[Jul-2022 Newly Released] H13-723_V2.0 Dumps for Huawei Other Certification Certified [Q126-Q143]

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[Jul-2022 Newly Released] H13-723_V2.0 Dumps for Huawei Other Certification Certified

Updated Verified H13-723_V2.0 dumps Q&As – 100% Pass

NO.126 RedisofLISTData structure (multiple choice) Which scenarios?

Build queuing systems, such as message queues

uniq operations, such as getting the ranking value of all data in a certain period of time

Get the latest N data operations: For example, for a Weibo, get the latest 10 comments,

Simulate stack operations

NO.127 forHiveWhich of the descriptions about normal tables and external tables is incorrect?

Create a normal table by default

The essence of the external table is that it will already existHDFSThe file path above is associated with the table

When deleting a normal table, both metadata and data are deleted at the same time

When deleting an external table, only the external table data is deleted without the metadata

NO.128 existSparkIn application development, which of the following codes can correctly count words?

rval counts = textFile.map(line => line.split(“”)).map(word =>(word,
1)).reduceByKey(+)

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

vrval counts = textFie.map(line => line.split(“)).map(word =>(word,
1)).groupByKey( )

vrval counts = textFile.flatMap(line => line.split(“”)).map(word =>(word,
1)).groupByKey( )

NO.129 When a task is submitted toYARNIn the cluster, which of the following options will generate for this taskTindivual JOPO

ResourceManager

container

AppMaster

NodeManager

NO.130 HDFSThe system time of the node where the client is located is the same as theFusionInsight HDThe system time of the cluster should be maintained Consistent, if there is a time difference, then the time difference should be less than a few minutes?

NO.131 existSpark, assuminglinesIs anDStreamObject, which of the following statements can periodically count the number of words on this stream?

lines.flatMap(_.split??)).map(word=>(word,1)).reduce(_+_).print ( )

lines.flatMap(_.split??)).map(word=>(word,word.length())).reduceByKey(_+_).print ( )

lines.flatMap(_.split??)).map(word=>(word,1)).reduceByKey(_+_).print ( )

lines.flatMap(_.split??)).flatmap(word=>(word,1)).groupByKey(_+_).print ( )

NO.132 FSpark Streamingapplication, in aJVM, there can only be one at a time
StreamingContextin active state

True

False

NO.133 FlumewriteHDFSWhen the file is generated, what are the ways of generating the file? (multiple choice)

Generate files directly according to the source file name

Set the file generation time interval, close the old file when the time interval is reached, and the new data will be written to the new file

Set the size of a single file, when the file size reaches the set value, the old file will be closed, and the new data will be written to the new file

Set up single file storageeventquantity, when the file is storedeventWhen the number reaches the set value, the old file will be closed, and the new data will be is written to a new file

NO.134 A large-scale production enterprise plans to transform its internal logistics data and sales data into big data.
The design department gives
Based on the analysis of the data storage scheme, which of the following statements are correct?
(multiple choice)

HBaseIt can store massive data and support dynamic expansion, which can fulfill the storage requirements of logistics and sales data.

HbaseIt supports efficient random reading, and can complete real-time analysis and command of the logistics situation through reasonable design.

Logistics data is very sparse,HBaseCan handle sparse data efficiently.

HBaseIt can be built on ordinary commercial servers, and the construction cost is relatively low.

NO.135 aboutStreamingdisaster recovery capability, which of the following statements is correct? (multiple choice)

SupervisorAfter the process exits, it can beNimbusAutomatically identify and pull up without affecting running business.

WorkerCan be used after abnormal exitSupervisorPulls up automatically without manual intervention.

When a node fails, the tasks on the node will be reassigned to other normal nodes without manual intervention.

NimbusAfter the failure, the backupNimbusIt will take over automatically without affecting the running business.

NO.136 Which of the following options isYarncore functionality?

storage

Resource management

data transmission

NO.137 Hadoopin the systemYARNassigned toContainerThe memory size, which can be passed through the parameter yarn.app.mapreduce.am.resource.mb(yarn.nodemanager.resource.memory-mb) to set.
( )

True

False

NO.138 Below aboutZKFCThe statement is wrong ().

zKFC(ZKFalovercontroler)as aZoKeeperCluster client for monitoringNameNode status information.

zkFCprocess hopeNameNodenode andZoKeeperofLeaderdeployed in the node.
//(ZKFCProcess is only deployingNameNodeexists in the node)
standbyameodepassZokceperKnow moreAcibe Nameodestate, onceAeametoesmachine,Standby

NameNodeThe primary operation will be performed.

HdFSNameoofCConnected to2Ke4Pf, save the hostname and other information tozoKe-p%rmiddle

NO.139 FusionInsightHDin the system,HiveWhat are the supported interface types? (multiple choice)

mouthJDB, Cinterface

mouthODB, Cinterface

mouthPythoninterface

mouthRubyinterface

NO.140 aboutFusionInsight HDplatformHiveservice, itsWebHCatDevelopment interface, which of the following descriptions is incorrect?

Support based onRESTquery request

WebHCatThe return data format isSML

WebHCatbased onHTTPandHTTPSAgreement to provide services to the outside world

able to passWebHCatCreate tables, query, etc.

NO.141 FusionInsight HDmiddle,HiveWhich of the following parameters of the client is used to controlreduceConcurrency? (multiple choice)

hive.exec.reducers.bytes.per.reducer

hive.exec-ducers.max

hive.exec.max.dynamic.partitions

hive.exec.max.dynamic.partitions.pernode

NO.142 FusionInsight HDsystematicV100R002C60version,HiveOnly supports based onMapReduceEngine query service, not supported based onSparkEngine query service.

True

False

NO.143 there are the following scenarios: new data is generated by the online system every day500G, it is necessary to analyze these data by day, week, Monthly and other dimensions for statistical summary. ask if it is suitable for useHiveWhat kind of table to handle?

Bucket table, bucket according to day

Partition table, partitioned by day

skew table, skew field select date, skew value random

partition+Bucket table, partitioned by time, each partition2560buckets

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