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Optimizing Hadoop for MapReduce.
In Detail MapReduce is the distribution system that the Hadoop MapReduce engine uses to distribute work around a cluster by working parallel on smaller data sets. It is useful in a wide range of applications, including distributed pattern-based searching, distributed sorting, web link-graph reversal...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Packt Publishing,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Author; Acknowledgments; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Understanding Hadoop MapReduce; The MapReduce model; Overview of Hadoop MapReduce; Hadoop MapReduce internals; Factors affecting the performance of MapReduce; Summary; Chapter 2: An Overview of the Hadoop Parameters; Investigating the Hadoop parameters; The mapred-site.xml configuration file; The CPU-related parameters; The disk I/O related parameters; The memory-related parameters; The network-related parameters; The hdfs-site.xml configuration file.
- The core-site.xml configuration fileHadoop MapReduce metrics; Performance monitoring tools; Using Chukwa to monitor Hadoop; Using Ganglia to monitor Hadoop; Using Nagios to monitor Hadoop; Using Apache Ambari to monitor Hadoop; Summary; Chapter 3: Detecting System Bottlenecks; Performance tuning; Creating a performance baseline; Identifying resource bottlenecks; Identifying RAM bottlenecks; Identifying CPU bottlenecks; Identifying storage bottlenecks; Identifying network bandwidth bottlenecks; Summary; Chapter 4: Identifying Resource Weaknesses; Identifying cluster weakness.
- Checking the Hadoop cluster node's healthChecking the input data size; Checking massive I/O and network traffic; Checking for insufficient concurrent tasks; Checking for CPU contention; Sizing your Hadoop cluster; Configuring your cluster correctly; Summary; Chapter 5: Enhancement of Map and Reduce Tasks; Enhancing Map tasks; Input data and block size impact; Dealing with small and unsplittable files; Reducing spilled records during the Map phase; Calculating map tasks' throughput; Enhancing Reduce tasks; Calculating reduce task throughput; Improving Reduce execution phase.
- Tuning map and reduce parametersSummary; Chapter 6: Optimizing MapReduce Tasks; Using Combiners; Using compression; Using appropriate Writable types; Reusing types smartly; Optimizing mappers and reducers code; Summary; Chapter 7: Best Practices and Recommendations; Hardware tuning and OS recommendations; Hadoop cluster checklists; The Bios tuning checklist; OS configuration recommendations; Hadoop best practices and recommendations; Deploying Hadoop; Hadoop tuning recommendations; Using a MapReduce template class code; Summary; Index.