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

True

False

Attribute values with high port access weights are placed inRowKeyFront

Attribute values with high port access weights are placed inRowkeysecond half

The attribute value with good dispersion is placed inRowkeyfirst half

The attribute value with good dispersion is placed inRowkeysecond half

True

False

Partition fields are defined when the table is created

There can only be one partition field, and multi-level partitions cannot be created

Using partitions can reduce the data scan range of some queries, thereby improving query efficiency

Partition fields can be used aswherecondition of the sentence

OneTopologyis made up of a group ofSpoutcomponents andBotcomponents passStream GroupingsA connected directed acyclic graph (DAG)

Topologywill run until it is explicitlykill

Business logic is encapsulated inTopologymiddle

OneTopologyOnly one can be specified to startWorkerprocess

True

False

Hivefinally store the data inHDFSmiddle

HQLable to passMapReduceperform tasks

HiveYesHadoopThe platform's data warehouse tools

HiverightHBasehave strong dependencies

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

KafkaPersistence of messages

KafkaApplicable to offline and online message consumption scenarios

Kafkaguarantee eachPartitionmessages in order

HBase

Hive

Spark

Redis

set upmapinput compression method

set upmapHow the output is delivered

set upmapoutput compression method

set upreduceoutput compression method

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

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

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

ZooKeeperThe number of nodes must be an odd number.

True

False

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

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

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

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

JDB, Cinterface

ODB, Cinterface

Pythoninterface

Rubyinterface

Nimbus

Supervisor

Broker

quorumpeer

ResourceManager

container

AppMaster

NodeManager

list

set

hash

sorted set

True

False

ShellOrder

Java API

Hue UI

Rest API

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)

mouthJDB, Cinterface

mouthODB, Cinterface

mouthPythoninterface

mouthRubyinterface

useJedisobject connectionRedis Server,transferJedisofset.qetWaiting for business operation interface to process data operate.

useJedisPoolobject createdJedisObject pool, each business operation starts fromJedisPoolget one Jedisobject, then call,Jedisofset.getWait for the business operation interface to perform data operations.

useredisClusterobject connectionRedis Server,transferJedisClusterofset.getother business operations interface for data manipulation; in multithreaded applications, multiple threads share oneJedisClusterobject.

useJedisClusterobject connectionRedis Server,transferJedisClusterofset,getother business operations interfacet.

In multithreaded applications, each thread creates aJedisClusterobject.

True

False

Click Tree under Cloud to view metadata such as Collections, configuration sets, and ive nodes in Solr loud information

Click Cloud to view the Replica distribution and status of each Shard under each Collection

Enter the Core Oveview interface where Calectiopeyshard Replicaf is installed, and you can view the Replca index Real Qunwen You Department relies on storing size and location information

Users of the Sor user group, Solr admin role, and Super group can access the Solr Admin UI

HDFS

HBase

Spark

YARN(streaming)

Support based onRESTquery request

WebHCatThe return data format isXML (Json)

WebHCatbased onHTTPandHTTPS

Agreement to provide services to the outside world able to passWebHCatCreate tables, query, etc.

LoaderSubmit the job toARNAfter execution, if at this timeLoaderIf the service is abnormal, this job executes line failed.

LoaderSubmit the job toYARAfter a small execution, if a certainMapperTask execution fails, can be automatically Try again.

LoaderIf the job fails to execute, garbage data will be generated, which needs to be cleared manually by the user.

LoderSubmit an assignment toYARAfter the job is executed, no other jobs can be submitted until the job is executed Industry.

True

False

True

False

True

False

True

False

Create an input stream

Create output stream

Business action statements (such asSELECT,INSERT,JIONWait)

Apply commit statement

True

False

twoworkerone of theworkerdistribute two

twoworkerone for each

no fixed rules

twoworkerBoth are distributed

True

False

Click Tree under Cloud to view cafrCollections, configuration sets and ive nodes in Solr Cloud and other metadata information

Click cloud to view the distribution and status of the replicas of each shard under the backup callion

Enter the Collectionyshard Replicats that you and Confidence Check 1dKepca's (ore-Oevew Open, you can view the actual number of documents submitted for the Relica index

The solr user group, solr, admin, and .Rrg can be used by the sr public and the .Rrg

True

False

True

False

mouthFlume

mouthLoader

mouthHBase

mouthMapReduce

In a network isolation environment,ZooKeeperofIPCan be configured as a businessIP, can also be configured to manageIP.

