01022nam0-22003371i-450-99000793238040332120041015124650.088-13-24383-9000793238FED01000793238(Aleph)000793238FED0100079323820041015d2003----km-y0itay50------baitaITy-------001yy<<La >>nuova dimensione degli interessi finanziari dell'Unione europeaFabrizio Carrarini, Rosario Massino, Cosimo SassoPadovaCEDAM2003VIII, 276 p.24 cm341.411 rid.itaCarrarini,Fabrizio420985Sasso,Cosimo114959Massino,Rosario496091ITUNINARICAUNIMARCBK990007932380403321O 109s.i.DSSO 146s.i.DSSDSSNuova dimensione degli interessi finanziari dell'Unione europea748139UNINA05618nam 2200709 450 991080784820332120230124190829.01-118-82418-01-118-61254-X(CKB)2670000000421687(EBL)1566514(SSID)ssj0001166371(PQKBManifestationID)11745514(PQKBTitleCode)TC0001166371(PQKBWorkID)11120555(PQKB)10314084(Au-PeEL)EBL1566514(CaPaEBR)ebr10756837(CaONFJC)MIL576363(OCoLC)861529054(CaSebORM)9781118824184(MiAaPQ)EBC1566514(EXLCZ)99267000000042168720130815h20132013 uy| 0engur|n|---|||||txtccrProfessional hadoop solutions /Boris Lublinsky, Kevin T. Smith, Alexey Yakubovich1st editionIndianapolis, IN :John Wiley and Sons,[2013]©20131 online resource (506 p.)Wrox Programmer to programmerDescription based upon print version of record.1-118-61193-4 Includes bibliographical references and index.Professional Hadoop® Solutions; Copyright; Credits; About the Authors; About the Technical Editors; Acnowledgments; Contents; Introduction; Who This Book Is For; What This Book Covers; How This Book Is Structured; What You Need to Use This Book; Conventions; Source Code; Errata; P2P.Wrox.Com; Chapter 1: Big Data and the Hadoop Ecosystem; Big Data Meets Hadoop; Hadoop: Meeting the Big Data Challenge; Data Science in the Business World; The Hadoop Ecosystem; Hadoop Core Components; Hadoop Distributions; Developing Enterprise Applications with Hadoop; Summary; Chapter 2: Storing Data in HadoopHDFSHDFS Architecture; Using HDFS Files; Hadoop-Specific File Types; HDFS Federation and High Availability; HBase; HBase Architecture; HBase Schema Design; Programming for HBase; New HBase Features; Combining HDFS and HBase for Effective Data Storage; Using Apache Avro; Managing Metadata with HCatalog; Choosing an Appropriate Hadoop Data Organization for Your Applications; Summary; Chapter 3: Processing Your Data with MapReduce; Getting to Know MapReduce; MapReduce Execution Pipeline; Runtime Coordination and Task Management in MapReduce; Your First MapReduce ApplicationBuilding and Executing MapReduce ProgramsDesigning MapReduce Implementations; Using MapReduce as a Framework for Parallel Processing; Simple Data Processing with MapReduce; Building Joins with MapReduce; Building Iterative MapReduce Applications; To MapReduce or Not to MapReduce?; Common MapReduce Design Gotchas; Summary; Chapter 4: Customizing MapReduce Execution; Controlling MapReduce Execution with InputFormat; Implementing InputFormat for Compute-Intensive Applications; Implementing InputFormat to Control the Number of Maps; Implementing InputFormat for Multiple HBase TablesReading Data Your Way with Custom RecordReadersImplementing a Queue-Based RecordReader; Implementing RecordReader for XML Data; Organizing Output Data with Custom Output Formats; Implementing OutputFormat for Splitting MapReduce Job's Output into Multiple Directories; Writing Data Your Way with Custom RecordWriters; Implementing a RecordWriter to Produce Output tar Files; Optimizing Your MapReduce Execution with a Combiner; Controlling Reducer Execution with Partitioners; Implementing a Custom Partitioner for One-to-Many Joins; Using Non-Java Code with Hadoop; Pipes; Hadoop StreamingUsing JNISummary; Chapter 5: Building Reliable MapReduce Apps; Unit Testing MapReduce Applications; Testing Mappers; Testing Reducers; Integration Testing; Local Application Testing with Eclipse; Using Logging for Hadoop Testing; Processing Applications Logs; Reporting Metrics with Job Counters; Defensive Programming in MapReduce; Summary; Chapter 6: Automating Data Processing with Oozie; Getting to Know Oozie; Oozie Workflow; Executing Asynchronous Activities in Oozie Workflow; Oozie Recovery Capabilities; Oozie Workflow Job Life Cycle; Oozie Coordinator; Oozie BundleOozie Parameterization with Expression LanguageThe go-to guidebook for deploying Big Data solutions with Hadoop Today's enterprise architects need to understand how the Hadoop frameworks and APIs fit together, and how they can be integrated to deliver real-world solutions. This book is a practical, detailed guide to building and implementing those solutions, with code-level instruction in the popular Wrox tradition. It covers storing data with HDFS and Hbase, processing data with MapReduce, and automating data processing with Oozie. Hadoop security, running Hadoop with Amazon Web Services, best practices, and automating HadoopElectronic data processingDistributed processingFile organization (Computer science)Cloud computingElectronic data processingDistributed processing.File organization (Computer science)Cloud computing.005.74Lublinsky Boris760142Smith Kevin T760143Yakubovich Alexey760144MiAaPQMiAaPQMiAaPQBOOK9910807848203321Professional Hadoop solutions1537544UNINA