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Microsoft Big Data Solutions

Jorgensen, Adam/Rowland-Jones, James/Welch, John et al
ISBN/EAN: 9781118729083
Umbreit-Nr.: 6000256

Sprache: Englisch
Umfang: 408 S.
Format in cm:
Einband: kartoniertes Buch

Erschienen am 04.04.2014
Auflage: 1/2014
€ 45,90
(inklusive MwSt.)
Nicht lieferbar
  • Zusatztext
    • Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all, it helps you integrate these new solutions with technologies you already know, such as SQL Server and Hadoop. * Walks you through how to integrate Big Data solutions in your company using Microsoft's HDInsight Server, HortonWorks Data Platform for Windows, and open source tools * Explores both on-premises and cloud-based solutions * Shows how to store, manage, analyze, and share Big Data through the enterprise * Covers topics such as Microsoft's approach to Big Data, installing and configuring HortonWorks Data Platform for Windows, integrating Big Data with SQL Server, visualizing data with Microsoft and HortonWorks BI tools, and more * Helps you build and execute a Big Data plan * Includes contributions from the Microsoft and HortonWorks Big Data product teams If you need a detailed roadmap for designing and implementing a fully deployed Big Data solution, you'll want Microsoft Big Data Solutions.

  • Kurztext
    • Implement Big Data solutions with powerful Microsoft tools Microsoft's powerful big data platform--Windows Azure HDInsight and Hortonworks Data Platform for Windows--can transform the way your organization processes, stores, and manages enterprise data. Designed to work seamlessly with your company's existing data infrastructure and with products like SQL Server and Hadoop, Microsoft's suite of big data solutions can be implemented without disrupting workflow or critical processes. If you need a detailed roadmap for designing and implementing a fully deployed big data solution, look no further than Microsoft Big Data Solutions. * Integrate big data solutions in your company using Windows Azure® HDInsight®, Hortonworks® Data Platform for Windows, and open source tools * Store, manage, analyze, and share big data throughout your organization * Install and configure Hortonworks Data Platform for Windows * Learn to integrate big data with SQL Server® and Hadoop * Visualize data with Microsoft and Microsoft and Hadoop BI tools * Create and execute a comprehensive big data strategy for your enterprise * Get leading-edge insights directly from the Microsoft big data product team

  • Autorenportrait
    • InhaltsangabeIntroduction xv Part I What Is Big Data? 1 Chapter 1 Industry Needs and Solutions 3 What's So Big About Big Data? 4 A Brief History of Hadoop 5 Google 5 Nutch 6 What Is Hadoop? 6 Derivative Works and Distributions 7 Hadoop Distributions 8 Core Hadoop Ecosystem 9 Important Apache Projects for Hadoop 11 The Future for Hadoop 17 Summary 17 Chapter 2 Microsoft's Approach to Big Data 19 A Story of "Better Together" 19 Competition in the Ecosystem 20 SQL on Hadoop Today 21 Hortonworks and Stinger 21 Cloudera and Impala 23 Microsoft's Contribution to SQL in Hadoop 25 Deploying Hadoop 25 Deployment Factors 26 Deployment Topologies 29 Deployment Scorecard 33 Summary 36 Part II Setting Up for Big Data with Microsoft 37 Chapter 3 Configuring Your First Big Data Environment 39 Getting Started 39 Getting the Install 40 Running the Installation 40 OnPremise Installation: SingleNode Installation 41 HDInsight Service: Installing in the Cloud 51 Windows Azure Storage Explorer Options 52 Validating Your New Cluster 55 Logging into HDInsight Service 55 Verify HDP Functionality in the Logs 57 Common PostSetup Tasks 58 Loading Your First Files 58 Verifying Hive and Pig 60 Summary 63 Part III Storing and Managing Big Data 65 Chapter 4 HDFS, Hive, HBase, and HCatalog 67 Exploring the Hadoop Distributed File System 68 Explaining the HDFS Architecture 69 Interacting with HDFS 72 Exploring Hive: The Hadoop Data Warehouse Platform 75 Designing, Building, and Loading Tables 76 Querying Data 77 Configuring the Hive ODBC Driver 77 Exploring HCatalog: HDFS Table and Metadata Management 78 Exploring HBase: An HDFS Column-Oriented Database 80 Columnar Databases 81 Defining and Populating an HBase Table 82 Using Query Operations 83 Summary 84 Chapter 5 Storing and Managing Data in HDFS 85 Understanding the Fundamentals of HDFS 86 HDFS Architecture 87 NameNodes and DataNodes 89 Data Replication 90 Using Common Commands to Interact with HDFS 92 Interfaces for Working with HDFS 92 File Manipulation Commands 94 Administrative Functions in HDFS 97 Moving and Organizing Data in HDFS 100 Moving Data in HDFS 100 Implementing Data Structures for Easier Management 101 Rebalancing Data 102 Summary 103 Chapter 6 Adding Structure with Hive 105 Understanding Hive's Purpose and Role 106 Providing Structure for Unstructured Data 107 Enabling Data Access and Transformation 114 Differentiating Hive from Traditional RDBMS Systems 115 Working with Hive 116 Creating and Querying Basic Tables 117 Creating Databases 117 Creating Tables 118 Adding and Deleting Data 121 Querying a Table 123 Using Advanced Data Structures with Hive 126 Setting Up Partitioned Tables 126 Loading Partitioned Tables 128 Using Views 129 Creating Indexes for Tables 130 Summary 131 Chapter 7 Expanding Your Capability with HBase and HCatalog 133 Using HBase 134 Creating HBase Tables 134 Loading Data into an HBase Table 136 Performing a Fast Lookup 138 Loading and Querying HBase 139 Managing Data with HCatalog 140 Working with HCatalog and Hive 140 Defining Data Structures 141 Creating Indexes 143 Creating Partitions 143 Integrating HCatalog with Pig and Hive 145 Using HBase or Hive as a Data Warehouse 149 Summary 150 Part IV Working with Your Big Data 151 Chapter 8 Effective Big Data ETL with SSIS, Pig, and Sqoop 153 Combining Big Data and SQL Server Tools for Better Solutions 154 Why Move the Data? 154 Transferring Data Between Hadoop and SQL Server 155 Working with SSIS and Hive 156 Connecting to Hive 157 Configuring Your Packages 161 Loading Data into Hadoop 165 Getting the Best Performance from SSIS 167 Transferring Data with Sqoop 167 Copying Data from SQL Server 168 Co
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