Reasons to Choose Our Cloudera CCA175 Exam Dumps

Cloudera CCA175 Exam Dumps - Curated by Subject Matter Experts

Are you tired of getting Cloudera CCA175 dumps with wrong answers? Don’t worry now because our CCA Spark and Hadoop Developer exam dumps are curated by subject matter experts ensuring every question has the right answer

Prepare Your Exam with Cloudera CCA175 Dumps on Any Device

We facilitate you by offering our Cloudera CCA175 exam dumps in three different formats (PDF file, Offline, and Online Practice Test Software)

Self-Assess Your Cloudera Certified Associate Exam Preparation

Self-Assess Your Cloudera CCA175 exam preparation with our CCA175 dumps enriched with various features such as time limit, personalized result page, etc

Eliminate Risk of Failure with Cloudera CCA175 Exam Dumps

Schedule your time wisely to provide yourself sufficient time each day to prepare for the Cloudera CCA175 exam. Make time each day to study in a quiet place, as you'll need to thoroughly cover the material for the CCA Spark and Hadoop Developer exam. Our actual Cloudera Certified Associate exam dumps help you in your preparation. Prepare for the Cloudera CCA175 exam with our CCA175 dumps every day if you want to succeed on your first try.

Q1.

Problem Scenario 92 : You have been given a spark scala application, which is bundled in jar named hadoopexam.jar.

Your application class name is com.hadoopexam.MyTask

You want that while submitting your application should launch a driver on one of the cluster node.

Please complete the following command to submit the application.

spark-submit XXX -master yarn \

YYY SSPARK HOME/lib/hadoopexam.jar 10

ASolution
XXX: -class com.hadoopexam.MyTask

BSolution
XXX: -class com.hadoopexam.MyTask
YYY : --deploy-mode cluster

Answer: B

Q2.

Problem Scenario 96 : Your spark application required extra Java options as below. -XX:+PrintGCDetails-XX:+PrintGCTimeStamps

Please replace the XXX values correctly

./bin/spark-submit --name "My app" --master local[4] --conf spark.eventLog.enabled=talse --conf XXX hadoopexam.jar

ASolution
XXX: Mspark.executoi\extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps'
Notes: ./bin/spark-submit \
--class <maln-class>
--master <master-url> \
--deploy-mode <deploy-mode> \
-conf <key>=<value> \
... # other options

\
[application-arguments]
Here, conf is used to pass the Spark related contigs which are required for the application to run like any specific property(executor memory) or if you want to override the default property which is set in Spark-default.conf.

BSolution
XXX: Mspark.executoi\extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps'
Notes: ./bin/spark-submit \

Answer: A

Q3.

Problem Scenario 95 : You have to run your Spark application on yarn with each executor Maximum heap size to be 512MB and Number of processorcores to allocate on each executor will be 1 and Your main application required three values as input arguments V1 V2 V3.

Please replace XXX, YYY, ZZZ

./bin/spark-submit -class com.hadoopexam.MyTask --master yarn-cluster--num-executors 3 --driver-memory 512m XXX YYY lib/hadoopexam.jarZZZ

ASolution
XXX: -executor-memory 512m YYY: -executor-cores 1
ZZZ : V1 V2 V3
Notes : spark-submit on yarn options Option Description
archives Comma-separated list of archives to be extracted into the working directory of each executor. The path must be globally visible inside your cluster; see Advanced Dependency Management.
executor-cores Number of processor cores to allocate on each executor. Alternatively, you can use the spark.executor.cores property, executor-memory Maximum heap size to allocate to each executor. Alternatively, you can use the spark.executor.memory-property. num-executors Total number of YARN containers to allocate for this application. Alternatively, you can use the spark.executor.instances property. queue YARN queue to submit to. For more information, see Assigning Applications and Queries to Resource Pools. Default: default.

