A.  

Configuration of rack awareness is accomplished using a configuration file. You cannot use a rack topology script.

B.  

Hadoop gives preference to intra-rack data transfer in order to conserve bandwidth

C.  

Rack location is considered in the HDFS block placement policy

D.  

HDFS is rack aware but MapReduce daemon are not

E.  

Even for small clusters on a single rack, configuring rack awareness will improve performance

A.  

The file will remain under-replicated until the administrator brings that node back online

B.  

The cluster will re-replicate the file the next time the system administrator reboots the NameNode daemon (as long as the file’s replication factor doesn’t fall below)

C.  

This will be immediately re-replicated and all other HDFS operations on the cluster will halt until the cluster’s replication values are resorted

D.  

The file will be re-replicated automatically after the NameNode determines it is under-replicated based on the block reports it receives from the NameNodes

A.  

Oozie

B.  

ZooKeeper

C.  

HBase

D.  

Sqoop

E.  

HUE

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

A.  

Hdfs fs –du

B.  

Hdfs fsck

C.  

Dskchk

D.  

The map-only checksum

E.  

Hadoop does not provide any tools to discover missing or corrupt data; there is not need because three replicas are kept for each data block

A.  

To ensure that there is capacity in HDFS for additional data

B.  

To ensure that all blocks in the cluster are 128MB in size

C.  

To help HDFS deliver consistent performance under heavy loads

D.  

To ensure that there is consistent disk utilization across the DataNodes

E.  

To improve data locality MapReduce

A.  

You cannot enforce this, since client code can always override this value

B.  

Set dfs.block.size to 128M on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to final

C.  

Set dfs.block.size to 128 M on all the worker nodes and client machines, and set the parameter to final. You do not need to set this value on the NameNode

D.  

Set dfs.block.size to 134217728 on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to final

E.  

Set dfs.block.size to 134217728 on all the worker nodes and client machines, and set the parameter to final. You do not need to set this value on the NameNode

A.  

The directory will appear to be empty until the entire file write is completed on the cluster

B.  

They will see the file with a ._COPYING_ extension on its name. If they view the file, they will see contents of the file up to the last completed block (as each 64MB block is written, that block becomes available)

C.  

They will see the file with a ._COPYING_ extension on its name. If they attempt to view the file, they will get a ConcurrentFileAccessException until the entire file write is completed on the cluster

D.  

They will see the file with its original name. If they attempt to view the file, they will get a ConcurrentFileAccessException until the entire file write is completed on the cluster

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.