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Mastering Hadoop
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DoyouwanttobroadenyourHadoopskillsetandtakeyourknowledgetothenextlevel?DoyouwishtoenhanceyourknowledgeofHadooptosolvechallengingdataprocessingproblems?AreyourHadoopjobs,Pigscripts,orHivequeriesnotworkingasfastasyouintend?AreyoulookingtounderstandthebenefitsofupgradingHadoop?Iftheanswerisyestoanyofthese,thisbookisforyou.Itassumesnovice-levelfamiliaritywithHadoop.
目錄(105章)
倒序
- coverpage
- Mastering Hadoop
- Credits
- About the Author
- Acknowledgments
- About the Reviewers
- www.PacktPub.com
- Support files eBooks discount offers and more
- Preface
- What this book covers
- What you need for this book?
- Who this book is for
- Conventions
- Reader feedback
- Customer support
- Chapter 1. Hadoop 2.X
- The inception of Hadoop
- The evolution of Hadoop
- Hadoop 2.X
- Hadoop distributions
- Summary
- Chapter 2. Advanced MapReduce
- MapReduce input
- The RecordReader class
- Hadoop's "small files" problem
- Filtering inputs
- The Map task
- The Reduce task
- MapReduce output
- MapReduce job counters
- Handling data joins
- Summary
- Chapter 3. Advanced Pig
- Pig versus SQL
- Different modes of execution
- Complex data types in Pig
- Compiling Pig scripts
- Development and debugging aids
- The advanced Pig operators
- User-defined functions
- Pig performance optimizations
- Best practices
- Summary
- Chapter 4. Advanced Hive
- The Hive architecture
- Data types
- File formats
- The data model
- Hive query optimizers
- Advanced DML
- UDF UDAF and UDTF
- Summary
- Chapter 5. Serialization and Hadoop I/O
- Data serialization in Hadoop
- Avro serialization
- File formats
- Compression
- Summary
- Chapter 6. YARN – Bringing Other Paradigms to Hadoop
- The YARN architecture
- Developing YARN applications
- Monitoring YARN
- Job scheduling in YARN
- YARN commands
- Summary
- Chapter 7. Storm on YARN – Low Latency Processing in Hadoop
- Batch processing versus streaming
- Apache Storm
- Storm on YARN
- Summary
- Chapter 8. Hadoop on the Cloud
- Cloud computing characteristics
- Hadoop on the cloud
- Amazon Elastic MapReduce (EMR)
- Summary
- Chapter 9. HDFS Replacements
- HDFS – advantages and drawbacks
- Amazon AWS S3
- Implementing a filesystem in Hadoop
- Implementing an S3 native filesystem in Hadoop
- Summary
- Chapter 10. HDFS Federation
- Limitations of the older HDFS architecture
- Architecture of HDFS Federation
- HDFS high availability
- HDFS block placement
- Summary
- Chapter 11. Hadoop Security
- The security pillars
- Authentication in Hadoop
- Authorization in Hadoop
- Data confidentiality in Hadoop
- Audit logging in Hadoop
- Summary
- Chapter 12. Analytics Using Hadoop
- Data analytics workflow
- Machine learning
- Apache Mahout
- Document analysis using Hadoop and Mahout
- RHadoop
- Summary
- Appendix A. Hadoop for Microsoft Windows
- Deploying Hadoop on Microsoft Windows
- Summary
- Index 更新時(shí)間：2021-08-06 19:53:18
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