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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. 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, no reducer runs and the job throws an exception. With one reducer, instances of matching patterns are stored in a single file on HDFS.
B) 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.
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.

2. Given a Mapper, Reducer, and Driver class packaged into a jar, which is the correct way of submitting the job to the cluster?

A) hadoop jar class MyJar.jar MyDriverClass inputdir outputdir
B) jar MyJar.jar
C) jar MyJar.jar MyDriverClass inputdir outputdir
D) hadoop jar MyJar.jar MyDriverClass inputdir outputdir

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

4. For each input key-value pair, mappers can emit:

A) As many intermediate key-value pairs as desired, but they cannot be of the same type as the input key-value pair.
B) One intermediate key value pair, but of the same type.
C) As many intermediate key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
D) As many intermediate key value pairs as desired, as long as all the keys have the same type and all the values have the same type.
E) One intermediate key value pair, of a different type.

5. You need a distributed, scalable, data Store that allows you random, realtime read/write access to hundreds of terabytes of data. Which of the following would you use?

A) Oozie
B) Hive
C) Pig
D) Flume
E) HBase
F) Sqoop
G) Hue

Solutions: