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HDP Certified Developer HDPCD そうだったら、下記のものを読んでください。

あなたの希望はNewValidDumpsのHortonworksのHDPCD - Hortonworks Data Platform Certified Developer復習解答例試験トレーニング資料にありますから、速く掴みましょう。 一回だけでHortonworksのHDPCD 復習時間試験に合格したい？NewValidDumpsは君の欲求を満たすために存在するのです。NewValidDumpsは君にとってベストな選択になります。

ですから、ぜひNewValidDumpsというチャンスを掴んでください。NewValidDumpsのHortonworksのHDPCD復習解答例試験トレーニング資料はあなたがHortonworksのHDPCD復習解答例認定試験に合格することを助けます。この認証を持っていたら、あなたは自分の夢を実現できます。

Hortonworks HDPCD復習解答例 - 信じないでしょうか。

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復習解答例試験のために勉強していますなら、NewValidDumpsの提供するHortonworksのHDPCD復習解答例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復習解答例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。

しかし、これは本当のことですよ。HDPCD復習解答例認定試験の準備を効率的にするために、どんなツールが利用に値するものかわかっていますか。

HDPCD PDF DEMO:

QUESTION NO: 1
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: 2
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

QUESTION NO: 3
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: 4
For each input key-value pair, mappers can emit:
A. As many intermediate key-value pairs as designed. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
B. As many intermediate key-value pairs as designed, but they cannot be of the same type as the input key-value pair.
C. One intermediate key-value pair, of a different type.
D. One intermediate key-value pair, but of the same type.
E. As many intermediate key-value pairs as designed, as long as all the keys have the same types and all the values have the same type.
Answer: E
Explanation:
Mapper maps input key/value pairs to a set of intermediate key/value pairs.
Maps are the individual tasks that transform input records into intermediate records. The transformed intermediate records do not need to be of the same type as the input records. A given input pair may map to zero or many output pairs.
Reference: Hadoop Map-Reduce Tutorial

QUESTION NO: 5
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

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Updated: May 27, 2022