Hadoop is parallel data processing framework that has traditionally been used to run map/reduce jobs. These are long running jobs that take minutes or hours to complete. Spark has designed to run on top of Hadoop and it is an alternative to the traditional batch map/reduce model that can be used for real-time stream data processing and fast interactive queries that finish within seconds. So, Hadoop supports both traditional map/reduce and Spark.
We should look at Hadoop as a general purpose Framework that supports multiple models and We should look at Spark as an alternative to Hadoop MapReduce rather than a replacement to Hadoop.
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