Solr

Configuring Apache HBase as the backend data store for Apache Nutch

Whole web crawling with Apache Nutch using a HadooP／HBase cluster

Elasticsearch for indexing and searching

Generating the in—links graph for crawled web pages

Chapter 9：CIassmcatiOns。Recommendations，and Findineg RelationshipS

Introduction

Performing content—based recommendations

Classification using the naive Bayes classifier

Assigning advertisements to keywords using the Adwords

balance algorithm

Chapter 10：Mass Text Data processing

Introduction

Data preprocessing using Hadoop streaming and Python

De—duplicating data using Hadoop streaming

Loading large datasets to an Apache HBase data store—importtsv

and bulkload

Creating TF and TF—IDF vectors for the text data

Clustering text data using Apache Mahout

Topic discovery using Latent Dirichlet Allocation（LDA）

Document classification using Mahout Naive Bayes Classifier

Index

網友評論我們期待著您對此商品發表評論

相關商品

在線留言 商品價格為新臺幣

關於我們送貨時間安全付款會員登入加入會員我的帳戶網站聯盟

返回頂部

商品搜索

商品分类

【醫學】

【各大出版社】