Mapr (HP) Hadoop Developer Certification Questions and Answers (Dumps and Practice Questions)

Question : In hadoop streaming job, can we use following as mapper

-mapper "cut -f1 | sed s/foo/bar/g"

1. True
2. False

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Explanation: Currently this does not work and gives an "java.io.IOException: Broken pipe" error. This is probably a bug that needs to be investigated.




Question : Is below command valid for Hadoop Streaming Job
hadoop jar hadoop-streaming.jar -input '/user/foo/dir1' -input '/user/foo/dir2'

1. Yes
2. No

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Explanation: You can specify multiple input directories with multiple '-input' options:

hadoop jar hadoop-streaming.jar -input '/user/foo/dir1' -input '/user/foo/dir2'




Question : Select the correct statement with regards to Hadoop streaming applications
A. A streaming process can use the stderr to emit counter information. reporter:counter:,, should be sent to stderr to update the counter.
B. A streaming process can use the stderr to emit status information. To set a status, reporter:status: should be sent to stderr.
C. You can use the record reader StreamXmlRecordReader to process XML documents.
D. During the execution of a streaming job, the names of the "mapred" parameters are transformed. The dots ( . ) become underscores ( _ ). For example, mapred.job.id becomes
mapred_job_id and mapred.jar becomes mapred_jar. In your code, use the parameter names with the underscores.

1. A,B,C
2. B,C,D
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4. A,B,D
5. A,B,C,D

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Explanation:

Related Questions

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Question : Because of OutOfMemory a Map or Reduce Task can crash, How does Hadoop MapReduce v (MRv)
handle JVMs when a new MapReduce job is started on a cluster?

1. The TaskTracker may or may not use same JVM for each task it manages on that node
2. The TaskTracker reuse the same JVM for each task it manages on that node
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4. The TaskTracker spawns a new JVM for each task it manages on that node


Question : You have configured Hadoop cluster with MR. And, you have a directory called HadoopExam in HDFS containing three files: Exam and Exam.
You submit a job to the cluster, using that directory as the input directory.
A few seconds after you have submitted the job, a user start copying a large file, Exam3,
into the directory. Select the correct statement?

1. All files Exam1, Exam2 and Exam3 will be processed by the job
2. Only files Exam1, and Exam2 will be processed by the job
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4. Only files Exam3 will be processed by the job


Question :
As you know Hadoop cluster is made of Multiple nodes and each file is divided in multiple blocks and stored in different nodes.
For this you need to able to serialize your data and you use Writable interface for this, select the correct statement for the
Writable interface.

1. Writable is a class that all keys and values in MapReduce must extend. Classes extending this interface must implement methods for serializing and deserializing themselves.
2. Writable is an class that all keys and values in MapReduce must extend. Classes extending this interface must not implement methods for serializing and deserializing themselves until they want to customize it.
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4. Writable is an interface that all values in MapReduce must implement. Classes implementing this interface must implement methods for serializing and deserializing themselves.


Question :
You have written a MapReduce job, and in the Reducer you want the data to be adjusted from multiple reducers before
writing to the HDFS,Is it possible that reduce tasks to communicate with each other and can talk to each other? .

1. Yes, all reducer task runs can share the data by doing proper configuration
2. Yes, each reduce task runs independently and in isolation, by creating a shared file reducer can communicate with each other
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4. It all depends on file size created if it is smaller than block size then it is possible


Question : All HadoopExam website subscribers information is stored in the MySQL database,
Which tool is best suited to import a portion of a subscribers information every day as files into HDFS,
and generate Java classes to interact with that imported data?

1. Hive
2. Pig
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4. Flume


Question :A client application of HadoopExam creates an HDFS file named HadoopExam.txt with a replication factor of .
Identify which best describes the file access rules in HDFS if the file has a single block that is stored on data nodes C1, C2, C3, C4 and C5?

1. The file can not be accessed if at least one of the DataNodes storing the block is un-available.
2. The file can be accessed if at least one of the DataNodes storing the block is available and client connected to that node only.
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4. The file can be accessed if at least one of the DataNodes storing the block is available and even NameNode is crashed.