Exam code : CCA-410
Exam name : Cloudera Certified Administrator for Apache Hadoop (CCAH)
Which two updates occur when a client application opens a stream to begin a file write on a
cluster running MapReduce v1 (MRv1)?
A. Once the write stream closes on the DataNode, the DataNode immediately initiates a
black report to the NameNode.
B. The change is written to the NameNode disk.
C. The metadata in the RAM on the NameNode is flushed to disk.
D. The metadata in RAM on the NameNode is flushed disk.
E. The metadata in RAM on the NameNode is updated.
F. The change is written to the edits file.
Answer: E,F
For a MapReduce job, on a cluster running MapReduce v1 (MRv1), what’s the relationship
between tasks and task templates?
A. There are always at least as many task attempts as there are tasks.
B. There are always at most as many tasks attempts as there are tasks.
C. There are always exactly as many task attempts as there are tasks.
D. The developer sets the number of task attempts on job submission.
Answer: A
What action occurs automatically on a cluster when a DataNode is marked as dead?
A. The NameNode forces re-replication of all the blocks which were stored on the dead
DataNode.
B. The next time a client submits job that requires blocks from the dead DataNode, the
JobTracker receives no heart beats from the DataNode. The JobTracker tells the
NameNode that the DataNode is dead, which triggers block re-replication on the cluster.
C. The replication factor of the files which had blocks stored on the dead DataNode is
temporarily reduced, until the dead DataNode is recovered and returned to the cluster.
D. The NameNode informs the client which write the blocks that are no longer available;
Question No : 1
Question No : 2
Question No : 3
the client then re-writes the blocks to a different DataNode.
Answer: A
Explanation: How NameNode Handles data node failures?
NameNode periodically receives a Heartbeat and a Blockreport from each of the
DataNodes in the cluster. Receipt of a Heartbeat implies that the DataNode is functioning
properly. A Blockreport contains a list of all blocks on a DataNode. When NameNode
notices that it has not recieved a hearbeat message from a data node after a certain
amount of time, the data node is marked as dead. Since blocks will be under replicated the
system begins replicating the blocks that were stored on the dead datanode. The
NameNode Orchestrates the replication of data blocks from one datanode to another. The
replication data transfer happens directly between datanodes and the data never passes
through the namenode.
Note:If the Name Node stops receiving heartbeats from a Data Node it presumes it to be
dead and any data it had to be gone as well. Based on the block reports it had been
receiving from the dead node, the Name Node knows which copies of blocks died along
with the node and can make the decision to re-replicate those blocks to other Data Nodes.
It will also consult the Rack Awareness data in order to maintain thetwo copies in one rack,
one copy in another rackreplica rule when deciding which Data Node should receive a new
copy of the blocks.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, How
NameNode Handles data node failures’
How does the NameNode know DataNodes are available on a cluster running MapReduce
v1 (MRv1)
A. DataNodes listed in the dfs.hosts file. The NameNode uses as the definitive list of
available DataNodes.
B. DataNodes heartbeat in the master on a regular basis.
C. The NameNode broadcasts a heartbeat on the network on a regular basis, and
DataNodes respond.
D. The NameNode send a broadcast across the network when it first starts, and
DataNodes respond.
Question No : 4
Answer: B
Explanation: How NameNode Handles data node failures?
NameNode periodically receives a Heartbeat and a Blockreport from each of the
DataNodes in the cluster. Receipt of a Heartbeat implies that the DataNode is functioning
properly. A Blockreport contains a list of all blocks on a DataNode. When NameNode
notices that it has not recieved a hearbeat message from a data node after a certain
amount of time, the data node is marked as dead. Since blocks will be under replicated the
system begins replicating the blocks that were stored on the dead datanode. The
NameNode Orchestrates the replication of data blocks from one datanode to another. The
replication data transfer happens directly between datanodes and the data never passes
through the namenode.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, How
NameNode Handles data node failures?
Which three distcp features can you utilize on a Hadoop cluster?
A. Use distcp to copy files only between two clusters or more. You cannot use distcp to
copy data between directories inside the same cluster.
B. Use distcp to copy HBase table files.
C. Use distcp to copy physical blocks from the source to the target destination in your
cluster.
