Spark and Scala Exam Questions - Free Practice Test

Companies are always on the lookout for Big Data professionals who can help their businesses. So, if you are aspiring for a career in Big Data, this Apache Spark and mock test can be of your great help. Simplilearn’s Apache Spark and Scala practice test contains Apache Spark and Scala questions that are similar to the questions that you might encounter in the final certification exam. This gives you the confidence to appear the certification exam and even clear it. Take this Apache Spark test today!

  • 25 Questions,
  • 30 Minutes
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Apache Spark & Scala

This Apache Spark and Scala certification training is designed to advance your expertise working with the Big Data Hadoop Ecosystem. You ...

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1. This is a FREE test and can be attempted multiple times. But it is recommended to take the test when you are ready for best practice experience.

2. Test Duration: 30 Minutes

3. Number of questions: 25 Multiple Choice Questions

4. Each question has multiple options out of which one or more may be correct

5. You can pause the test in between and you are allowed to re-take the test later. Your test will resume from where you left, but the test time will be reduced by the amount of time you've taken in the previous attempt.

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1. Which of the following data sources can be accessed by Spark?
2. With which of the following modes Apache Spark can run?
3. Which of the following is called a driver?
4. You have created a jar file for the word count example written in Java. Which of the following is the correct command to submit a job in Spark? Your jar name is firstprogram.jar and the main class is, which requires an input file name and output directory as input parameters.
5. Which of the following is the correct statement regarding RDDs?
6. Which of the following statement is true about the tail method in Scala?
7. Which of the following is the correct statement regarding importing SparkContext?
8. Which of the following is the correct statement regarding importing SparkContext?
9. Which of the following operations can cause a shuffle include repartition operations?
10. Which of the below methods are used for persisting an RDD into memory?
11. Which of the following can be used to implement counters (as in MapReduce) or sums?
12. Which of the following built-in sources are supported in Spark SQL?
13. Which of the following clustering algorithms are supported in Spark?
14. Which of the following statement is true about the saveAsObjectFile method?
15. Which of the following Machine Learning API is built over RDDs?
16. Which of the following can transform one DataFrame into another DataFrame?
17. Machine Learning can be applied to which of the following data types?
18. Which of the following complex data types are supported by DataFrames and Spark SQL?
19. Which of the following Hive features are not yet supported by Spark?
20. Which of the following mode(s) is/are supported by Spark SQL for converting existing RDDs into DataFrames?
21. Which of the following statement is true about 'SaveMode.Ignore' in Spark SQL?
22. Which of the following in Spark ML helps running a sequence of algorithms to process and learn from data?
23. Which of the following class is used for model selection in the library?
24. Which among following is a collaborative filtering technique?
25. Which of the following are classification and regression techniques?
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  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.

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