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

HMaster

ResourceManager

TaskManager

JobTracker

NameNode

DataNode

YARN doesn’t configure a default scheduler, you must first assign an appropriate scheduler class in yarn-site.xml

Capacity Scheduler

Fair Scheduler

FIFO Scheduler

Automatically configures permissions for log files at & MAPRED_LOG_DIR/userlogs

Creates users for hdfs and mapreduce to facilitate role assignment

Creates directories for temp, hdfs, and mapreduce with the correct permissions

Creates a set of pre-configured Kerberos keytab files and their permissions

Creates and configures your kdc with default cluster values

Delete the /dev/vmswap file on the node

Delete the /etc/swap file on the node

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

Set vm.swapfile file on the node

Delete the /swapfile file on the node

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

Two active NameNodes and two Standby NameNodes

One active NameNode and one Standby NameNode

Two active NameNodes and on Standby NameNode

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

It only keeps track of which NameNode is Active at any given time

It monitors an NFS mount point and reports if the mount point disappears

It both keeps track of which NameNode is Active at any given time, and manages the Edits file. Which is a log of changes to the HDFS filesystem

If only manages the Edits file, which is log of changes to the HDFS filesystem

Clients connect to ZooKeeper to determine which NameNode is Active

Run hdfs fs –du / and locate the DFS Remaining value

Run hdfs dfsadmin –report and locate the DFS Remaining value

Run hdfs dfs / and subtract NDFS Used from configured Capacity

Connect to http://mynamenode:50070/dfshealth.jsp and locate the DFS remaining value

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

Sample.jar is placed in a temporary directory in HDFS

SampleJar.jar is sent directly to the ResourceManager

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

The DataNode JVM on one host is not active

Because your under-replicated blocks count matches the Live Nodes, one node is dead, and your DFS Used % equals 0%, you can’t be certain that your cluster has all the data you’ve written it.

Your cluster has lost all HDFS data which had bocks stored on the dead DatNode

The HDFS cluster is in safe mode

Configure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.resource.cpu-vcores so that ApplicationMaster container allocations match the capacity you require.

You don’t need to configure or balance these properties in YARN as YARN dynamically balances resource management capabilities on your cluster

Configure mapred.tasktracker.map.tasks.maximum and mapred.tasktracker.reduce.tasks.maximum ub yarn-site.xml to match your cluster’s capacity set by the yarn-scheduler.minimum-allocation

Configure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu-vcores to match the capacity you require under YARN for each NodeManager

Yarn application –refreshJobHistory

Yarn application –kill application_1374638600275_0109

Yarn rmadmin –refreshQueue

Yarn rmadmin –kill application_1374638600275_0109

Configure the NodeManager to enable MapReduce services on YARN by setting the following property in yarn-site.xml:

< name > yarn.nodemanager.hostname < /name >

< value > your_nodeManager_shuffle < /value >

Configure the NodeManager hostname and enable node services on YARN by setting the following property in yarn-site.xml:

< name > yarn.nodemanager.hostname < /name >

< value > your_nodeManager_hostname < /value >

Configure a default scheduler to run on YARN by setting the following property in mapred-site.xml:

< name > mapreduce.jobtracker.taskScheduler < /name >

< Value > org.apache.hadoop.mapred.JobQueueTaskScheduler < /value >

Configure the number of map tasks per jon YARN by setting the following property in mapred:

< name > mapreduce.job.maps < /name >

< value > 2 < /value >

Configure the ResourceManager hostname and enable node services on YARN by setting the following property in yarn-site.xml:

< name > yarn.resourcemanager.hostname < /name >

< value > your_resourceManager_hostname < /value >

Configure MapReduce as a Framework running on YARN by setting the following property in mapred-site.xml:

< name > mapreduce.framework.name < /name >

< value > yarn < /value >

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

ApplicationManager

JobTracker

ApplicationMaster

JobHistoryServer

ResoureManager

NodeManager