D. Use distcp to copy data between directories inside the same cluster.
E. Use distcp to run an internal MapReduce job to copy files.
Answer: B,D,E
Explanation:
DistCp (distributed copy) is a tool used for large inter/intra-cluster copying. It uses
Map/Reduce to effect its distribution, error handling and recovery, and reporting. It expands
a list of files and directories into input to map tasks, each of which will copy a partition of
the files specified in the source list. Its Map/Reduce pedigree has endowed it with some
quirks in both its semantics and execution.
Reference: Hadoop DistCp Guide
Question No : 5
How does HDFS Federation help HDFS Scale horizontally?
A. HDFS Federation improves the resiliency of HDFS in the face of network issues by
removing the NameNode as a single-point-of-failure.
B. HDFS Federation allows the Standby NameNode to automatically resume the services
of an active NameNode.
C. HDFS Federation provides cross-data center (non-local) support for HDFS, allowing a
cluster administrator to split the Block Storage outside the local cluster.
D. HDFS Federation reduces the load on any single NameNode by using the multiple,
independent NameNode to manage individual pars of the filesystem namespace.
Answer: D
Explanation: HDFS FederationIn order to scale the name service horizontally, federation
uses multiple independent Namenodes/Namespaces. The Namenodes are federated, that
is, the Namenodes are independent and don’t require coordination with each other. The
datanodes are used as common storage for blocks by all the Namenodes. Each datanode
registers with all the Namenodes in the cluster. Datanodes send periodic heartbeats and
block reports and handles commands from the Namenodes.
Reference: Apache Hadoop 2.0.2-alpha
http://hadoop.apache.org/docs/current/
Choose which best describe a Hadoop cluster's block size storage parameters once you
set the HDFS default block size to 64MB?
A. The block size of files in the cluster can be determined as the block is written.
B. The block size of files in the Cluster will all be multiples of 64MB.
C. The block size of files in the duster will all at least be 64MB.
D. The block size of files in the cluster will all be the exactly 64MB.
Answer: D
Explanation:
Note: What is HDFS Block size? How is it different from traditional file system block size?
In HDFS data is split into blocks and distributed across multiple nodes in the cluster. Each
block is typically 64Mb or 128Mb in size. Each block is replicated multiple times. Default is
to replicate each block three times. Replicas are stored on different nodes. HDFS utilizes
the local file system to store each HDFS block as a separate file. HDFS Block size can not
be compared with the traditional file system block size.
Which MapReduce daemon instantiates user code, and executes map and reduce tasks on
a cluster running MapReduce v1 (MRv1)?
A. NameNode
B. DataNode
C. JobTracker
D. TaskTracker
E. ResourceManager
F. ApplicationMaster
G. NodeManager
Answer: D
Explanation: A TaskTracker is a slave node daemon in the cluster that accepts tasks
(Map, Reduce and Shuffle operations) from a JobTracker. There is only One Task Tracker
process run on any hadoop slave node. Task Tracker runs on its own JVM process. Every
TaskTracker is configured with a set of slots, these indicate the number of tasks that it can
accept. The TaskTracker starts a separate JVM processes to do the actual work (called as
Task Instance) this is to ensure that process failure does not take down the task tracker.
The TaskTracker monitors these task instances, capturing the output and exit codes. When
the Task instances finish, successfully or not, the task tracker notifies the JobTracker. The
TaskTrackers also send out heartbeat messages to the JobTracker, usually every few
minutes, to reassure the JobTracker that it is still alive. These message also inform the
JobTracker of the number of available slots, so the JobTracker can stay up to date with
where in the cluster work can be delegated.
Question No : 8
Note: How many Daemon processes run on a Hadoop system?
Hadoop is comprised of five separate daemons. Each of these daemon run in its own JVM.
Following 3 Daemons run on Master
nodes NameNode - This daemon stores and maintains the metadata for HDFS.
Secondary NameNode - Performs housekeeping functions for the NameNode.
JobTracker - Manages MapReduce jobs, distributes individual tasks to machines running
the Task Tracker.
Following 2 Daemons run on each Slave nodes
DataNode – Stores actual HDFS data blocks.
