She might hit some web service too many times by the way of using multiple clusters.She may end up running everything on the local node instead of distributing work over to the cluster.A casual developer might make following mistakes: So, in a shared environment, it might consume little more memory for longer durations. If you understand the MapReduce then you will be able to optimize your queries better. Almost, every other tool such as Hive or Pig converts its query into MapReduce phases.Many organizations have already written a lot of code in MapReduce.So, understanding the MapReduce paradigm and how to convert a problem into series of MapReduce tasks is very important. MapReduce is a paradigm used by many big data tools including Spark.Watch this video to learn more about benefits of using Apache Spark over MapReduce.Ģ. Is there any point of learning MapReduce, then? Spark kind of equals to MapReduce and Oozie put together.This also leads to less context switch of the developer and more productivity. Switching between ‘Running something on cluster’ and ‘doing something locally’ is fairly easy and straightforward. In Spark, you can basically do everything from single code or console (PySpark or Scala console) and get the results immediately.And quite often, translating the output of one MapReduce job into the input of another MapReduce job might require writing another code because Oozie may not suffice. In case of Spark, this is avoided using RDDs and utilizing memory (RAM). Between two consecutive MapReduce jobs, the data has to be written to HDFS and read from HDFS. This mechanism is very time consuming and MapReduce tasks have heavy latency. In Hadoop MapReduce, you write many MapReduce jobs and then tie these jobs together using Oozie/shell script.If run in-memory it is 100x faster than Hadoop MapReduce. What is Apache Spark and what are the benefits of Spark over MapReduce? Hope these Apache Spark interview questions and answers guide will help you in getting prepared for your next interview. Our experts have curated these questions to give you an idea of the type of questions which may be asked in an interview. There is a massive growth in the big data space, and job opportunities are skyrocketing, making this the perfect time to launch your career in this space. Here are the top Apache Spark interview questions and answers.

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