IT業の多くの人がいくつか認証試験にパスしたくて、それなりの合格証明書が君に最大な上昇空間を与えます。この競争の激しい業界でとんとん拍子に出世させるのはHortonworksのHDPCD関連復習問題集認定試験ですが、簡単にパスではありません。でもたくさんの方法があって、最も少ない時間をエネルギーをかかるのは最高です。 しかし、HDPCD関連復習問題集認定試験を受けて資格を得ることは自分の技能を高めてよりよく自分の価値を証明する良い方法ですから、選択しなければならならないです。ところで、受験生の皆さんを簡単にIT認定試験に合格させられる方法がないですか。 NewValidDumpsのHortonworksのHDPCD関連復習問題集の認証したカバー率は１００パーセントに達したのですから、弊社の問題と解答を利用する限り、あなたがきっと気楽に試験に合格することを保証します。

HDPCD関連復習問題集認定試験に合格することは難しいようですね。

我々社の練習問題は長年でHDPCD - Hortonworks Data Platform Certified Developer関連復習問題集全真模擬試験トレーニング資料に研究している専業化チームによって編集されます。 もし不合格になったら、私たちは全額返金することを保証します。一回だけでHortonworksのHDPCD テスト参考書試験に合格したい？NewValidDumpsは君の欲求を満たすために存在するのです。

Hortonworks　HDPCD関連復習問題集試験参考書に疑問を持たれば、Hortonworks会社のウエブサイトから無料でHDPCD関連復習問題集試験のためのデモをダウンロードできます。HDPCD関連復習問題集試験参考書の高品質でHDPCD関連復習問題集試験の受験者は弊社と長期的な協力関係を築いています。HDPCD関連復習問題集試験参考書はお客様の試験のために最も役に立つ商品だとも言えます。

Hortonworks HDPCD関連復習問題集 - もし弊社の問題集を勉強してそれは簡単になります。

時間とお金の集まりより正しい方法がもっと大切です。HortonworksのHDPCD関連復習問題集試験のために勉強していますなら、NewValidDumpsの提供するHortonworksのHDPCD関連復習問題集試験ソフトはあなたの選びの最高です。我々の目的はあなたにHortonworksのHDPCD関連復習問題集試験に合格することだけです。試験に失敗したら、弊社は全額で返金します。我々の誠意を信じてください。あなたが順調に試験に合格するように。

弊社の資料を使って、１００％に合格を保証いたします。NewValidDumpsはIT試験問題集を提供するウエブダイトで、ここによく分かります。

HDPCD PDF DEMO:

QUESTION NO: 1
Which best describes how TextInputFormat processes input files and line breaks?
A. 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.
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. The input file is split exactly at the line breaks, so each RecordReader will read a series of complete lines.
D. Input file splits may cross line breaks. A line that crosses file splits is ignored.
E. 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.
Answer: A
Reference: How Map and Reduce operations are actually carried out

QUESTION NO: 2
In a MapReduce job with 500 map tasks, how many map task attempts will there be?
A. It depends on the number of reduces in the job.
B. Between 500 and 1000.
C. At most 500.
D. At least 500.
E. Exactly 500.
Answer: D
Explanation:
From Cloudera Training Course:
Task attempt is a particular instance of an attempt to execute a task
- There will be at least as many task attempts as there are tasks
- If a task attempt fails, another will be started by the JobTracker
- Speculative execution can also result in more task attempts than completed tasks

QUESTION NO: 3
You have just executed a MapReduce job.
Where is intermediate data written to after being emitted from the Mapper's map method?
A. Intermediate data in streamed across the network from Mapper to the Reduce and is never written to disk.
B. Into in-memory buffers on the TaskTracker node running the Mapper that spill over and are written into HDFS.
C. Into in-memory buffers that spill over to the local file system of the TaskTracker node running the
Mapper.
D. Into in-memory buffers that spill over to the local file system (outside HDFS) of the TaskTracker node running the Reducer
E. Into in-memory buffers on the TaskTracker node running the Reducer that spill over and are written into HDFS.
Answer: C
Explanation:
The mapper output (intermediate data) is stored on the Local file system (NOT HDFS) of each individual mapper nodes. This is typically a temporary directory location which can be setup in config by the hadoop administrator. The intermediate data is cleaned up after the Hadoop Job completes.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, Where is the
Mapper Output (intermediate kay-value data) stored ?

QUESTION NO: 4
You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
TextInputFormat: the mapper applies a regular expression over input values and emits key-values pairs with the key consisting of the matching text, and the value containing the filename and byte offset. Determine the difference between setting the number of reduces to one and settings the number of reducers to zero.
A. There is no difference in output between the two settings.
B. With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of matching patterns are stored in a single file on HDFS.
C. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS.
With one reducer, instances of matching patterns are stored in multiple files on HDFS.
D. With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one reducer, all instances of matching patterns are gathered together in one file on HDFS.
Answer: D
Explanation:
* It is legal to set the number of reduce-tasks to zero if no reduction is desired.
In this case the outputs of the map-tasks go directly to the FileSystem, into the output path set by setOutputPath(Path). The framework does not sort the map-outputs before writing them out to the
FileSystem.
* Often, you may want to process input data using a map function only. To do this, simply set mapreduce.job.reduces to zero. The MapReduce framework will not create any reducer tasks.
Rather, the outputs of the mapper tasks will be the final output of the job.
Note:
Reduce
In this phase the reduce(WritableComparable, Iterator, OutputCollector, Reporter) method is called for each <key, (list of values)> pair in the grouped inputs.
The output of the reduce task is typically written to the FileSystem via
OutputCollector.collect(WritableComparable, Writable).
Applications can use the Reporter to report progress, set application-level status messages and update Counters, or just indicate that they are alive.
The output of the Reducer is not sorted.

QUESTION NO: 5
Which one of the following classes would a Pig command use to store data in a table defined in
HCatalog?
A. org.apache.hcatalog.pig.HCatOutputFormat
B. org.apache.hcatalog.pig.HCatStorer
C. No special class is needed for a Pig script to store data in an HCatalog table
D. Pig scripts cannot use an HCatalog table
Answer: B

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Updated: May 27, 2022