TaskTracker - Responsible for instantiating and monitoring individual Map and Reduce
tasks.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, What is
a Task Tracker in Hadoop? How many instances of TaskTracker run on a Hadoop Cluster
What two processes must you do if you are running a Hadoop cluster with a single
NameNode and six DataNodes, and you want to change a configuration parameter so that
it affects all six DataNodes.
A. You must restart the NameNode daemon to apply the changes to the cluster
B. You must restart all six DataNode daemons to apply the changes to the cluster.
C. You don't need to restart any daemon, as they will pick up changes automatically.
D. You must modify the configuration files on each of the six DataNode machines.
E. You must modify the configuration files on only one of the DataNode machine
F. You must modify the configuration files on the NameNode only. DataNodes read their
configuration from the master nodes.
Answer: A,F
Identify the function performed by the Secondary NameNode daemon on a cluster configured to run with a single NameNode.
A. In this configuration, the Secondary NameNode performs a checkpoint operation on the
files by the NameNode.
B. In this configuration, the Secondary NameNode is standby NameNode, ready to failover
and provide high availability.
C. In this configuration, the Secondary NameNode performs deal-time backups of the
NameNode.
D. In this configuration, the Secondary NameNode servers as alternate data channel for
clients to reach HDFS, should the NameNode become too busy.
Answer: A
Explanation: The term "secondary name-node" is somewhat misleading. It is not a namenode
in the sense that data-nodes cannot connect to the secondary name-node, and in no
event it can replace the primary name-node in case of its failure.
The only purpose of the secondary name-node is to perform periodic checkpoints. The
secondary name-node periodically downloads current name-node image and edits log files,
joins them into new image and uploads the new image back to the (primary and the only)
name-node.
So if the name-node fails and you can restart it on the same physical node then there is no
need to shutdown data-nodes, just the name-node need to be restarted. If you cannot use
the old node anymore you will need to copy the latest image somewhere else. The latest
image can be found either on the node that used to be the primary before failure if
available; or on the secondary name-node. The latter will be the latest checkpoint without
subsequent edits logs, that is the most recent name space modifications may be missing
there. You will also need to restart the whole cluster in this case.
Reference: Hadoop Wiki, What is the purpose of the secondary name-node?
Exam name : Cloudera Certified Administrator for Apache Hadoop (CCAH)
Which two updates occur when a client application opens a stream to begin a file write on a
cluster running MapReduce v1 (MRv1)?
A. Once the write stream closes on the DataNode, the DataNode immediately initiates a
black report to the NameNode.
B. The change is written to the NameNode disk.
C. The metadata in the RAM on the NameNode is flushed to disk.
D. The metadata in RAM on the NameNode is flushed disk.
E. The metadata in RAM on the NameNode is updated.
F. The change is written to the edits file.
Answer: E,F
For a MapReduce job, on a cluster running MapReduce v1 (MRv1), what’s the relationship
between tasks and task templates?
A. There are always at least as many task attempts as there are tasks.
B. There are always at most as many tasks attempts as there are tasks.
C. There are always exactly as many task attempts as there are tasks.
D. The developer sets the number of task attempts on job submission.
Answer: A
What action occurs automatically on a cluster when a DataNode is marked as dead?
A. The NameNode forces re-replication of all the blocks which were stored on the dead
DataNode.
B. The next time a client submits job that requires blocks from the dead DataNode, the
JobTracker receives no heart beats from the DataNode. The JobTracker tells the
NameNode that the DataNode is dead, which triggers block re-replication on the cluster.
C. The replication factor of the files which had blocks stored on the dead DataNode is
temporarily reduced, until the dead DataNode is recovered and returned to the cluster.
D. The NameNode informs the client which write the blocks that are no longer available;
Question No : 1
Question No : 2
Question No : 3
the client then re-writes the blocks to a different DataNode.
Answer: A
Explanation: How NameNode Handles data node failures?
NameNode periodically receives a Heartbeat and a Blockreport from each of the
DataNodes in the cluster. Receipt of a Heartbeat implies that the DataNode is functioning
properly. A Blockreport contains a list of all blocks on a DataNode. When NameNode
notices that it has not recieved a hearbeat message from a data node after a certain
amount of time, the data node is marked as dead. Since blocks will be under replicated the
system begins replicating the blocks that were stored on the dead datanode. The
NameNode Orchestrates the replication of data blocks from one datanode to another. The
replication data transfer happens directly between datanodes and the data never passes
through the namenode.
Note:If the Name Node stops receiving heartbeats from a Data Node it presumes it to be
dead and any data it had to be gone as well. Based on the block reports it had been
receiving from the dead node, the Name Node knows which copies of blocks died along
with the node and can make the decision to re-replicate those blocks to other Data Nodes.
It will also consult the Rack Awareness data in order to maintain thetwo copies in one rack,
one copy in another rackreplica rule when deciding which Data Node should receive a new
copy of the blocks.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, How
NameNode Handles data node failures’
How does the NameNode know DataNodes are available on a cluster running MapReduce
v1 (MRv1)
A. DataNodes listed in the dfs.hosts file. The NameNode uses as the definitive list of
available DataNodes.
B. DataNodes heartbeat in the master on a regular basis.
C. The NameNode broadcasts a heartbeat on the network on a regular basis, and
DataNodes respond.
D. The NameNode send a broadcast across the network when it first starts, and
DataNodes respond.
Question No : 4
Answer: B
Explanation: How NameNode Handles data node failures?
NameNode periodically receives a Heartbeat and a Blockreport from each of the
DataNodes in the cluster. Receipt of a Heartbeat implies that the DataNode is functioning
properly. A Blockreport contains a list of all blocks on a DataNode. When NameNode
notices that it has not recieved a hearbeat message from a data node after a certain
amount of time, the data node is marked as dead. Since blocks will be under replicated the
system begins replicating the blocks that were stored on the dead datanode. The
NameNode Orchestrates the replication of data blocks from one datanode to another. The
replication data transfer happens directly between datanodes and the data never passes
through the namenode.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, How
NameNode Handles data node failures?
Which three distcp features can you utilize on a Hadoop cluster?
A. Use distcp to copy files only between two clusters or more. You cannot use distcp to
copy data between directories inside the same cluster.
B. Use distcp to copy HBase table files.
C. Use distcp to copy physical blocks from the source to the target destination in your
cluster.
D. Use distcp to copy data between directories inside the same cluster.
E. Use distcp to run an internal MapReduce job to copy files.
Answer: B,D,E
Explanation:
DistCp (distributed copy) is a tool used for large inter/intra-cluster copying. It uses
Map/Reduce to effect its distribution, error handling and recovery, and reporting. It expands
a list of files and directories into input to map tasks, each of which will copy a partition of
the files specified in the source list. Its Map/Reduce pedigree has endowed it with some
quirks in both its semantics and execution.
Reference: Hadoop DistCp Guide
Question No : 5
How does HDFS Federation help HDFS Scale horizontally?
A. HDFS Federation improves the resiliency of HDFS in the face of network issues by
removing the NameNode as a single-point-of-failure.
B. HDFS Federation allows the Standby NameNode to automatically resume the services
of an active NameNode.
C. HDFS Federation provides cross-data center (non-local) support for HDFS, allowing a
cluster administrator to split the Block Storage outside the local cluster.
D. HDFS Federation reduces the load on any single NameNode by using the multiple,
independent NameNode to manage individual pars of the filesystem namespace.
Answer: D
Explanation: HDFS FederationIn order to scale the name service horizontally, federation
uses multiple independent Namenodes/Namespaces. The Namenodes are federated, that
is, the Namenodes are independent and don’t require coordination with each other. The
datanodes are used as common storage for blocks by all the Namenodes. Each datanode
registers with all the Namenodes in the cluster. Datanodes send periodic heartbeats and
block reports and handles commands from the Namenodes.
Reference: Apache Hadoop 2.0.2-alpha
http://hadoop.apache.org/docs/current/
Choose which best describe a Hadoop cluster's block size storage parameters once you
set the HDFS default block size to 64MB?
A. The block size of files in the cluster can be determined as the block is written.
B. The block size of files in the Cluster will all be multiples of 64MB.
C. The block size of files in the duster will all at least be 64MB.
D. The block size of files in the cluster will all be the exactly 64MB.
Answer: D
Explanation:
Note: What is HDFS Block size? How is it different from traditional file system block size?
