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Cloudera Hadoop Developer Certification Questions and Answer (Dumps and Practice Questions)
Question : If a file which is MB how much space block space it will used ?
1. 33 MB
2. 64 MB
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4. None of the Above
Correct Answer
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Although files are split into 64MB or 128 MBblocks, if a file is smaller than this the full
64 MB or 128 MB will not be used.
Question : How blocks are stored in HDFS
1. As a binary file
2. As a decoded file
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4. Stored as archived
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Blocks are stored as standard files on the DataNodes, in a set of directories apecified in
Hadoop's configuration files
Question : Without the metadata on the NameNode file can be recovered ?
1. True
2. False
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Without the metadata on the NameNode, there is no way to access the files in the HDFS cluster
Related Questions
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.