Free Download Latest 2014 Pass4sure&Lead2pass Cloudera CCD-333 Dumps

23 Jul

Vendor: Cloudera
Exam Code: CCD-333
Exam Name: Cloudera Certified Developer for Apache Hadoop

Custom programmer-defined counters in MapReduce are:

A.    Lightweight devices forbookkeeping within MapReduce programs.
B.    Lightweight devices for ensuring the correctness ofa MapReduce program. Mappers Increment counters, and reducers decrement counters. If at the end of the program the counters read zero, then you are sure that the job completed correctly.
C.    Lightweight devices for synchronization within MapReduce programs. You can usecounters to coordinate executionbetween a mapper and a reducer.

Answer: B

Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the two tables are formatted as comma-separated file in HDFS.

A.    Yes.
B.    Yes, but only if one of the tables fits into memory.
C.    Yes, so long as both tables fit into memory.
D.    No, MapReduce cannot perform relational operations.
E.    No, but it can be done with either Pig or Hive.

Answer: C

To process input key-value pairs, your mapper needs to load a 512 MB data file in memory. What is the best way to accomplish this?

A.    Place the data tile in theDataCache and read the data into memory in the configure method of the mapper.
B.    Place the data file in the DtStribub&dCache and read the data into memory in the map method of the mapper.
C.    Place the data file in the DistribulodCache and read the data into memory in the configure method of the mapper.
D.    Serialize the data file, insert it in the Jobconfobject, and read the data into memory in the configure method of the mapper.

Answer: D

What types of algorithms are difficult to express MapReduce?

A.    Algorithms that requite global, shared state.
B.    Large-scale graph algorithms that require one-step link traversal.
C.    Relational operations on large amounts of structured and semi structured data.
D.    Text analysis algorithms on large collections of unstructured text (e.g., Web crawls).
E.    Algorithms that require applying the same mathematical function to large numbers of individual binary records.

Answer: C

MapReduce is well-suited for all of the following applications EXCEPT? (Choose one):

A.    Text mining on a large collections of unstructured documents.
B.    Analysis of large amounts of Web logs (queries, clicks, etc.).
C.    Online transaction processing (OLTP) for an e-commerce Website.
D.    Graph mining on a large social network (e.g., Facebook friends network).

Answer: C

Your Custer’s HOFS block size is 64MB. You have a directory containing 100 plain text files, each of which Is 100MB in size. The InputFormat for your job is TextInputFormat. How many Mappers will run?

A.    64
B.    100
C.    200
D.    640

Answer: B

Does the MapReduce programming model provide a way for reducers to communicate with each other?

A.    Yes,all reducers can communicate with each other by passinginformation through the jobconf object.
B.    Yes,reducers can communicate with each other by dispatchingintermediate key value pairs that get shuffled to another reduce
C.    Yes,reducers running on the same machine can communicatewith each other through shared memory, but not reducers on different machines.
D.    No, each reducer runs independently and in isolation.

Answer: D

Which of the following best describes the map method input and output?

A.    It accepts a single key-value pair as input and can emit only one key-value pair as output.
B.    It acceptsa list ofkey-valuepairsasinput hut run emitonly one key value pair as output.
C.    It acceptsasinglekey-valuepairasinputand emits a single key and list of corresponding values as output
D.    It accepts a singlekey-valuepairas inputandcan emitany number ofkey-valuepairs as output, includingzero.

Answer: C

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