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2021 Sep CCA-500 question
Q31. A slave node in your cluster has 4 TB hard drives installed (4 x 2TB). The DataNode is configured to store HDFS blocks on all disks. You set the value of the dfs.datanode.du.reserved parameter to 100 GB. How does this alter HDFS block storage?
A. 25GB on each hard drive may not be used to store HDFS blocks
B. 100GB on each hard drive may not be used to store HDFS blocks
C. All hard drives may be used to store HDFS blocks as long as at least 100 GB in total is available on the node
D. A maximum if 100 GB on each hard drive may be used to store HDFS blocks
Answer: B
Q32. Which YARN daemon or service negotiations map and reduce Containers from the Scheduler, tracking their status and monitoring progress?
A. NodeManager
B. ApplicationMaster
C. ApplicationManager
D. ResourceManager
Answer: B
Explanation: Reference:http://www.devx.com/opensource/intro-to-apache-mapreduce-2-yarn.html(See resource manager)
Q33. 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.
Answer: D
Renovate CCA-500 exam answers:
Q34. In CDH4 and later, which file contains a serialized form of all the directory and files inodes in the filesystem, giving the NameNode a persistent checkpoint of the filesystem metadata?
A. fstime
B. VERSION
C. Fsimage_N (where N reflects transactions up to transaction ID N)
D. Edits_N-M (where N-M transactions between transaction ID N and transaction ID N)
Answer: C
Explanation: Reference:http://mikepluta.com/tag/namenode/
Q35. 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-ration</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. 8.9 GB
D. 8.2 GB
E. 24.6 GB
Answer: D
Q36. You want to understand more about how users browse your public website. For example, you want to know which pages they visit prior to placing an order. You have a server farm of 200 web servers hosting your website. Which is the most efficient process to gather these web server across logs into your Hadoop cluster analysis?
A. Sample the web server logs web servers and copy them into HDFS using curl
B. Ingest the server web logs into HDFS using Flume
C. Channel these clickstreams into Hadoop using Hadoop Streaming
D. Import all user clicks from your OLTP databases into Hadoop using Sqoop
E. Write a MapReeeduce job with the web servers for mappers and the Hadoop cluster nodes for reducers
Answer: B
Explanation: Apache Flume is a service for streaming logs into Hadoop.
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming data into the Hadoop Distributed File System (HDFS). It has a simple and flexible architecture based on streaming data flows; and is robust and fault tolerant with tunable reliability mechanisms for failover and recovery.