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- Name: Google Cloud Certified - Professional Cloud Database Engineer
- Exam Code: Professional-Cloud-Database-Engineer
- Certification: Professional-Cloud-Database-Engineer
- Vendor: Google
- Total Question: 630
- Price: 49$
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NEW QUESTION: 1
고객은 자주 데이터를 덮어 쓰고 삭제하는 프로덕션 응용 프로그램을 가지고 있으므로 응용 프로그램은 요청할 때마다 항상 최신 버전의 데이터가 필요합니다. 솔루션 설계자는 이 사용 사례를 가장 잘 수용 할 수 있도록 어떤 스토리지 서비스를 권장합니까?
A. AWS Storage Gateway
B. Amazon RDS
C. Amazon S3
D. 아마존 레드 시프트
Answer: C
NEW QUESTION: 2
OceanStor V3 series storage can only support iSCSI or FC host links separately, not both Connect to the network.
A. FALSE
B. TRUE
Answer: A
NEW QUESTION: 3
Your customer collects diagnostic data from its storage systems that are deployed at customer sites. The customer needs to capture and process this data by country in batches.
Why should the customer choose Hadoop to process this data?
A. Hadoop is a batch data processing architecture.
B. Hadoop processes data on large clusters (10-50 max) on commodity hardware.
C. