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H13-723_V2.0 Exam Dumps - HCIP-Big Data Developer V2.0

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Question # 9

TowardsHBaseincrease in the clusterRegionServerhost, the original cluster must be stopped first, becauseHBase

Dynamic expansion is not supported.

A.

True

B.

False

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Question # 10

aboutHiveandHadoopThe relationship of other components, the following description is wrong?

A.

Hivefinally store the data inHDFSmiddle

B.

HQLable to passMapReduceperform tasks

C.

HiveYesHadoopThe platform's data warehouse tools

D.

HiverightHBasehave strong dependencies

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Question # 11

aboutKafkaThe characteristics of the following description are correct? (multiple choice)

A.

KafkaIt is a high-throughput, distributed, publish-subscribe-based messaging system

B.

KafkaPersistence of messages

C.

KafkaApplicable to offline and online message consumption scenarios

D.

Kafkaguarantee eachPartitionmessages in order

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Question # 12

FusionInsightHD which components are provided externallySQLor classSQLability?

(multiple choice)

A.

HBase

B.

Hive

C.

Spark

D.

Redis

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Question # 13

existMapReduceDuring application development,setMapOutputCompressorClassWhat is the role of classes?

A.

set upmapinput compression method

B.

set upmapHow the output is delivered

C.

set upmapoutput compression method

D.

set upreduceoutput compression method

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Question # 14

Below aboutZooKeeperThe description of the feature is wrong ()?

A.

Updates sent by the client are applied in the order in which they were sent.

B.

A message to be read by more than halfserverreceive, it will be able to successfully write to disk.

C.

Message updates can only succeed or fail, with no intermediate states.

D.

ZooKeeperThe number of nodes must be an odd number.

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Question # 15

due toSparkis a memory-based computing engine, therefore, aSparkThe amount of data the app can handle Can't give more than thisSparkThe total memory of the application.

A.

True

B.

False

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Question # 16

existSparkIn application development, which of the following codes can correctly count words?

A.

val counts=textFile.map(line=>line.split(" ')).map(-rd=>(word,1)).reduceByKey(_+_)

B.

val counts=textFile.flatMap(line=>line.split(" ")).map(word=>(word,1)).reduceByKey(_+_)

C.

val counts=textFile.map(line=>line.split(" ")).map(word=>(word,1)).groupByKey()

D.

val counts=textFile.flatmap(line=>line.split(" ")).map(-rd=>(word,1)).reduceByKey()

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