Published date: February 15, 2022 4:18 pm
Location: Mumbai, Maharashtra, India
Apache Spark has become one of the key cluster-computing frame works in the world. Spark can be deployed in numereous ways like in machine Learning, Streaming data and graphic processing. Spark supports programming languages like Python, Scala, Java, and R.
Apache Hadoop is an open-source framework written in Java that allows us to store and process Big Data in a distributed environment, across various clusters of computers using simple programming constructs. To do this, Hadoop uses an algorithm called Map Reduce, which divides the task into small parts and assigns them to a set of computers. Hadoop also has its own file system, Hadoop Distributed File System (HDFS), which is based on Google File System (GFS). HDFS is designed to run on low-cost hardware.
Apache Spark is an open-source distributed cluster-computing framework. Spark is a data processing engine developed to provide faster and easy-to-use analytics than Hadoop Ma pReduce.
Apache Spark in the big data industry is because of its in-memory data processing that makes it high-speed data processing engine compare to Map Reduce. Apache Spark has huge potential to contribute to Big data related business in the industry.
Apache Spark is a Big data processing interface which provides not only programming interface in the data cluster but also adequate fault tolerance and data parallelism. This open-source platform is efficient in speedy processing of massive datasets.
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