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CCA-500 Dumps PDF - 100% Passing Guarantee on CCA-500 Exam

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CCA-500 Dumps PDF - 100% Passing Guarantee on CCA-500 Exam

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  1. Cloudera Cloudera Certified Administrator for Apache Hadoop CCA-500 Exam QUESTIONS & ANSWERS (FREE - DEMO VERSION) Download Now Updated CCA-500 Exam PFD Demo Buy Full Product Here https://authenticdumps.com/dumps/cca-500/

  2. Question: 1 Your cluster’s mapred-start.xml includes the following parameters <name>mapreduce.map.memory.mb</name> <value>4096</value> <name>mapreduce.reduce.memory.mb</name> <value>8192</value> And any cluster’s yarn-site.xml includes the following parameters <name>yarn.nodemanager.vmen-pmen-raton</name> <value>2.1</value> What is the maximum amount of virtual memory allocated for each map task before YARN will kill its Container? A. 4 GB B. 17.2 GB C. 8.9GB D. 8.2 GB E. 24.6 GB Answer: D Question: 2 Assuming you’re not running HDFS Federatonn 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 actve NameNodes and two Standby NameNodes B. One actve NameNode and one Standby NameNode C. Two actve NameNodes and on Standby NameNode D. Unlimited. HDFS High Availability (HA) is designed to overcome limitatons on the number of NameNodes you can deploy Answer: B Question: 3 Table schemas in Hive are: A. Stored as metadata on the NameNode B. Stored along with the data in HDFS C. Stored in the Metadata D. Stored in ZooKeeper Answer: B

  3. Question: 4 For each YARN jobn the Hadoop framework generates task log fle. Where are Hadoop task log fles stored? A. Cached by the NodeManager managing the job containersn then writen to a log directory on the NameNode B. Cached in the YARN container running the taskn then copied into HDFS on job completon C. In HDFSn in the directory of the user who generates the job D. On the local disk of the slave mode running the task Answer: D Question: 5 You have a cluster running with the fair Scheduler enabled. There are currently no jobs running on the clustern and you submit a job An so that only job A is running on the cluster. A while latern you submit Job B. now Job A and Job B are running on the cluster at the same tme. How will the Fair Scheduler handle these two jobs? A. When Job B gets submitedn it will get assigned tasksn while job A contnues to run with fewer tasks. B. When Job B gets submitedn Job A has to fnish frstn before job B can gets scheduled. C. When Job A gets submitedn it doesn’t consumes all the task slots. D. When Job A gets submitedn it consumes all the task slots. Answer: B Question: 6 Each node in your Hadoop clustern running YARNn has 64GB memory and 24 cores. Your yarn.site.xml has the following confguraton: <property> <name>yarn.nodemanager.resource.memory-mb</name> <value>32768</value> </property> <property> <name>yarn.nodemanager.resource.cpu-vcores</name> <value>12</value> </property> You want YARN to launch no more than 16 containers per node. What should you do? A. Modify yarn-site.xml with the following property: <name>yarn.scheduler.minimum-allocaton-mb</name> <value>2048</value> B. Modify yarn-sites.xml with the following property: <name>yarn.scheduler.minimum-allocaton-mb</name>

  4. <value>4096</value> C. Modify yarn-site.xml with the following property: <name>yarn.nodemanager.resource.cpu-vccores</name> D. No acton is needed: YARN’s dynamic resource allocaton automatcally optmiies the node memory and cores Answer: C

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