Edition |
Second edition. |
Description |
1 online resource (1 volume) : illustrations. |
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text file |
Series |
Community experience distilled
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Community experience distilled.
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Note |
Includes index. |
Contents |
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. |
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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. |
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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. |
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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. |
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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. |
Summary |
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. |
Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
Subject |
Apache Hadoop.
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Apache Hadoop. |
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Electronic data processing -- Distributed processing.
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Electronic data processing -- Distributed processing. |
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File organization (Computer science)
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File organization (Computer science) |
Genre/Form |
Electronic books.
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Added Title |
Design and implement a series of Flume agents to send streamed data into Hadoop |
Other Form: |
Print version: Hoffman, Steve. Apache Flume : Distributed Log Collection for Hadoop. Birmingham : Packt Publishing, ©2015 9781784392178 |
ISBN |
9781784399146 (electronic book) |
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1784399140 (electronic book) |
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1784399140 |
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1784392170 |
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9781784392178 |
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