Free Big Data and Hadoop Developer Practice Test8956 Tests taken

Take this Hadoop exam and prepare yourself for the official Hadoop certification. This Hadoop cca175 certification dumps will give you an insight into the concepts covered in the certification exam and tests you on Spark and Hive concepts. The Hadoop online practice test is free and can you can take it multiple times. If you are the kind to get nervous before a test, then these Hadoop certification questions will help you. Take the Big Data exam questions today and kickstart your career as a certified Big Data professional today.

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  • Instructions:

  • FREE test and can be attempted multiple times.
  • 45 Minutes
  • 45 Multiple Choice Questions
  • You can pause the test in between and you are allowed to re-take the test later.
1. When is the earliest point at which the reduce method of a given Reducer can be called?
2. How does a client read a file from HDFS?
3. You are developing a combiner that takes text keys and IntWritable values as input and emits text keys and IntWritable values. Which interface should your class implement?
4. Identify the utility that allows you to create and run MapReduce jobs with any executable script as the Mapper and/or the Reducer?
5. How are keys and values presented and passed to Reducers during a standard sort and shuffle phase of MapReduce?
6. Assuming default settings, which best describes the order of data provided to a Reducer's reduce method?
7. Which command helps show a file or directory indication in Linux?
8. Which file contains the entire file system namespace, including the mapping of blocks to files and file system properties?
9. You have written a MapReduce job that will process 500 million input records and generate 500 million key-value pairs. The data are not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that will need to be transfered between Mappers and Reducers, which is a potential bottleneck. A custom implementation of which interface is most likely to reduce the amount of intermediate data transferred across the network?
10. Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the two tables are formatted as comma-separated files in HDFS.
11. You have just executed a MapReduce job. Where is intermediate data written to after being emitted from the Mapper's map method?
12. Who is responsible for the creation, deletion and replication of blocks?
13. Which command is used to start Pig in MapReduce mode?
14. Which keyword in Pig Latin is used to accept input files?
15. You develop a MapReduce job for sales reporting. The Mapper will process input keys which represent the year (IntWritable) and input values represent product identifiers (Text). Identify what determines the data types used by the Mapper.
16. Identify the MapReduce v2 (MRv2 / YARN) daemon that launches application containers and monitors the application resource usage.
17. Which best describes how TextInputFormat processes input files and line breaks?
18. For each input key-value pair, Mappers can emit:
19. The following key-value pairs are the output from a Map task: (the, 1), (fox, 1), (faster, 1), (than, 1), (the, 1), (dog, 1). How many keys will be passed to the Reducer's reduce method?
20. Provide the correct sequence for writing to HDFS. (i) the HDFS client caches packets of data in memory (ii) The client will stream the packet of data to the first targeted DataNode (iii) The NameNode will provide the DataNode information about the locations for the block replicas.
21. What is the disadvantage of using multiple Reducers with the default HashPartitioner and distributing your workload across your cluster?
22. Which component compiles HiveQL into a directed acyclic graph of map/reduce tasks?
23. If you want to input each line as one record to your Mapper, then which InputFormat should you use to complete the line: conf.setInputFormat (----.class) ; ?
24. You need to perform a statistical analysis in your MapReduce job and would like to call methods in the Apache Commons Math library, which is distributed as a 1.3 megabyte Java archive (JAR) file. Which is the best way to make this library available to your MapReducer job at runtime?
25. While reading, the HDFS client will try to find a replica based on:
26. For each intermediate key, each Reducer task can emit:
27. What data does a Reducer's reduce method process?
28. All keys used for intermediate output from Mappers must:
29. On a cluster which runs MapReduce v1 (MRv1), a TaskTracker heartbeats into the JobTracker and alerts the JobTracker it has an open map task slot. What determines how the JobTracker assigns each map task to a TaskTracker?
30. What is a SequenceFile?
31. A client application creates an HDFS file named foo.txt with a replication factor of 3. Identify which best describes the file access rules in HDFS if the file has a single block that is stored on data nodes A, B, and C?
32. In a MapReduce job, you want each of your input files to be processed by a single map task. How do you configure a MapReduce job such that a single map task processes each input file regardless of how many blocks the input file occupies?
33. Which is the single entry point for clients to submit YARN applications?
34. When is the reduce method first called in a MapReduce job?
35. You have written a Mapper which invokes five calls to the OutputColletor.collect method: output.collect (new Text ( Apple ), new Text ( Red ) ) ; output.collect (new Text ( Banana ), new Text ( Yellow ) ) ; output.collect (new Text ( Apple ), new Text ( Yellow ) ) ; output.collect (new Text ( Cherry ), new Text ( Red ) ) ; output.collect (new Text ( Apple ), new Text ( Green ) ) ; How many times will the Reducer's reduce method be invoked?
36. To process input key-value pairs, your Mapper needs to lead a 512 MB data file in memory. What is the best way to accomplish this?
37. In a MapReduce job, the Reducer receives all values associated with the same key. Which statement best describes the ordering of these values?
38. You need to create a job that performs a frequency analysis on input data. Do this by writing a Mapper that uses TextInputFormat and splits each value (a line of text from an input file) into individual characters. For each one of these characters, you will emit the character as a key and an InputWritable as the value. As this will produce proportionally more intermediate data than input data, which two resources should you expect to be bottlenecks?
39. You want to count the number of occurrences of each unique word in the input data. You have decided to implement this by having your Mapper tokenize each word and emit a literal value 1, and then have your Reducer increment a counter for each literal 1 it receives. After successfully implementing this, it occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your existing Reducers as your combiner in this case? Why or why not?
40. Which one is a better configuration for NameNodes hard disks?
41. Which project gives you a distributed, scalable data store that allows random, real-time read/write access to hundreds of terabytes of data?
42. You use the Hadoop fs put command to write a 300 MB file using an HDFS block size of 64 MB. The command has just finished writing 200 MB of this file. What would another user see when they try to access this file?
43. Identify the tool best suited to import a portion of a relational database every day as files into HDFS, and which can generate Java classes to interact with the imported data.
44. You have a directory named jobdata in HDFS that contains four files: -first.txt, second.txt, .third.txt, and #data.txt. How many files will be processed by the FileInputFormat.setInputPaths () command when it is given a path object representing this directory?
45. You write a MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses TextInputFormat: the Mapper applies a regular expression over input values and emits key-values pairs with the key consisting of the matching text and the value containing the filename and byte offset. Determine the difference between setting the number of Reducers to one and setting the number of Reducers to zero.


