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

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Questions # 1:

Which scheduler would you deploy to ensure that your cluster allows short jobs to finish within a reasonable time without starting long-running jobs?

Options:

Complexity Fair Scheduler (CFS)

Capacity Scheduler

Fair Scheduler

FIFO Scheduler

Answer

Explanation

[Reference: http://hadoop.apache.org/docs/r1.2.1/fair_scheduler.html , , ]

Questions # 2:

You have just run a MapReduce job to filter user messages to only those of a selected geographical region. The output for this job is in a directory named westUsers, located just below your home directory in HDFS. Which command gathers these into a single file on your local file system?

Options:

Hadoop fs –getmerge –R westUsers.txt

Hadoop fs –getemerge westUsers westUsers.txt

Hadoop fs –cp westUsers/* westUsers.txt

Hadoop fs –get westUsers westUsers.txt

Answer

Questions # 3:

You are working on a project where you need to chain together MapReduce, Pig jobs. You also need the ability to use forks, decision points, and path joins. Which ecosystem project should you use to perform these actions?

Options:

Oozie

ZooKeeper

HBase

Sqoop

HUE

Answer

Questions # 4:

You are running a Hadoop cluster with a NameNode on host mynamenode, a secondary NameNode on host mysecondarynamenode and several DataNodes.

Which best describes how you determine when the last checkpoint happened?

Options:

Execute hdfs namenode –report on the command line and look at the Last Checkpoint information

Execute hdfs dfsadmin –saveNamespace on the command line which returns to you the last checkpoint value in fstime file

Connect to the web UI of the Secondary NameNode (http://mysecondary:50090/) and look at the “Last Checkpoint” information

Connect to the web UI of the NameNode (http://mynamenode:50070) and look at the “Last Checkpoint” information

Answer

Explanation

[Reference: https://www.inkling.com/read/hadoop-definitive-guide-tom-white-3rd/chapter-10/hdfs , , ]

Questions # 5:

Your Hadoop cluster contains nodes in three racks. You have not configured the dfs.hosts property in the NameNode’s configuration file. What results?

Options:

The NameNode will update the dfs.hosts property to include machines running the DataNode daemon on the next NameNode reboot or with the command dfsadmin –refreshNodes

No new nodes can be added to the cluster until you specify them in the dfs.hosts file

Any machine running the DataNode daemon can immediately join the cluster

Presented with a blank dfs.hosts property, the NameNode will permit DataNodes specified in mapred.hosts to join the cluster

Answer

Questions # 6:

Your cluster implements HDFS High Availability (HA). Your two NameNodes are named nn01 and nn02. What occurs when you execute the command: hdfs haadmin –failover nn01 nn02?

Options:

nn02 is fenced, and nn01 becomes the active NameNode

nn01 is fenced, and nn02 becomes the active NameNode

nn01 becomes the standby NameNode and nn02 becomes the active NameNode

nn02 becomes the standby NameNode and nn01 becomes the active NameNode

Answer

Explanation

Explanation:

failover – initiate a failover between two NameNodes

This subcommand causes a failover from the first provided NameNode to the second. If the first

NameNode is in the Standby state, this command simply transitions the second to the Active state without error. If the first NameNode is in the Active state, an attempt will be made to gracefully transition it to the Standby state. If this fails, the fencing methods (as configured by dfs.ha.fencing.methods) will be attempted in order until one of the methods succeeds. Only after this process will the second NameNode be transitioned to the Active state. If no fencing method succeeds, the second NameNode will not be transitioned to the Active state, and an error will be returned.

Questions # 7:

You suspect that your NameNode is incorrectly configured, and is swapping memory to disk. Which Linux commands help you to identify whether swapping is occurring? (Select all that apply)

Options:

free

memcat

top

jps

vmstat

swapinfo

Answer

A, D, F

Explanation

[Reference: http://www.cyberciti.biz/faq/linux-check-swap-usage-command/ , , ]

Questions # 8:

You are planning a Hadoop cluster and considering implementing 10 Gigabit Ethernet as the network fabric. Which workloads benefit the most from faster network fabric?

Options:

When your workload generates a large amount of output data, significantly larger than the amount of intermediate data

When your workload consumes a large amount of input data, relative to the entire capacity if HDFS

When your workload consists of processor-intensive tasks

When your workload generates a large amount of intermediate data, on the order of the input data itself

Answer

Questions # 9:

Which two are features of Hadoop’s rack topology? (Choose two)

Options:

Configuration of rack awareness is accomplished using a configuration file. You cannot use a rack topology script.

Hadoop gives preference to intra-rack data transfer in order to conserve bandwidth

Rack location is considered in the HDFS block placement policy

HDFS is rack aware but MapReduce daemon are not

Even for small clusters on a single rack, configuring rack awareness will improve performance

Answer

B, C

Questions # 10:

You have a cluster running with a FIFO scheduler enabled. You submit a large job A to the cluster, which you expect to run for one hour. Then, you submit job B to the cluster, which you expect to run a couple of minutes only.

You submit both jobs with the same priority.

Which two best describes how FIFO Scheduler arbitrates the cluster resources for job and its tasks? (Choose two)

Options:

Because there is a more than a single job on the cluster, the FIFO Scheduler will enforce a limit on the percentage of resources allocated to a particular job at any given time

Tasks are scheduled on the order of their job submission

The order of execution of job may vary

Given job A and submitted in that order, all tasks from job A are guaranteed to finish before all tasks from job B

The FIFO Scheduler will give, on average, and equal share of the cluster resources over the job lifecycle

The FIFO Scheduler will pass an exception back to the client when Job B is submitted, since all slots on the cluster are use

Answer

A, D

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