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Apache Flume

Distributed Log Collection for Hadoop

Parámetros

  • 108 páginas
  • 4 horas de lectura

Más información sobre el libro

Apache Flume is a distributed service designed for efficiently collecting, aggregating, and moving large volumes of log data, primarily aimed at delivering data to Apache Hadoop's HDFS. Its architecture is simple and flexible, focusing on streaming data flows while ensuring robustness and fault tolerance through various failover and recovery mechanisms. This resource addresses issues related to HDFS and streaming data/logs, demonstrating how Flume can effectively resolve these challenges. The book begins with an architectural overview of Flume, detailing each component and guiding readers through the installation and compilation processes. It covers the use of channels and channel selectors, providing in-depth explanations of architectural components such as Sources, Channels, Sinks, Channel Processors, and Sink Groups, along with their configuration options. This allows for customization of Flume to meet specific needs. Additionally, it offers insights into writing custom implementations, enhancing your understanding and ability to apply them. By the end of the book, readers will be equipped to construct a series of Flume agents that transport streaming data and logs from their systems into Hadoop in near real time.

Compra de libros

Apache Flume, Subas D'Souza

Idioma
Publicado en
2013
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Título
Apache Flume
Subtítulo
Distributed Log Collection for Hadoop
Idioma
Inglés
Publicado en
2013
Formato
Tapa blanda
Páginas
108
ISBN10
1782167919
ISBN13
9781782167914
Serie
Descripción
Apache Flume is a distributed service designed for efficiently collecting, aggregating, and moving large volumes of log data, primarily aimed at delivering data to Apache Hadoop's HDFS. Its architecture is simple and flexible, focusing on streaming data flows while ensuring robustness and fault tolerance through various failover and recovery mechanisms. This resource addresses issues related to HDFS and streaming data/logs, demonstrating how Flume can effectively resolve these challenges. The book begins with an architectural overview of Flume, detailing each component and guiding readers through the installation and compilation processes. It covers the use of channels and channel selectors, providing in-depth explanations of architectural components such as Sources, Channels, Sinks, Channel Processors, and Sink Groups, along with their configuration options. This allows for customization of Flume to meet specific needs. Additionally, it offers insights into writing custom implementations, enhancing your understanding and ability to apply them. By the end of the book, readers will be equipped to construct a series of Flume agents that transport streaming data and logs from their systems into Hadoop in near real time.