Hortonworks Hortonworks Certifications HADOOP-PR000007 Questions & Answers

• Question 41:

  Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which

  is 100MB in size. The InputFormat for your job is TextInputFormat.

  Determine how many Mappers will run?

  A. 64

  B. 100

  C. 200

  D. 640

  Correct Answer: C

  Explanation: Each file would be split into two as the block size (64 MB) is less than the file size (100 MB),

  so 200 mappers would be running.

  Note:

  If you're not compressing the files then hadoop will process your large files (say 10G), with a number of

  mappers related to the block size of the file.

  Say your block size is 64M, then you will have ~160 mappers processing this 10G file (160*64 ~= 10G).

  Depending on how CPU intensive your mapper logic is, this might be an

  acceptable blocks size, but if you find that your mappers are executing in sub minute times, then you might

  want to increase the work done by each mapper (by increasing the block size to 128, 256, 512m - the

  actual size depends on how you intend to process the data). Reference: http://stackoverflow.com/

• Question 42:

  In Hadoop 2.0, which TWO of the following processes work together to provide automatic failover of the NameNode? Choose 2 answers

  A. ZKFailoverController

  B. ZooKeeper

  C. QuorumManager

  D. JournalNode

  Correct Answer: AD

• Question 43:

  To use a lava user-defined function (UDF) with Pig what must you do?

  A. Define an alias to shorten the function name

  B. Pass arguments to the constructor of UDFs implementation class

  C. Register the JAR file containing the UDF

  D. Put the JAR file into the userandapos;s home folder in HDFS

  Correct Answer: C

• Question 44:

  Table metadata in Hive is:

  A. Stored as metadata on the NameNode.

  B. Stored along with the data in HDFS.

  C. Stored in the Metastore.

  D. Stored in ZooKeeper.

  Correct Answer: C

  Explanation: By default, hive use an embedded Derby database to store metadata information. The metastore is the "glue" between Hive and HDFS. It tells Hive where your data files live in HDFS, what type of data they contain, what tables they belong to, etc.

  The Metastore is an application that runs on an RDBMS and uses an open source ORM layer called DataNucleus, to convert object representations into a relational schema and vice versa. They chose this approach as opposed to storing this information in hdfs as they need the Metastore to be very low latency. The DataNucleus layer allows them to plugin many different RDBMS technologies.

  Note:

  *

  By default, Hive stores metadata in an embedded Apache Derby database, and other client/server

  databases like MySQL can optionally be used.

  *

  features of Hive include:

  Metadata storage in an RDBMS, significantly reducing the time to perform semantic checks during query

  execution.

  Reference: Store Hive Metadata into RDBMS

• Question 45:

  You need to run the same job many times with minor variations. Rather than hardcoding all job configuration options in your drive code, you've decided to have your Driver subclass org.apache.hadoop.conf.Configured and implement the org.apache.hadoop.util.Tool interface.

  Indentify which invocation correctly passes.mapred.job.name with a value of Example to Hadoop?

  A. hadoop "mapred.job.name=Example" MyDriver input output

  B. hadoop MyDriver mapred.job.name=Example input output

  C. hadoop MyDrive 璂 mapred.job.name=Example input output

  D. hadoop setproperty mapred.job.name=Example MyDriver input output

  E. hadoop setproperty ("mapred.job.name=Example") MyDriver input output

  Correct Answer: C

  Explanation: Configure the property using the -D key=value notation:

  -D mapred.job.name='My Job'

  You can list a whole bunch of options by calling the streaming jar with just the -info argument

  Reference: Python hadoop streaming : Setting a job name

• Question 46:

  Your client application submits a MapReduce job to your Hadoop cluster. Identify the Hadoop daemon on which the Hadoop framework will look for an available slot schedule a MapReduce operation.

  A. TaskTracker

  B. NameNode

  C. DataNode

  D. JobTracker

  E. Secondary NameNode

  Correct Answer: D

  Explanation: JobTracker is the daemon service for submitting and tracking MapReduce jobs in Hadoop. There is only One Job Tracker process run on any hadoop cluster. Job Tracker runs on its own JVM process. In a typical production cluster its run on a separate machine. Each slave node is configured with job tracker node location. The JobTracker is single point of failure for the Hadoop MapReduce service. If it goes down, all running jobs are halted. JobTracker in Hadoop performs following actions(from Hadoop Wiki:)

  Client applications submit jobs to the Job tracker. The JobTracker talks to the NameNode to determine the location of the data The JobTracker locates TaskTracker nodes with available slots at or near the data The JobTracker submits the work to the chosen TaskTracker nodes. The TaskTracker nodes are monitored. If they do not submit heartbeat signals often enough, they are deemed to have failed and the work is scheduled on a different TaskTracker. A TaskTracker will notify the JobTracker when a task fails. The JobTracker decides what to do then: it may resubmit the job elsewhere, it may mark that specific record as something to avoid, and it may may even blacklist the TaskTracker as unreliable. When the work is completed, the JobTracker updates its status.

  Client applications can poll the JobTracker for information.

  Reference: 24 Interview Questions and Answers for Hadoop MapReduce developers, What is a JobTracker in Hadoop? How many instances of JobTracker run on a Hadoop Cluster?

• Question 47:

  Consider the following two relations, A and B.

  

  Which Pig statement combines A by its first field and B by its second field?

  A. C = DOIN B BY a1, A by b2;

  B. C = JOIN A by al, B by b2;

  C. C = JOIN A a1, B b2;

  D. C = JOIN A SO, B $1;

  Correct Answer: B

• Question 48:

  Which TWO of the following statements are true regarding Hive? Choose 2 answers A. Useful for data analysts familiar with SQL who need to do ad-hoc queries

  B. Offers real-time queries and row level updates

  C. Allows you to define a structure for your unstructured Big Data

  D. Is a relational database

  Correct Answer: AC

• Question 49:

  Which one of the following statements describes the relationship between the ResourceManager and the ApplicationMaster?

  A. The ApplicationMaster requests resources from the ResourceManager

  B. The ApplicationMaster starts a single instance of the ResourceManager

  C. The ResourceManager monitors and restarts any failed Containers of the ApplicationMaster

  D. The ApplicationMaster starts an instance of the ResourceManager within each Container

  Correct Answer: A

• Question 50:

  In a MapReduce job with 500 map tasks, how many map task attempts will there be?

  A. It depends on the number of reduces in the job.

  B. Between 500 and 1000.

  C. At most 500.

  D. At least 500.

  E. Exactly 500.

  Correct Answer: D

  From Cloudera Training Course: Task attempt is a particular instance of an attempt to execute a task ?There will be at least as many task attempts as there are tasks ?If a task attempt fails, another will be started by the JobTracker ?Speculative execution can also result in more task attempts than completed tasks