  • What is a Big Data and Hadoop Developer Practice Test?

    The Big Data and Hadoop Developer Practice Test is an online assessment tool designed as a mock version of CCA175 Certification exam conducted by Cloudera. The test is free of cost and includes 45 multiple choice questions that are picked from Spark and Hive concepts and gives you a clear picture of what you will face in the actual Big Data Certification exam.

  • Who can take up this Hadoop online practice test?

    The Hadoop CCA175 certification dumps can be taken up by the candidates preparing for the official Hadoop Certification exam to become a certified Big Data professional.

  • What will I learn from the Hadoop certification dumps?

    The questions asked in this Hadoop practice exam validate your skills in data processing using Spark, Spark RDD optimization techniques, interactive Spark algorithms and more. You can build effective learning strategies to master the Big Data framework using Hadoop and Spark, including HDFS, YARN, and MapReduce. 

  • What are the requirements to take this Big Data practice test?

    The Big Data exam questions can be attempted without any requirements.

  • Will the Practice Tests be updated frequently?

    Yes, we continually improvise our Big Data question bank to include the most recent information crucial to the CCA 175 exam content.

  • Will this Big Data Hadoop practice test help in clearing the CCA175 exam?

    Yes, our question style provides a fair perspective of what can be expected in Cloudera's CCA175 Certification exam. While we can not ensure your success, you will definitely find appearing the actual test much easier. 

  • What is included in this Hadoop practice test?

    This Big Data Hadoop practice exam consists of 45 questions. Each question has multiple options out of which one or more may be correct. You can find a pause option while attempting the test. The pause function allows you to interrupt the test and continue it afterward. 

  • Can I retake this Hadoop practice exam?

    Yes, you can re-take answering the Hadoop multiple choice questions to make a comparative analysis of your score and improve your performance. Make sure to re-take the test only when you have completed your preparation to get a better analysis post the test.

  • Are these the same CCA175 questions I'll see on the real exam?

    The Big Data practice questions extensively resemble the ones that are asked in the exam conducted by Cloudera. 

  • I didn’t do well on this Big Data practice test. What should I do now?

    You can re-take the test if you are unsure of your preparation. You can also register for our Big Data Hadoop Certification Training course to get deep insights into the Big Data concepts. For an in-depth knowledge on the Big Data concepts, the Big Data Engineer Master’s Certification program could be of help. The program in collaboration with IBM provides online training on the popular skills required for a successful career in data engineering. This enables one to master the Big Data & Hadoop frameworks, leverage the functionality of AWS services, and use the database management tool MongoDB to store data.

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.