CCA-505学習指導、CCA-500全真問題集

最近、Clouderaの認定試験はますます人気があるようになっています。それと同時に、Clouderaの認証資格ももっと重要になっています。IT業界では広く認可されている試験として、CCA-505認定試験はClouderaの中の最も重要な試験の一つです。この試験の認証資格を取ったら、あなたは多くの利益を得ることができます。あなたもこの試験を受ける予定があれば、Pass4TestのCCA-505問題集は試験に準備するときに欠くことができないツールです。この問題集はCCA-505認定試験に関連する最も優秀な参考書ですから。

ClouderaのCCA-500の認定試験に合格すれば、就職機会が多くなります。Pass4TestはClouderaのCCA-500の認定試験の受験生にとっても適合するサイトで、受験生に試験に関する情報を提供するだけでなく、試験の問題と解答をはっきり解説いたします。

あなたが悲しいとき、勉強したほうがいいです。勉強があなたに無敵な位置に立たせます。Pass4TestのClouderaのCCA-505試験トレーニング資料は同様にあなたに無敵な位置に立たせることができます。このトレーニング資料を手に入れたら、あなたは国際的に認可されたClouderaのCCA-505認定試験に合格することができるようになります。そうしたら、金銭と地位を含むあなたの生活は向上させることができます。そのとき、あなたはまだ悲しいですか。いいえ、あなたはきっと非常に誇りに思うでしょう。Pass4Testがそんなに良いトレーニング資料を提供してあげることを感謝すべきです。Pass4Testはあなたが方途を失うときにヘルプを提供します。あなたの独自の品質を向上させるだけでなく、完璧な人生価値を実現することも助けます。

試験番号：CCA-505
試験科目：「Cloudera Certified Administrator for Apache Hadoop (CCAH) CDH5 Upgrade Exam」
一年間無料で問題集をアップデートするサービスを提供いたします
最近更新時間：2015-02-06
問題と解答：全45問 CCA-505 トレーニング費用

>>詳しい紹介はこちら

 

試験番号：CCA-500
試験科目：「Cloudera Certified Administrator for Apache Hadoop (CCAH)」
一年間無料で問題集をアップデートするサービスを提供いたします
最近更新時間：2015-02-06
問題と解答：全60問 CCA-500 認定資格

>>詳しい紹介はこちら

 

たくさんの人はCloudera CCA-500「Cloudera Certified Administrator for Apache Hadoop (CCAH)」認証試験を通ることが難しいと思います。もし弊社の問題集を勉強してそれは簡単になります。弊社はオンラインサービスとアフターサービスとオンラインなどの全面方面を含めてます。オンラインサービスは研究資料模擬练習問題などで、アフターサービスはPass4Testが最新の認定問題だけでなく、絶えずに問題集を更新しています。

しかし、CCA-505「Cloudera Certified Administrator for Apache Hadoop (CCAH) CDH5 Upgrade Exam」試験は簡単ではありません。専門的な知識が必要で、もしあなたはまだこの方面の知識を欠かれば、Pass4Testは君に向ける知識を提供いたします。Pass4Testの専門家チームは彼らの知識や経験を利用してあなたの知識を広めることを助けています。そしてあなたにCCA-505試験に関するテスト問題と解答が分析して差し上げるうちにあなたのIT専門知識を固めています。

あなたは弊社の商品を買ったら一年間に無料でアップサービスが提供された認定試験に合格するまで利用しても喜んでいます。もしテストの内容が変われば、すぐにお客様に伝えます。弊社はあなた１００％合格率を保証いたします。

購入前にお試し,私たちの試験の質問と回答のいずれかの無料サンプルをダウンロード：http://www.pass4test.jp/CCA-500.html

NO.1 You decide to create a cluster which runs HDFS in High Availability mode with automatic
failover, using Quorum Storage. What is the purpose of ZooKeeper in such a configuration?
A. It only keeps track of which NameNode is Active at any given time
B. It monitors an NFS mount point and reports if the mount point disappears
C. It both keeps track of which NameNode is Active at any given time, and manages the Edits file.
Which is a log of changes to the HDFS filesystem
D. If only manages the Edits file, which is log of changes to the HDFS filesystem
E. Clients connect to ZooKeeper to determine which NameNode is Active
Answer: A

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Reference: http://www.cloudera.com/content/cloudera-
content/clouderadocs/CDH4/latest/PDF/CDH4-High-Availability-Guide.pdf (page 15)

NO.2 You need to analyze 60,000,000 images stored in JPEG format, each of which is approximately
25 KB. Because you Hadoop cluster isn't optimized for storing and processing many small files, you
decide to do the following actions:
1.Group the individual images into a set of larger files
2.Use the set of larger files as input for a MapReduce job that processes them directly with python
using Hadoop streaming.
Which data serialization system gives the flexibility to do this?
A. CSV
B. XML
C. HTML
D. Avro
E. SequenceFiles
F. JSON
Answer: E

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Explanation:
Sequence files are block-compressed and provide direct serialization and deserialization of several
arbitrary data types (not just text). Sequence files can be generated as the output of other
MapReduce tasks and are an efficient intermediate representation for data that is passing from one
MapReduce job to anther.

