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Apache Flume: Distributed Log Collection for Hadoop
Table of Contents
Apache Flume: Distributed Log Collection for Hadoop
Credits
About the Author
About the Reviewers
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Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Errata
Piracy
Questions
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)
Summary
2. Flume Quick Start
Downloading Flume
Flume in Hadoop distributions
Flume configuration file overview
Starting up with "Hello World"
Summary
3. Channels
Memory channel
File channel
Summary
4. Sinks and Sink Processors
HDFS sink
Path and filename
File rotation
Compression codecs
Event serializers
Text output
Text with headers
Apache Avro
File type
Sequence file
Data stream
Compressed stream
Timeouts and workers
Sink groups
Load balancing
Failover
Summary
5. Sources and Channel Selectors
The problem with using tail
The exec source
The spooling directory source
Syslog sources
The syslog UDP source
The syslog TCP source
The multiport syslog TCP source
Channel selectors
Replicating
Multiplexing
Summary
6. Interceptors, ETL, and Routing
Interceptors
Timestamp
Host
Static
Regular expression filtering
Regular expression extractor
Custom interceptors
Tiering data flows
Avro Source/Sink
Command-line Avro
Log4J Appender
The Load Balancing Log4J Appender
Routing
Summary
7. Monitoring Flume
Monitoring the agent process
Monit
Nagios
Monitoring performance metrics
Ganglia
The internal HTTP server
Custom monitoring hooks
Summary
8. 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
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