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H13-723_V2.0 – HCIP-Big Data Developer V2.0

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Showing 4–6 of 20 questions

Question 4 (Exam Pool D)

existKafkain, aboutConsumerWhich statement is correct? (multiple choice)

Select all that apply, then click Submit answer.

  • ○

    ConsumerMainly for data consumption
  • ○

    ConsumerNeed to specify when consuming dataTopic
  • ○

    multipleConsumerconfigure the samegroup.idwhen theseConsumerConsumed data will not be duplicated
  • ○

    newConsumerAPIConsumption data does not need to be specifiedZooKeeperaddress
Question 5 (Exam Pool A)

An application requires simultaneous and twoFusionInsightsCluster interaction: both need to access the cluster1ofHBaseservice, need to visit

Ask the cluster2ofHiveServe;

So which of the following operations are required? (multiple choice)

Select all that apply, then click Submit answer.

  • ○

    in the cluster1Create the account required for this application on theHBaseServe
  • ○

    in the cluster2created onAThe account with the same name in the options, and set this account to be able to access the cluster'sHiveServe
  • ○

    Aoptions andBThe account created by the option must belong tosupergroupGroup
  • ○

    cluster1and cluster2Complete the mutual trust operation
Question 6 (Exam Pool C)

There are the following business scenarios: User online log files have been stored inHDFSabove, the log file content format the formula is: each online record has three fields, namely name, gender, and online time, and the fields are separated by ",";

It is required to print out all female netizens who spend more than two hours online. Which of the following code snippets can achieve

The above business scenario? (multiple choice)

Select all that apply, then click Submit answer.

  • ○

    sc.textFile("/data/file/path”).map(.split(",")).map(p=>FemaleInfo(p
    (O),p(1),p(2).trim.toInt)).toDF.registerTemp Table("FemaleinfoTable”)sqlContext.sql
    ("select name,sum(stay Time)as stay Time from FemaleInfoTable where gender=
    female'group by name”).filter("stay Time >=120”).collect).foreach(printin)
  • ○

    sc.textFile("/data/file/path").map(.split(",")).map(p=>FemaleInfo
    (p(O),p(1),p(2).trim.toInt)).toDF.registerTemp Table("Female infoTable")
    sqlContext.sq(l "select name, sum(stay Time)as stay Time from FemaleInfoTable where
    gender=female).filter(“stay Time >=120”).collect).foreach(printin)
  • ○

    val text=sc.textFile("/data/fle/path")
    val data=text.filter(_.contains("female"))
    Val fermaleData:RDD(String,Int) =data.map{line=>val t=line.split(',')
    (t(0),t(2).toInt)
    }.reduceByKey(_+_)
    Val result=femaleData.filter(line=>line.2>120)
    Rusult.collect.map(x=>x._1 + ',' + x._2).foreach(println)
  • ○

    val text=sc.textFile("/data/fle/path”)
    val data=text.filter(_.contains("female”))
    Val fermaleData:RDD(String,Int) =data.map(line=>val t=line.split(',')
    (t(0),t(2).toInt)
    }
    Val result=femaleData.filter(line=>line.2>120)
    Rusult.collect.map(x=>x._1 +','+ x._2).foreach(println)