Question

In the context of Hadoop ecosystem, briefly explain the following services: Spark and Mahout

Answer 1

Spark in the context of Hadoop:

Spark is an cluster computing framework. This is an efficient framework for for fault tolerance and maintains the framework and interface for a better programming the clusters. This has an efficient framework for cluster and data set reading over the distrubuted data set.

This is developed in using the "Scala". This supports in maintanance of os like windows, Linux, macOs.

This is a mainly used for analysis of data and understanding the machine learning algorithms. This provides an environment for implementation of algorithms which are recursive and iterative as well.

This helps to maintain the latency that is "maintaining the relationship between the physical ans system settings of arranging the data clusters".

This requires an databbase storage facility and a cluster organizer and manager to operate and perform the operations on the set of data clusters.

This is available for "SQL, Python, R programming" as well to operate in .

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Mahout:

This is a software fremework which is used for implementing and handling of algorithms which are mainly dependant on machine learning technology. This is also used for implementing data analysis techniques like clustering, classification, and filtering.

Mahout was developed by Apache Softwares and written in scala and java which can support various types of OS.

Mahout performs the operations on data analysis and provide statistical information with the clusters of raw data.

This has an ability to perform operations on stand alone project clusters in hadoop environment too.

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Hadoop environment includes the organization of BIGDATA infromations and logics. "MAHOUT and SPARK" helps in organizing the data clusters with handling of various algorithms as well.

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