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PolyBase revealed : data virtualization with SQL server, Hadoop, Apache Spark, and beyond /

Harness the power of PolyBase data virtualization software to make data from a variety of sources easily accessible through SQL queries while using the T-SQL skills you already know and have mastered. PolyBase Revealed shows you how to use the PolyBase feature of SQL Server 2019 to integrate SQL Ser...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Feasel, Kevin
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berkeley, CA : Apress L.P., 2020.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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505 0 |a Intro -- Table of Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Chapter 1: Installing and Configuring PolyBase -- Choose the Form of Your PolyBase -- Installing PolyBase Standalone-Windows -- Installing PolyBase Scale-Out Group -- Building a Configuration File -- Installing Without a GUI -- Installing PolyBase Standalone-Linux -- Configuring PolyBase -- Configuring a Client -- Enable PolyBase -- Mandatory Configuration -- Scale-Out Group Configuration -- Troubleshooting Common Errors -- Testing for Success -- Conclusion 
505 8 |a Chapter 2: Connecting to Azure Blob Storage -- Making Preparations in Azure -- Create a Storage Account -- Upload Data -- Building a Link -- Credentials -- External Data Sources -- External File Formats -- Delimited Files -- Flat File Compression -- Define an External File Format -- External Tables -- Querying External Data -- Inserting into External Tables -- PolyBase Data Insertion Considerations -- PolyBase Is Insert-Only -- Insert Only into Folders -- Conclusion -- Chapter 3: Connecting to Hadoop -- Hadoop Prerequisites -- Preparing Files in HDFS -- Gather Configuration Settings 
505 8 |a Configuring SQL Server -- Update PolyBase Configuration Files -- External PolyBase Objects for Hadoop -- Credentials -- External Data Sources -- External File Formats -- Delimited Files -- RCFile -- ORC -- Parquet -- External Tables -- Querying Data in Hadoop -- Row Counts with Police Incident Data -- Newlines and Quotes with Fire Incident Data -- Going Faster with Parking Violations Data -- Inserting Data into Hadoop -- Conclusion -- Chapter 4: Using Predicate Pushdown to Enhance Query Performance -- The Importance of Predicate Pushdown -- Predicate Pushdown in PolyBase 
505 8 |a Diving into Predicate Pushdown -- Packet Capture Without Predicate Pushdown -- Packet Capture with Predicate Pushdown -- When Predicate Pushdown Makes Sense -- Small Data: Raleigh Police Incidents -- Bigger Data: New York City Parking Violations -- Limitations in Pushdown-Eligible Predicates -- Limitations on Pushdown with Complex Filters -- MapReduce and Pushdown in Summary -- Conclusion -- Chapter 5: Common Hadoop and Blob Storage Integration Errors -- Finding the Real Logger -- PolyBase Log Files -- DMS Errors -- DMS Movement -- DWEngine Errors -- DWEngine Movement -- DWEngine Server 
505 8 |a DMS PolyBase -- DWEngine PolyBase -- Hadoop Log Files -- Job Tracker -- YARN Resource Manager -- JobHistory UI -- NameNode Logs -- Log Files -- Configuration Issues -- SQL Server Configuration -- Check External Resources -- Check SQL Server Configuration Files -- Hadoop-Side Configuration -- Invalid User Permissions or Missing Account -- Could Not Obtain Block -- Host File Pointing to 127.0.0.1 -- Kerberos Should Be On or Off, Not Both -- PolyBase and Dockerized Data Nodes -- Data Issues -- Structural Mismatch -- Unsupported Characters or Formats -- PolyBase Data Limitations -- Curate Your Data 
500 |a Predicate Pushdown Failure 
520 |a Harness the power of PolyBase data virtualization software to make data from a variety of sources easily accessible through SQL queries while using the T-SQL skills you already know and have mastered. PolyBase Revealed shows you how to use the PolyBase feature of SQL Server 2019 to integrate SQL Server with Azure Blob Storage, Apache Hadoop, other SQL Server instances, Oracle, Cosmos DB, Apache Spark, and more. You will learn how PolyBase can help you reduce storage and other costs by avoiding the need for ETL processes that duplicate data in order to make it accessible from one source. PolyBase makes SQL Server into that one source, and T-SQL is your golden ticket. The book also covers PolyBase scale-out clusters, allowing you to distribute PolyBase queries among several SQL Server instances, thus improving performance. With great flexibility comes great complexity, and this book shows you where to look when queries fail, complete with coverage of internals, troubleshooting techniques, and where to find more information on obscure cross-platform errors. Data virtualization is a key target for Microsoft with SQL Server 2019. This book will help you keep your skills current, remain relevant, and build new business and career opportunities around Microsoft's product direction. You will: Install and configure PolyBase as a stand-alone service, or unlock its capabilities with a scale-out cluster Understand how PolyBase interacts with outside data sources while presenting their data as regular SQL Server tables Write queries combining data from SQL Server, Apache Hadoop, Oracle, Cosmos DB, Apache Spark, and more Troubleshoot PolyBase queries using SQL Server Dynamic Management Views Tune PolyBase queries using statistics and execution plans Solve common business problems, including "cold storage" of infrequently accessed data and simplifying ETL jobs 
504 |a Includes bibliographical references and index. 
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