In HDFS data is split into blocks and distributed across multiple nodes in the cluster. Each
block is typically 64Mb or 128Mb in size. Each block is replicated multiple times. Default is
to replicate each block three times. Replicas are stored on different nodes. HDFS utilizes
the local file system to store each HDFS block as a separate file. HDFS Block size can not
be compared with the traditional file system block size.
Which MapReduce daemon instantiates user code, and executes map and reduce tasks on
a cluster running MapReduce v1 (MRv1)?
A. NameNode
B. DataNode
C. JobTracker
D. TaskTracker
E. ResourceManager
F. ApplicationMaster
G. NodeManager
Answer: D
Explanation: A TaskTracker is a slave node daemon in the cluster that accepts tasks
(Map, Reduce and Shuffle operations) from a JobTracker. There is only One Task Tracker
process run on any hadoop slave node. Task Tracker runs on its own JVM process. Every
TaskTracker is configured with a set of slots, these indicate the number of tasks that it can
accept. The TaskTracker starts a separate JVM processes to do the actual work (called as
Task Instance) this is to ensure that process failure does not take down the task tracker.
The TaskTracker monitors these task instances, capturing the output and exit codes. When
the Task instances finish, successfully or not, the task tracker notifies the JobTracker. The
TaskTrackers also send out heartbeat messages to the JobTracker, usually every few
minutes, to reassure the JobTracker that it is still alive. These message also inform the
JobTracker of the number of available slots, so the JobTracker can stay up to date with
where in the cluster work can be delegated.
Question No : 8
Note: How many Daemon processes run on a Hadoop system?
Hadoop is comprised of five separate daemons. Each of these daemon run in its own JVM.
Following 3 Daemons run on Master
nodes NameNode - This daemon stores and maintains the metadata for HDFS.
Secondary NameNode - Performs housekeeping functions for the NameNode.
JobTracker - Manages MapReduce jobs, distributes individual tasks to machines running
the Task Tracker.
Following 2 Daemons run on each Slave nodes
DataNode – Stores actual HDFS data blocks.
TaskTracker - Responsible for instantiating and monitoring individual Map and Reduce
tasks.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, What is
a Task Tracker in Hadoop? How many instances of TaskTracker run on a Hadoop Cluster
What two processes must you do if you are running a Hadoop cluster with a single
NameNode and six DataNodes, and you want to change a configuration parameter so that
it affects all six DataNodes.
A. You must restart the NameNode daemon to apply the changes to the cluster
B. You must restart all six DataNode daemons to apply the changes to the cluster.
C. You don't need to restart any daemon, as they will pick up changes automatically.
D. You must modify the configuration files on each of the six DataNode machines.
E. You must modify the configuration files on only one of the DataNode machine
F. You must modify the configuration files on the NameNode only. DataNodes read their
configuration from the master nodes.
Answer: A,F
Identify the function performed by the Secondary NameNode daemon on a cluster configured to run with a single NameNode.
A. In this configuration, the Secondary NameNode performs a checkpoint operation on the
files by the NameNode.
B. In this configuration, the Secondary NameNode is standby NameNode, ready to failover
and provide high availability.
C. In this configuration, the Secondary NameNode performs deal-time backups of the
NameNode.
D. In this configuration, the Secondary NameNode servers as alternate data channel for
clients to reach HDFS, should the NameNode become too busy.
Answer: A
Explanation: The term "secondary name-node" is somewhat misleading. It is not a namenode
in the sense that data-nodes cannot connect to the secondary name-node, and in no
event it can replace the primary name-node in case of its failure.
The only purpose of the secondary name-node is to perform periodic checkpoints. The
secondary name-node periodically downloads current name-node image and edits log files,
joins them into new image and uploads the new image back to the (primary and the only)
name-node.
So if the name-node fails and you can restart it on the same physical node then there is no
need to shutdown data-nodes, just the name-node need to be restarted. If you cannot use
the old node anymore you will need to copy the latest image somewhere else. The latest
image can be found either on the node that used to be the primary before failure if
available; or on the secondary name-node. The latter will be the latest checkpoint without
subsequent edits logs, that is the most recent name space modifications may be missing
there. You will also need to restart the whole cluster in this case.
Reference: Hadoop Wiki, What is the purpose of the secondary name-node?
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