CCD-410の無料問題集（60題）、CCD-410認定試験参考書

Cloudera CCD-410 問題集

試験コード：CCD-410

試験名称：Cloudera Certified Developer for Apache Hadoop (CCDH)

最近更新時間：2024-04-17

問題と解答：全60問

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無料問題集CCD-410 資格取得

質問 1：
Which best describes how TextInputFormat processes input files and line breaks?
A. The input file is split exactly at the line breaks, so each RecordReader will read a series of complete lines.
B. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReaders of both splits containing the broken line.
C. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the split that contains the end of the broken line.
D. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the split that contains the beginning of the broken line.
E. Input file splits may cross line breaks. A line that crosses file splits is ignored.
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 2：
Your client application submits a MapReduce job to your Hadoop cluster. Identify the Hadoop daemon on which the Hadoop framework will look for an available slot schedule a MapReduce operation.
A. TaskTracker
B. NameNode
C. Secondary NameNode
D. DataNode
E. JobTracker
正解：E
解説: (Topexam メンバーにのみ表示されます)

質問 3：
In the reducer, the MapReduce API provides you with an iterator over Writable values. What does calling the next () method return?
A. It returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.
B. It returns a reference to a different Writable object time.
C. It returns a reference to the same Writable object each time, but populated with different data.
D. It returns a reference to a Writable object from an object pool.
E. It returns a reference to the same Writable object if the next value is the same as the previous value, or a new Writable object otherwise.
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 4：
You've written a MapReduce job that will process 500 million input records and generated 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that it needs to transfer between mappers and reduces which is a potential bottleneck. A custom implementation of which interface is most likely to reduce the amount of intermediate data transferred across the network?
A. Partitioner
B. Combiner
C. WritableComparable
D. Writable
E. InputFormat
F. OutputFormat
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 5：
On a cluster running MapReduce v1 (MRv1), a TaskTracker heartbeats into the JobTracker on your cluster, and alerts the JobTracker it has an open map task slot.
What determines how the JobTracker assigns each map task to a TaskTracker?
A. The number and speed of CPU cores on the TaskTracker node.
B. The average system load on the TaskTracker node over the past fifteen (15) minutes.
C. The amount of RAM installed on the TaskTracker node.
D. The location of the InsputSplit to be processed in relation to the location of the node.
E. The amount of free disk space on the TaskTracker node.
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 6：
You want to run Hadoop jobs on your development workstation for testing before you submit them to your production cluster. Which mode of operation in Hadoop allows you to most closely simulate a production cluster while using a single machine?
A. Run simldooop, the Apache open-source software for simulating Hadoop clusters.
B. Run all the nodes in your production cluster as virtual machines on your development workstation.
C. Run the hadoop command with the -jt local and the -fs file:///options.
D. Run the DataNode, TaskTracker, NameNode and JobTracker daemons on a single machine.
正解：D

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Cloudera Certified Developer for Apache Hadoop (CCDH) 認定 CCD-410 試験問題:

1. What data does a Reducer reduce method process?

A) All data produced by a single mapper.
B) All the data in a single input file.
C) All data for a given key, regardless of which mapper(s) produced it.
D) All data for a given value, regardless of which mapper(s) produced it.

2. When is the earliest point at which the reduce method of a given Reducer can be called?

A) As soon as at least one mapper has finished processing its input split.
B) It depends on the InputFormat used for the job.
C) As soon as a mapper has emitted at least one record.
D) Not until all mappers have finished processing all records.

3. All keys used for intermediate output from mappers must:

A) Override isSplitable.
B) Be a subclass of FileInputFormat.
C) Implement a comparator for speedy sorting.
D) Implement a splittable compression algorithm.
E) Implement WritableComparable.

4. You want to count the number of occurrences for each unique word in the supplied input data. You've decided to implement this by having your mapper tokenize each word and emit a literal value 1, and then have your reducer increment a counter for each literal 1 it receives. After successful implementing this, it occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your existing Reduces as your combiner in this case and why or why not?

A) Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as a combiner.
B) No, because the Combiner is incompatible with a mapper which doesn't use the same data type for both the key and value.
C) No, because the Reducer and Combiner are separate interfaces.
D) Yes, because the sum operation is both associative and commutative and the input and output types to the reduce method match.
E) No, because the sum operation in the reducer is incompatible with the operation of a Combiner.

5. You use the hadoop fs -put command to write a 300 MB file using and HDFS block size of 64 MB. Just after this command has finished writing 200 MB of this file, what would another user see when trying to access this life?

A) They would see the current state of the file, up to the last bit written by the command.
B) They would see the current of the file through the last completed block.
C) They would see no content until the whole file written and closed.
D) They would see Hadoop throw an ConcurrentFileAccessException when they try to access this file.

質問と回答：

質問 # 1
正解： C

質問 # 2
正解： D

質問 # 3
正解： E

質問 # 4
正解： D

質問 # 5
正解： B