Learn about the concept and importance of MapReduce.
- HDFS stands for Hadoop Distributed File System.…To conduct distributed processing on HDFS,…we need MapReduce.…MapReduce is a batch processing solution.…Batch processing involves a data set…that doesn't need to be processed immediately…when a transaction occurs.…Let's say that an e-commerce company…stores all its online customer transactions in a database.…
Imagine that an executive wants a weekly sales report.…You can run a batch job every Sunday…to process all the purchase data for that particular week…to produce the necessary information such as market trends.…Since batch jobs don't require real-time processing,…MapReduce has the luxury of spending time…in splitting a big data set…into smaller more manageable chunks.…
It can then move these newly created data sets…across multiple computers…until they are ready to be collapsed into a desired result.…The splitting and shuffling part of MapReduce…is called map tasks…while the collapsing part is referred to as reduce tasks.…To help you understand this concept better,…
Author
Released
8/30/2018- Enabling technologies in data science
- Cloud computing and virtualization
- Installing and working with Proxmox, Hadoop, Spark, and Weka
- Managing virtual machines on Proxmox
- Distributed processing with Spark
- Fundamental applications of machine learning
- Distributed systems and distributed processing
- How Hadoop, Spark, and Weka can work together
Skill Level Beginner
Duration
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Conclusion
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Next steps41s
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Video: Distributed processing with MapReduce