최신 Apache-Hadoop-Developer 무료덤프 - Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer

A. 6

B. 1

C. 3

D. 0

E. 5

A. The client queries the NameNode for the block location(s). The NameNode returns the block location(s) to the client. The client reads the data directory off the DataNode(s).

B. The client contacts the NameNode for the block location(s). The NameNode then queries the DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects the client to the DataNode that holds the requested data block(s). The client then reads the data directly off the DataNode.

C. The client contacts the NameNode for the block location(s). The NameNode contacts the DataNode that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then from the NameNode to the client.

D. The client queries all DataNodes in parallel. The DataNode that contains the requested data responds directly to the client. The client reads the data directly off the DataNode.

A. Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure method of the mapper.

B. Place the data file in the DataCache and read the data into memory in the configure method of the mapper.

C. Place the data file in the DistributedCache and read the data into memory in the map method of the mapper.

D. Place the data file in the DistributedCache and read the data into memory in the configure method of the mapper.

A. The default partitioner computes the hash of the key and divides that valule modulo the number of reducers. The result determines the reducer assigned to process the key-value pair.

B. The default partitioner computes the hash of the value and takes the mod of that value with the number of reducers. The result determines the reducer assigned to process the key-value pair.

C. The default partitioner implements a round-robin strategy, shuffling the key-value pairs to each reducer in turn. This ensures an event partition of the key space.

D. The default partitioner assigns key-values pairs to reduces based on an internal random number generator.

E. The default partitioner computes the hash of the key. Hash values between specific ranges are associated with different buckets, and each bucket is assigned to a specific reducer.

A. A SequenceFile contains a binary encoding of an arbitrary number of homogeneous writable objects.

B. A SequenceFile contains a binary encoding of an arbitrary number key-value pairs. Each key must be the same type. Each value must be same type.

C. A SequenceFile contains a binary encoding of an arbitrary number of WritableComparable objects, in sorted order.

D. A SequenceFile contains a binary encoding of an arbitrary number of heterogeneous writable objects.

A. Sample the weblogs from the web servers, copying them into Hadoop using curl.

B. Ingest the server web logs into HDFS using Flume.

C. Channel these clickstreams inot Hadoop using Hadoop Streaming.

D. Write a MapReduce job, with the web servers for mappers, and the Hadoop cluster nodes for reduces.

E. Import all users' clicks from your OLTP databases into Hadoop, using Sqoop.

A. hadoop fs -Is x

B. hadoop fs -cat x

C. hdfs fs -get x

D. hadoop fs -cp x

A. Ordered collection of maps, ordered collection of bags, and unordered set of key/value pairs

B. Unordered collection of tuples, ordered set of fields, set of key value pairs

C. Ordered set of fields, ordered collection of tuples, ordered collection of maps

D. Unordered collection of maps, ordered collection of tuples, ordered set of key/value pairs

A. Pig scripts cannot use an HCatalog table

B. org.apache.hcatalog.pig.HCatStorer

C. No special class is needed for a Pig script to store data in an HCatalog table

D. org.apache.hcatalog.pig.HCatOutputFormat

A. Stores HDFS data in a database for performing SQL-like ad-hoc queries

B. Provides a shared schema mechanism

C. Exists as a subproject of Hive

D. Designed to be used by other programs such as Pig, Hive and MapReduce