{"id":6104,"date":"2018-01-26T07:56:04","date_gmt":"2018-01-26T07:56:04","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=6104"},"modified":"2021-03-04T18:37:05","modified_gmt":"2021-03-04T13:07:05","slug":"spark-interview-questions","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/spark-interview-questions\/","title":{"rendered":"Top 100 Apache Spark Interview Questions and Answers"},"content":{"rendered":"

1. Spark Interview Questions<\/h2>\n

As we know Apache Spark is a booming technology nowadays. Hence it is very important to know each and every aspect of Apache Spark<\/strong><\/a> as well as Spark Interview Questions. So, this blog will definitely help you regarding the same. \u00a0In this blog, we will cover each and every aspect of Spark, which may also be possible frequently asked Spark Interview Questions. Moreover, we will try our best to provide each Question, that from now onwards your search for best and all Spark Interview Questions will end here.<\/p>\n

So, let’s explore important Spark Interview Questions.<\/p>\n

2. Apache Spark Interview Questions Answers<\/h2>\n

So, here is the Spark Interview Questions list which contains all types of interview Questions asked in Spark interview.<\/p>\n

Que 1. What is Apache Spark?<\/strong>
\nView Answer<\/a><\/strong>
\nQue 2. Why Apache Spark?<\/strong>
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\nQue 3. What are the components of Apache Spark Ecosystem?<\/strong>
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\nQue 4. What is Spark Core?<\/strong>
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\nQue 5. Which all languages Apache Spark supports?<\/strong>
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\nQue 6. How is Apache Spark better than Hadoop?<\/strong>
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\nQue 7. What are the different methods to run Spark over Apache Hadoop? <\/strong>
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\nQue 8. What is SparkContext in Apache Spark?<\/strong>
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\nQue 9. What is SparkSession in Apache Spark?<\/strong>
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\nQue 10. SparkSession vs SparkContext in Apache Spark.<\/strong>
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\nQue 11. What are the abstractions of Apache Spark?<\/strong>
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\nQue 12. How can we create RDD in Apache Spark? <\/strong>
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\nQue 13. Why is Spark RDD immutable?<\/strong>
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\nQue 14. Explain the term paired RDD in Apache Spark<\/strong>
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\nQue 15. How is RDD in Spark different from Distributed Storage Management?<\/strong>
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\nQue 16. Explain transformation and action in RDD in Apache Spark.<\/strong>
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\nQue 17. What are the types of Apache Spark transformation?<\/strong>
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\nQue 18. Explain the RDD properties.<\/strong>
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\nQue 19. What is lineage graph in Apache Spark? <\/strong>
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\nQue 20. \u00a0Explain the terms\u00a0 Spark Partitions and Partitioners.<\/strong>
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\nQue 21. By Default, how many partitions are created in RDD in Apache Spark?<\/strong>
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\nQue 22. What is Spark DataFrames?<\/strong>
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\nQue 23. What are benefits of DataFrame in Spark?<\/strong>
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\nQue 24. What is Spark Dataset?<\/strong>
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\nQue 25. What are the advantages of datasets in spark?<\/strong>
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\nQue 26. What is Directed Acyclic Graph in Apache Spark?<\/strong>
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\nQue 27. What is the need for Spark DAG?<\/strong>
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\nQue 28.What is the difference between DAG and Lineage?<\/strong>
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\nQue 29. What is the difference between Caching and Persistence in Apache Spark?<\/strong>
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\nQue 30. What are the limitations of Apache Spark?<\/strong>
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\nQue 31. Different Running Modes of Apache Spark <\/strong>
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\nQue 32. What are the different ways of representing data in Spark? <\/strong>
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\nQue 33. What is write ahead log(journaling) in Spark? <\/strong>
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\nQue 34. Explain catalyst query optimizer in Apache Spark.<\/strong>
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\nQue 35. What are shared variables in Apache Spark?<\/strong>
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\nQue 36. How does Apache Spark handles accumulated Metadata?<\/strong>
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\nQue 37. What is Apache Spark Machine learning library? <\/strong>
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\nQue 38. List commonly used Machine Learning Algorithm.<\/strong>
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\nQue 39. What is the difference between DSM and RDD?<\/strong>
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\nQue 40. List the advantage of Parquet file in Apache Spark.<\/strong>
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\nQue 41. What is lazy evaluation in Spark? <\/strong>
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\nQue 42. What are the benefits of Spark lazy evaluation?<\/strong>
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\nQue 43. How much faster is Apache spark than Hadoop?<\/strong>
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\nQue 44. What are the ways to launch Apache Spark over YARN?<\/strong>
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\nQue 45. Explain various cluster manager in Apache Spark?<\/strong>
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\nQue 46. What is Speculative Execution in Apache Spark?<\/strong>
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\nQue 47. How can data transfer be minimized when working with Apache Spark?<\/strong>
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\nQue 48. What are the cases where Apache Spark surpasses Hadoop?<\/strong>
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\nQue 49. What is action, how it process data in apache spark<\/strong>
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\nQue 50. How is fault tolerance achieved in Apache Spark?<\/strong>
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\nQue 51. What is the role of Spark Driver in spark applications?<\/strong>
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\nQue 52. What is worker node in Apache Spark cluster?<\/strong>
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\nQue 53. Why is Transformation lazy in Spark?<\/strong>
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\nQue 54. Can I run Apache Spark without Hadoop?<\/strong>