NO.3 You are migrating a cluster from MApReduce version 1 (MRv1) to MapReduce version 2 (MRv2)
on YARN. You want to maintain your MRv1 TaskTracker slot capacities when you
migrate. What should you do/
A. Configure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.resource.cpu-
vcores so that ApplicationMaster container allocations match the capacity you require.
B. You don't need to configure or balance these properties in YARN as YARN dynamically balances
resource management capabilities on your cluster
C. Configure mapred.tasktracker.map.tasks.maximum and
mapred.tasktracker.reduce.tasks.maximum ub yarn-site.xml to match your cluster's capacity set by
the yarn-scheduler.minimum-allocation
D. Configure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu-vcores
to match the capacity you require under YARN for each NodeManager
Answer: D

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NO.4 You have a cluster running with the fair Scheduler enabled. There are currently no jobs running
on the cluster, and you submit a job A, so that only job A is running on the cluster. A while later, you
submit Job B. now Job A and Job B are running on the cluster at the same time. How will the Fair
Scheduler handle these two jobs?
A. When Job B gets submitted, it will get assigned tasks, while job A continues to run with fewer
tasks.
B. When Job B gets submitted, Job A has to finish first, before job B can gets scheduled.
C. When Job A gets submitted, it doesn't consumes all the task slots.
D. When Job A gets submitted, it consumes all the task slots.
Answer: B

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NO.5 Identify two features/issues that YARN is designated to address:
A. Standardize on a single MapReduce API
B. Single point of failure in the NameNode
C. Reduce complexity of the MapReduce APIs
D. Resource pressure on the JobTracker
E. Ability to run framework other than MapReduce, such as MPI
F. HDFS latency
Answer: D,E

Clouderaプログラム   CCA-500   CCA-500   CCA-500返済   CCA-500一番
Reference: http://www.revelytix.com/?q=content/hadoop-ecosystem (YARN, first para)

NO.6 A slave node in your cluster has 4 TB hard drives installed (4 x 2TB). The DataNode is configured
to store HDFS blocks on all disks. You set the value of the dfs.datanode.du.reserved parameter to 100
GB. How does this alter HDFS block storage?
A. 25GB on each hard drive may not be used to store HDFS blocks
B. 100GB on each hard drive may not be used to store HDFS blocks
C. All hard drives may be used to store HDFS blocks as long as at least 100 GB in total is available on
the node
D. A maximum if 100 GB on each hard drive may be used to store HDFS blocks
Answer: D

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NO.7 You want to understand more about how users browse your public website. For example, you
want to know which pages they visit prior to placing an order. You have a server farm of 200 web
servers hosting your website. Which is the most efficient process to gather these web server across
logs into your Hadoop cluster analysis?
A. Sample the web server logs web servers and copy them into HDFS using curl
B. Ingest the server web logs into HDFS using Flume
C. Channel these clickstreams into Hadoop using Hadoop Streaming
D. Import all user clicks from your OLTP databases into Hadoop using Sqoop
E. Write a MapReeeduce job with the web servers for mappers and the Hadoop cluster nodes for
reducers
Answer: B

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Explanation:
Apache Flume is a service for streaming logs into Hadoop. Apache Flume is a distributed, reliable, and
available service for efficiently collecting,aggregating, and moving large amounts of streaming data
into the Hadoop Distributed FileSystem (HDFS). It has a simple and flexible architecture based on
streaming data flows;and is robust and fault tolerant with tunable reliability mechanisms for failover
and recovery.

NO.8 Assume you have a file named foo.txt in your local directory. You issue the following three
commands:
Hadoop fs -mkdir input
Hadoop fs -put foo.txt input/foo.txt
Hadoop fs -put foo.txt input
What happens when you issue the third command?
A. The write succeeds, overwriting foo.txt in HDFS with no warning
B. The file is uploaded and stored as a plain file named input
C. You get a warning that foo.txt is being overwritten
D. You get an error message telling you that foo.txt already exists, and asking you if you would like to
overwrite it.
E. You get a error message telling you that foo.txt already exists. The file is not written to HDFS
F. You get an error message telling you that input is not a directory
G. The write silently fails
Answer: C,E

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