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Apache Flume: distributed log collection for Hadoop : design and implement a series of Flume agents to send streamed data into Hadoop /

If you are a Hadoop programmer who wants to learn about Flume to be able to move datasets into Hadoop in a timely and replicable manner, then this book is ideal for you. No prior knowledge about Apache Flume is necessary, but a basic knowledge of Hadoop and the Hadoop File System (HDFS) is assumed.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Hoffman, Steve (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2015.
Edición:Second edition.
Colección:Community experience distilled.
Temas:
Acceso en línea:Texto completo
Texto completo

MARC

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245 1 0 |a Apache Flume: distributed log collection for Hadoop :  |b design and implement a series of Flume agents to send streamed data into Hadoop /  |c Steve Hoffman. 
246 3 0 |a Design and implement a series of Flume agents to send streamed data into Hadoop 
250 |a Second edition. 
264 1 |a Birmingham, UK :  |b Packt Publishing,  |c 2015. 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
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500 |a Includes index. 
505 0 |a Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Overview and Architecture; Flume 0.9; Flume 1.X (Flume-NG); The problem with HDFS and streaming data/logs; Sources, channels, and sinks; Flume events; Interceptors, channel selectors, and sink processors; Tiered data collection (multiple flows and/or agents); The Kite SDK; Summary; Chapter 2: A Quick Start Guide to Flume; Downloading Flume; Flume in Hadoop distributions; An overview of the Flume configuration file; Starting up with ""Hello, World!""; Summary. 
505 8 |a Chapter 3: ChannelsThe memory channel; The file channel; Spillable Memory Channel; Summary; Chapter 4: Sinks and Sink Processors; HDFS sink; Path and filename; File rotation; Compression codecs; Event Serializers; Text output; Text with headers; Apache Avro; User-provided Avro schema; File type; SequenceFile; DataStream; CompressedStream; Timeouts and workers; Sink groups; Load balancing; Failover; MorphlineSolrSink; Morphline configuration files; Typical SolrSink configuration; Sink configuration; ElasticSearchSink; LogStash Serializer; Dynamic Serializer; Summary. 
505 8 |a Chapter 5: Sources and Channel SelectorsThe problem with using tail; The Exec source; Spooling Directory Source; Syslog sources; The syslog UDP source; The syslog TCP source; The multiport syslog TCP source; JMS source; Channel selectors; Replicating; Multiplexing; Summary; Chapter 6: Interceptors, ETL, and Routing; Interceptors; Timestamp; Host; Static; Regular expression filtering; Regular expression extractor; Morphline interceptor; Custom interceptors; The plugins directory; Tiering flows; The Avro source/sink; Compressing Avro; SSL Avro flows; The Thrift source/sink. 
505 8 |a Using command-line AvroThe Log4J appender; The Log4J load-balancing appender; The embedded agent; Configuration and startup; Sending data; Shutdown; Routing; Summary; Chapter 7: Putting it All Together; Web logs to searchable UI; Setting up the web server; Configuring log rotation to the spool directory; Setting up the target -- Elasticsearch; Setting up Flume on collector/relay; Setting up Flume on the client; Creating more search fields with an interceptor; Setting up a better user interface -- Kibana; Archiving to HDFS; Summary; Chapter 8: Monitoring Flume; Monitoring the agent process. 
505 8 |a MonitNagios; Monitoring performance metrics; Ganglia; Internal HTTP server; Custom monitoring hooks; Summary; Chapter 9: There Is No Spoon -- the Realities of Real-time Distributed Data Collection; Transport time versus log time; Time zones are evil; Capacity planning; Considerations for multiple data centers; Compliance and data expiry; Summary; Index. 
520 |a If you are a Hadoop programmer who wants to learn about Flume to be able to move datasets into Hadoop in a timely and replicable manner, then this book is ideal for you. No prior knowledge about Apache Flume is necessary, but a basic knowledge of Hadoop and the Hadoop File System (HDFS) is assumed. 
546 |a English. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
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830 0 |a Community experience distilled. 
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