It stores the intermediate processing data in memory. This is possible by reducing number of read/write operations to disk. Speed − Spark helps to run an application in Hadoop cluster, up to 100 times faster in memory, and 10 times faster when running on disk.
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It was donated to Apache software foundation in 2013, and now Apache Spark has become a top level Apache project from Feb-2014. It was Open Sourced in 2010 under a BSD license.
Spark is one of Hadoop’s sub project developed in 2009 in UC Berkeley’s AMPLab by Matei Zaharia. Apart from supporting all these workload in a respective system, it reduces the management burden of maintaining separate tools. Spark is designed to cover a wide range of workloads such as batch applications, iterative algorithms, interactive queries and streaming. The main feature of Spark is its in-memory cluster computing that increases the processing speed of an application. It is based on Hadoop MapReduce and it extends the MapReduce model to efficiently use it for more types of computations, which includes interactive queries and stream processing. Apache SparkĪpache Spark is a lightning-fast cluster computing technology, designed for fast computation. Since Spark has its own cluster management computation, it uses Hadoop for storage purpose only. Spark uses Hadoop in two ways – one is storage and second is processing. Hadoop is just one of the ways to implement Spark. Spark was introduced by Apache Software Foundation for speeding up the Hadoop computational computing software process.Īs against a common belief, Spark is not a modified version of Hadoop and is not, really, dependent on Hadoop because it has its own cluster management. Here, the main concern is to maintain speed in processing large datasets in terms of waiting time between queries and waiting time to run the program. The reason is that Hadoop framework is based on a simple programming model (MapReduce) and it enables a computing solution that is scalable, flexible, fault-tolerant and cost effective.
Industries are using Hadoop extensively to analyze their data sets.
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