HiveUnlike traditional databases, soJDB, CThe established connection does not need to be closed.

In a secure cluster environment, establish andHiveBefore connecting, you need to use unified authentication to log in.

useJDB, CsubmitSQL, you canSQLA semicolon ";" is added after the statement.

Get data and convert raw data into data objects that you process yourself

Cache data and save data in memory or files according to different reliability policies

Output data to the destination, support multiple output protocols

Split the data and send the data to different destinations according to the characteristics of the data

True

False

compromise method (rowkeyDesign takes into accountAandBbusiness needs)

Redundancy method (use space for time factory efficiency)

Create secondary index

pre-scoreregion

easy to program

good scalability

real-time computing

High fault tolerance

split

combine

partition

sort

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

KafkaPersistence of messages

KafkaApplicable to offline and online message consumption scenarios

Kafkaguarantee eachPartitionmessages in order

If ZooKeeperIf there is an interruption in the process of synchronizing the message, after the failure is recovered, the transmission status before the failure can be adjusted according to the the state continues to synchronize, that is, support for resuming transmission from a breakpoint.

ZooKeeperUse a custom atomic message protocol to ensure the consistency of node data in the entire system.

ZooKeeperThe cluster is elected at startupLeaderRole.

LeaderAfter a node receives a data change request, it first writes to disk and then writes to memory.

True

False

Mouth compromise (rowkeyDesign takes into accountAandBbusiness needs)

Port redundancy method (exchange space for time/effectiveness)

Create a secondary index

mouth pre-scoreregion

existSolrCreate an index and save the data, and return all the data during full-text search.

existHBasestore data on theHBaseThe filtering characteristics of , satisfy fuzzy matching query.

When storing data, inSolrindex on theHBaseStore complete data? ? when, throughSolrFull-text search to obtain and record

record key information, through the key information inHBasefor the full record.

JDB, C

spark-beeline

spark-sql

True

False

broadcast variable in everyTasksave a copy

broadcast variable in eachExecutorsave a copy

Broadcast variables are read-only

broadcast variable viaSparkContext.broadcast() method to generate

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

OneTopologyis made up of a group ofSpoutcomponents andBoltcomponents passStream GroupingsA connected directed acyclic graph

(DAG)

Topologywill run until it is explicitlykill

Business logic is encapsulatedTopologymiddle

OneTopologyOnly one can be specified to startWorkerprocess

Only the HMI account can be used.

Only the machine account can be used.

A client does not support the simultaneous use of multiple accounts.

The ticket obtained by executing this command is intwenty fourIt will time out when it is small and needs to be executed againkinitcommand to log in again.

True

False

XCompareYhigher performance

XCompareYlower performance

XandYsame as performance

UncertaintyXandYdifference in performance

True

False

Create an input stream

Create output stream

Business action statements (such asSELECT,INSERT,JIONWait)

Apply commit statement

HDFS

HBase

Kafka

Redis

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.

supportCSVandJSON

supportCSV,JSONandHTML

supportCSV,JSONandXML

BufferedOutputStream.write

BufferedOutputStream.flush

FileSystem.create

FileSystem.append

pre-scoreregion,MakeregionEvenly distributed, improve concurrency

Query frequent attributes are placed inrowkeyThe front part

Use secondary indexes to adapt to more query scenarios

Data read at the same time are stored in the samecellmiddle

Spark Streaming

Streaming

MapReduce

HDFS

split

combine

partition

sort

NodeManager

Resource Manager

Data Node

NameNode

True

False

Build queuing systems, such as message queues

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

get latestNdata operations: for example, for a certain microblog, get the latest10comments

Simulate stack operations

True

False

True

False

Streaming data monitoring

Real-time visit statistics of the website

Offline log analysis

Traffic flow analysis

Partition fields are defined when the table is created

There can only be one partition field, and multi-level partitions cannot be created

Using partitions can reduce the data scan range of some queries, thereby improving query efficiency

Partition fields can be used aswherecondition of the sentence

FusionInsight Managerofwebinterface

Loader Webinterface

Solr webinterface

Yarn Webinterface