BSolution
XXX: -executor-memory 510m YYY: -executor-cores 1
ZZZ : V2 V6 V1
Notes : spark-submit on yarn options Option Description
archives Comma-separated list of archives to be extracted into the working directory of each executor. The path must be globally visible inside your cluster; see Advanced Dependency Management.
executor-cores Number of processor cores to allocate on each executor. Alternatively, you can use the spark.executor.cores property, executor-memory Maximum heap size to allocate to each executor. Alternatively, you can use the spark.executor.memory-property. num-executors Total number of YARN containers to allocate for this application.

Answer: A

Q4.

Problem Scenario 94 : You have to run your Spark application on yarn with each executor 20GB and number of executors should be 50.Please replace XXX, YYY, ZZZ

export HADOOP_CONF_DIR=XXX

./bin/spark-submit \

-class com.hadoopexam.MyTask \

xxx\

-deploy-mode cluster \ # can be client for client mode

YYY\

222 \

/path/to/hadoopexam.jar \

1000

ASolution
XXX: -master yarn
YYY : -executor-memory 20G
ZZZ: -num-executors 50

BSolution
XXX: -master yarn
YYY : -executor-memory 40G
ZZZ: -num-executors 80

Answer: A

Q5.

Problem Scenario 93 : You have to run your Spark application with locally 8 thread or locally on 8 cores. Replace XXX with correct values.

spark-submit --class com.hadoopexam.MyTask XXX \ -deploy-mode cluster SSPARK_HOME/lib/hadoopexam.jar 10

ASolution
XXX: -master local[8]
Notes : The master URL passed to Spark can be in one of the following formats:
Master URL Meaning
local Run Spark locally with one worker thread (i.e. no parallelism at all}.
local[K] Run Spark locally with K worker threads (ideally, set this to the number of cores on your machine).
The port must be whichever one your is configured to use, which is 5050 by default.Or, for a Mesoscluster using ZooKeeper, use mesos://zk://.... To submit with --deploy-mode cluster, the HOST:PORT should be configured to connect to the MesosClusterDispatcher.
yarn Connect to a YARN cluster in client or cluster mode depending on the value of -deploy-mode. The cluster location will be found based onthe HADOOP CONF DIR or YARN CONF DIR variable.

BSolution
XXX: -master local[8]
Notes : The master URL passed to Spark can be in one of the following formats:
Master URL Meaning
local Run Spark locally with one worker thread (i.e. no parallelism at all}.
local[K] Run Spark locally with K worker threads (ideally, set this to the number of cores on your machine).
local[*] Run Spark locally with as many worker threads as logical cores on your machine.
spark://HOST:PORT Connect to the given Spark standalone cluster master. The port must be whichever one your master is configured to use, which is 7077 by default.
mesos://HOST:PORT Connect to the given Mesos cluster. The port must be whichever one your is configured to use, which is 5050 by default.Or, for a Mesoscluster using ZooKeeper, use mesos://zk://.... To submit with --deploy-mode cluster, the HOST:PORT should be configured to connect to the MesosClusterDispatcher.
yarn Connect to a YARN cluster in client or cluster mode depending on the value of -deploy-mode. The cluster location will be found based onthe HADOOP CONF DIR or YARN CONF DIR variable.

Answer: B

Cloudera CCA175 Exam Candidates Are also Interested In:

How To Get Sample Questions And Answers For Cloudera CCA175 Exam ?,

CCA Spark And Hadoop Developer Mock Test,

Cloudera Certified Associate Exam Dumps,

Are You Looking for More Updated and Actual Cloudera CCA175 Exam Questions?

If you want a more premium set of actual Cloudera CCA175 Exam Questions then you can get them at the most affordable price. Premium Cloudera Certified Associate exam questions are based on the official syllabus of the Cloudera CCA175 exam. They also have a high probability of coming up in the actual CCA Spark and Hadoop Developer exam.
You will also get free updates for 90 days with our premium Cloudera CCA175 exam. If there is a change in the syllabus of Cloudera CCA175 exam our subject matter experts always update it accordingly.

GET CCA175 EXAM PREMIUM ACCESS