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Cloudera CCA-500 - Cloudera Certified Administrator for Apache Hadoop (CCAH)

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Total 60 questions

You observed that the number of spilled records from Map tasks far exceeds the number of map output records. Your child heap size is 1GB and your io.sort.mb value is set to 1000MB. How would you tune your io.sort.mb value to achieve maximum memory to disk I/O ratio?

A.

For a 1GB child heap size an io.sort.mb of 128 MB will always maximize memory to disk I/O

B.

Increase the io.sort.mb to 1GB

C.

Decrease the io.sort.mb value to 0

D.

Tune the io.sort.mb value until you observe that the number of spilled records equals (or is as close to equals) the number of map output records.

You want to node to only swap Hadoop daemon data from RAM to disk when absolutely necessary. What should you do?

A.

Delete the /dev/vmswap file on the node

B.

Delete the /etc/swap file on the node

C.

Set the ram.swap parameter to 0 in core-site.xml

D.

Set vm.swapfile file on the node

E.

Delete the /swapfile file on the node

Your cluster is configured with HDFS and MapReduce version 2 (MRv2) on YARN. What is the result when you execute: hadoop jar SampleJar MyClass on a client machine?

A.

SampleJar.Jar is sent to the ApplicationMaster which allocates a container for SampleJar.Jar

B.

Sample.jar is placed in a temporary directory in HDFS

C.

SampleJar.jar is sent directly to the ResourceManager

D.

SampleJar.jar is serialized into an XML file which is submitted to the ApplicatoionMaster

On a cluster running MapReduce v2 (MRv2) on YARN, a MapReduce job is given a directory of 10 plain text files as its input directory. Each file is made up of 3 HDFS blocks. How many Mappers will run?

A.

We cannot say; the number of Mappers is determined by the ResourceManager

B.

We cannot say; the number of Mappers is determined by the developer

C.

30

D.

3

E.

10

F.

We cannot say; the number of mappers is determined by the ApplicationMaster

Identify two features/issues that YARN is designated to address: (Choose two)

A.

Standardize on a single MapReduce API

B.

Single point of failure in the NameNode

C.

Reduce complexity of the MapReduce APIs

D.

Resource pressure on the JobTracker

E.

Ability to run framework other than MapReduce, such as MPI

F.

HDFS latency

Assuming you’re not running HDFS Federation, what is the maximum number of NameNode daemons you should run on your cluster in order to avoid a “split-brain” scenario with your NameNode when running HDFS High Availability (HA) using Quorum-based storage?

A.

Two active NameNodes and two Standby NameNodes

B.

One active NameNode and one Standby NameNode

C.

Two active NameNodes and on Standby NameNode

D.

Unlimited. HDFS High Availability (HA) is designed to overcome limitations on the number of NameNodes you can deploy

Assume you have a file named foo.txt in your local directory. You issue the following three commands:

Hadoop fs –mkdir input

Hadoop fs –put foo.txt input/foo.txt

Hadoop fs –put foo.txt input

What happens when you issue the third command?

A.

The write succeeds, overwriting foo.txt in HDFS with no warning

B.

The file is uploaded and stored as a plain file named input

C.

You get a warning that foo.txt is being overwritten

D.

You get an error message telling you that foo.txt already exists, and asking you if you would like to overwrite it.

E.

You get a error message telling you that foo.txt already exists. The file is not written to HDFS

F.

You get an error message telling you that input is not a directory

G.

The write silently fails

You are running a Hadoop cluster with MapReduce version 2 (MRv2) on YARN. You consistently see that MapReduce map tasks on your cluster are running slowly because of excessive garbage collection of JVM, how do you increase JVM heap size property to 3GB to optimize performance?

A.

yarn.application.child.java.opts=-Xsx3072m

B.

yarn.application.child.java.opts=-Xmx3072m

C.

mapreduce.map.java.opts=-Xms3072m

D.

mapreduce.map.java.opts=-Xmx3072m