Apache Spark Interview Questions
Apache Spark is prevailing because of its capability to handle real-time streaming and processing big data faster than Hadoop MapReduce. As the demand for Spark developers are expected to grow in lightning fast manner, 2017 is the golden time to polish your Apache Spark knowledge and build up your career as a data analytics professional, data scientist or big data developer. This guide on spark interview questions and answers will help you to improve your skills that will shape you for Spark developer job roles. This section contains top 50 Apache Spark Interview Questions and Answer. Hope these questions will help you to crack the Spark interview. Happy Job Hunting!
Top 50 Apache Spark Interview Questions and Answers
Let’s proceed further with Apache Spark Interview Questions and Answer-
1) What is Apache Spark? What is the reason behind the evolution of this framework?
2) Explain the features of Apache Spark because of which it is superior to Apache MapReduce?
3) Why is Apache Spark faster than Apache Hadoop?
4) List down the languages supported by Apache Spark.
5) What are the components of Apache Spark Eco-system?
6) Is it possible to run Apache Spark without Hadoop?
7) What is RDD in Apache Spark? How are they computed in Spark? what are the various ways in which it can be created?
8) What are the features of RDD, that makes RDD an important abstraction of Spark?
9) List out the ways of creating RDD in Apache Spark.
10) Explain Transformation in RDD. How is lazy evaluation helpful in reducing the complexity of the System?
11) What are the types of Transformation in Spark RDD Operations?
12) What is the reason behind Transformation being a lazy operation in Apache Spark RDD? How is it useful?
13) What is RDD lineage graph? How is it useful in achieving Fault Tolerance?
14) Explain the various Transformation on Apache Spark RDD like distinct(), union(), intersection(), and subtract().
15) What is the FlatMap Transformation in Apache Spark RDD?
16) Explain first() operation in Apache Spark RDD.
17) Describe join() operation. How is outer join supported?
18) Describe coalesce() operation. When can you coalesce to a larger number of partitions? Explain.
19) Explain pipe() operation. How it writes the result to the standard output?
20) What is the key difference between textFile and wholeTextFile method?
21) what is Action, how it process data in Apache Spark?
22) How is Transformation on RDD different from Action?
23) What are the ways in which one can know that the given operation is Transformation or Action?
24) Describe Partition and Partitioner in Apache Spark.
25) How can you manually partition the RDD?
26) Name the two types of shared variable available in Apache Spark.
27) What are accumulators in Apache Spark?
28) Explain SparkContext in Apache Spark.
29) Discuss the role of Spark driver in Spark application.
30) What role does worker node play in Apache Spark Cluster? And what is the need to register worker node with the driver program?
31) Discuss the various running mode of Apache Spark.
32) Describe the run-time architecture of Spark.
33) What is the command to start and stop the Spark in an interactive shell?
34) Describe Spark SQL.
35) What is SparkSession in Apache Spark? Why is it needed?
36) Explain API create Or Replace TempView().
37) What are the various advantages of DataFrame over RDD in Apache Spark?
38) What is a DataSet? What are its advantages over DataFrame and RDD?
39) On what all basis can you differentiate RDD, DataFrame, and DataSet?
40) What is Apache Spark Streaming? How is the processing of streaming data achieved in Apache Spark? Explain.
41) What is the abstraction of Spark Streaming?
42) Explain what are the various types of Transformation on DStream?
43) Explain the level of parallelism in Spark Streaming. Also describe its need.
44) Discuss writeahead logging in Apache Spark Streaming.
45) What are the roles of the file system in any framework?
46) What do you mean by Speculative execution in Apache Spark?
47) How do you parse data in XML? Which kind of class do you use with java to pass data?
48) Explain Machine Learning library in Spark.
49) List various commonly used Machine Learning Algorithm.
50) Explain the Parquet File format in Apache Spark. When is it the best to choose this?
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Here we have covered all the top Apache spark interview questions which you can encounter in you spark interview. You can share the spark interview questions that you have faced in your interview and what was you experience in it. Also, for any feedback on Apache spark interview questions, feel free to comment.