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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. In a MapReduce job, you want each of you input files processed by a single map task. How do you configure a MapReduce job so that a single map task processes each input file regardless of how many blocks the input file occupies?

A) Set the number of mappers equal to the number of input files you want to process.
B) Increase the parameter that controls minimum split size in the job configuration.
C) Write a custom MapRunner that iterates over all key-value pairs in the entire file.
D) Write a custom FileInputFormat and override the method isSplittable to always return false.

2. Which of the following utilities allows you to create and run MapReduce jobs with any executable or script as the mapper and/or the reducer?

A) Hadoop Streaming
B) Sqoop
C) Oozie
D) Flume

3. You write a MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses TextInputFormat and the IdentityReducer: the mapper applies a regular expression over input values and emits key-value 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 zero.

A) With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one reducer, all instances of matching patterns are gathered together in one file on HDFS.
B) With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of matching patterns are stored in a single file on HDFS.
C) With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With one reducer, instances of matching patterns stored in multiple files on HDFS.
D) There is no difference in output between the two settings.

4. Which of the following best describes the map method input and output?

A) It accepts a single key-value pair as input and emits a single key and list of corresponding values as output
B) It accepts a list of key-value pairs as input hut run emit only one key value pair as output.
C) It accepts a single key-value pair as input and can emit only one key-value pair as output.
D) It accepts a single key-value pair as input and can emit any number of key-value pairs as output, including zero.

5. 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 file in HDFS.

A) Yes.
B) No, but it can be done with either Pig or Hive.
C) No, MapReduce cannot perform relational operations.
D) Yes, so long as both tables fit into memory.
E) Yes, but only if one of the tables fits into memory.

Solutions: