Programming with MapReduce
Apache Hadoop
| Beginner
- 16 videos | 1h 6m 43s
- Includes Assessment
- Earns a Badge
You must have a good understanding of MapReduce to be able to program with it. Here we look at MapReduce in detail, and demonstrate the basics of programming in MapReduce.
WHAT YOU WILL LEARN
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Understand the components of a mapreduce job and the steps to create them. explain each job component and it's function in hadoop mapreduce. understand the steps in creating map reduce job components.Understand a conceptual example of the mapreduce process and how each piece fits into the overall mapreduce algorithmLearn how to use java to write hadoop mapreduce jobs. understand which additional jar to use, and the functionality of the classes within themKnow how to create and execute hadoop mapreduce jobs. illustrate how to compile and run mapreduce programs.Understand the programmatic steps in a hadoop mapreduce job. know how the jobclient, jobtracker, and tasktracker work, and their interaction with the hadoop distributed file system (hdfs).Understand the concept of mapreduce chaining. describe how mapreduce jobs may have several steps with the last mapreduce output will be used as input for the next mapreduce job.Understanding pre-compile, compile, and run commands. discover different techniques to package and run mapreduce jobs.Understand how mapreduce stores and reads big data. demonstrate how mapreduce and hadoop handle data with the hdfs over a distributed processing system.
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Understand how persistence in the hdfs compares to other file storage systems. learn the specifics of reading and writing data in the hdfs, and it's redundancy across the cluster.Overview of how jobs run in mapreduce. introduction to the unit testing process. understand tools and techniques in unit testing.Understand how to view mapreduce job status and how to review and understand log files. learn about how log files are handled by different distributions of hadoop.Understand scenarios where a mapreduce job would need to be terminated. learn how to use the "-list" and "-kill" commands.Overview of junit, and unit testing techniques using junit. understand test cases using junit. overview of junit configuration scripts.Explain cloudera mrunit. compare unit testing with mrunit and without mrunit. understand the unit testing process, and unit testing files.Understand how to use a dummy cluster for unit and integration testing. learn the basics of a mini-hdfs and a mini-mapreduce cluster.Understand the basics of the hadoop localjobrunner. understand that the localjobrunner is a mini version of the mapreduce execution engine. explain how the localjobrunner can run in a debugger and can step through code in mappers and reducers.
IN THIS COURSE
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4m 24sIn this video, you will understand the components of a MapReduce job and the steps to create them. Explain each job component and its function in Hadoop MapReduce. Understand the steps in creating map reduce job components. FREE ACCESS
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3m 34sIn this video, you will understand a conceptual example of the MapReduce process and how each piece fits into the overall MapReduce algorithm. FREE ACCESS
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3m 38sIn this video, you will learn how to use Java to write Hadoop MapReduce jobs. You will understand which additional JAR to use, and the functionality of the classes within them. FREE ACCESS
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7mIn this video, you will learn how to create and execute Hadoop MapReduce jobs. You will also learn how to compile and run MapReduce programs. FREE ACCESS
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3m 57sIn this video, you will understand the programmatic steps in a Hadoop MapReduce job. You will know how the JobClient, JobTracker, and TaskTracker work, and their interaction with the Hadoop Distributed File System (HDFS). FREE ACCESS
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3m 15sIn this video, you will understand the concept of MapReduce chaining. Describe how MapReduce jobs may have several steps with the last MapReduce output being used as input for the next MapReduce Job. FREE ACCESS
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7m 37sLearn how to understand pre-compile, compile, and run commands. Discover different techniques to package and run MapReduce Jobs. FREE ACCESS
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3m 23sIn this video, you will understand how MapReduce stores and reads Big Data. You will also see how MapReduce and Hadoop handle data with the HDFS over a distributed processing system. FREE ACCESS
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3m 21sIn this video, you will understand how persistence in the HDFS compares to other file storage systems. Learn the specifics of reading and writing data in the HDFS, and its redundancy across the cluster. FREE ACCESS
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3m 46sIn this video, you will get an overview of how jobs run in MapReduce. You will also learn about the unit testing process and understand tools and techniques in unit testing. FREE ACCESS
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5m 36sIn this video, you will understand how to view MapReduce job status and how to review and understand log files. Learn about how log files are handled by different distributions of Hadoop. FREE ACCESS
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3m 28sIn this video, you will understand scenarios where a MapReduce job would need to be terminated. Learn how to use the "-list" and "-kill" commands. FREE ACCESS
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3m 21sIn this video, learn how to do an overview of JUnit, and unit testing techniques using JUnit. Understand test cases using JUnit. Overview of JUnit configuration scripts. FREE ACCESS
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3m 12sDuring this video, you will learn how to explain Cloudera MRUnit. Compare unit testing with MRUnit and without MRUnit. Understand the unit testing process, and unit testing files. FREE ACCESS
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3m 37sIn this video, you will understand how to use a dummy cluster for unit and integration testing. Learn the basics of a mini-HDFS and a mini-MapReduce cluster. FREE ACCESS
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3m 35sIn this video, you will understand the basics of the Hadoop LocalJobRunner. Understand that the LocalJobRunner is a mini version of the MapReduce execution engine. Explain how the LocalJobRunner can run in a debugger and can step through code in mappers and reducers. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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