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\nQue 55. Explain Accumulator in Spark.<\/strong>
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\nQue 56. \u00a0What is the role of Driver program in Spark Application?<\/strong>
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\nQue 57. How to identify that given operation is Transformation\/Action in your program?<\/strong>
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\nQue 58. Name the two types of shared variable available in Apache Spark.<\/strong>
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\nQue 59. What are the common faults of the developer while using Apache Spark? <\/strong>
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\nQue 60. By Default, how many partitions are created in RDD in Apache Spark?<\/strong>
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\nQue 61. Why we need compression and what are the different compression format supported?<\/strong>
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\nQue 62. Explain the filter transformation.<\/strong>
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\nQue 63. How to start and stop spark in interactive shell?<\/strong>
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\nQue 64. Explain sortByKey() operation.<\/strong>
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\nQue 65. Explain distnct(),union(),intersection() and substract() transformation in Spark<\/strong>
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\nQue 66.Explain foreach() operation in apache spark<\/strong>
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\nQue 67.groupByKey vs reduceByKey in Apache Spark <\/strong>
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\nQue 68. Explain mapPartitions() and mapPartitionsWithIndex()<\/strong>
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\nQue 69. What is Map in Apache Spark?<\/strong>
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\nQue 70. What is FlatMap in Apache Spark?<\/strong>
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\nQue 71.Explain fold() operation in Spark.<\/strong>
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\nQue 72. Explain API createOrReplaceTempView()<\/strong>
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\nQue 73. Explain values() operation in Apache Spark.<\/strong>
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\nQue 74. Explain keys() operation in Apache spark.<\/strong>
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\nQue 75. Explain textFile Vs wholeTextFile in Spark <\/strong>
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\nQue 76. Explain cogroup() operation in Spark<\/strong>
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\nQue 77. Explain pipe() operation in Apache Spark<\/strong>
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\nQue 78. Explain Spark coalesce() operation<\/strong>
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\nQue 79.Explain the repartition() operation in Spark<\/strong>
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\nQue 80. Explain fullOuterJoin() operation in Apache Spark<\/strong>
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\nQue 81. Expain Spark leftOuterJoin() and rightOuterJoin() operation<\/strong>
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\nQue 82. Explain Spark join() operation<\/strong>
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\nQue 83. Explain the top() and takeOrdered() operation<\/strong>
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\nQue 84. Explain first() operation in Spark<\/strong>
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\nQue 85. Explain sum(), max(), min() operation in Apache Spark<\/strong>
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\nQue 86. Explain countByValue() operation in Apache Spark RDD<\/strong>
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\nQue 87. Explain the lookup() operation in Spark<\/strong>
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\nQue 88. Explain Spark countByKey() operation<\/strong>
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\nQue 89. Explain Spark saveAsTextFile() operation<\/strong>
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\nQue 90. Explain reduceByKey() Spark operation<\/strong>
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\nQue 91. Explain the operation reduce() in Spark<\/strong>
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\nQue 92.Explain the action count() in Spark RDD<\/strong>
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\nQue 93. Explain\u00a0Spark map() transformation<\/strong>
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\nQue 94. Explain the flatMap() transformation in Apache Spark<\/strong>
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\nQue 95. What are the limitations of Apache Spark?<\/strong>
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\nQue 96. What is Spark SQL?<\/strong>
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\nQue 97. Explain Spark SQL caching and uncaching<\/strong>
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\nQue 98. Explain Spark streaming<\/strong>
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\nQue 99. What is DStream in Apache Spark Streaming?<\/strong>
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\nQue 100. Explain different transformations in DStream in Apache Spark Streaming<\/strong>
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\nQue 101. What is Starvation scenario in spark streaming<\/strong>
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\nQue 102.Explain the level of parallelism in spark streaming<\/strong>
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\nQue 103. What are the different input sources for Spark Streaming<\/strong>
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\nQue 104. Explain Spark Streaming with Socket<\/strong>
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\nQue 105. \u00a0Define the roles of the file system in any framework?<\/strong>
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\nQue 106. How do you parse data in XML? Which kind of class do you use with Java to parse data?<\/strong>
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\nQue 107. What is PageRank in Spark?<\/strong>
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\nQue 108. What are the roles and responsibilities of worker nodes in the Apache Spark cluster? Is Worker Node in Spark is same as Slave Node?<\/strong>
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\nQue 109. How to split single HDFS block into partitions RDD?<\/strong>
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\nQue 110. On what all basis can you differentiate RDD, DataFrame, and DataSet?<\/strong>
\nView Answer <\/a><\/strong>
\nSo, this was all on Apache spark interview Questions. hope you like the Apache spark interview Questions and Answers explained to it.<\/p>\n

3. Conclusion – Spark Interview Questions<\/strong><\/h2>\n

Hence, we have tried to cover, all the possible frequent Apache Spark<\/a> Interview Questions which may ask in Spark Interview when you\u00a0search for Spark jobs. However, if you want to add any question in Spark Interview Questions or if you want to ask any Query regarding Spark Interview Questions, feel free to ask in the comment section. Moreover, we assure you that, we will definitely get back to you.<\/span>

1. Spark Interview Questions As we know Apache Spark is a booming technology nowadays. 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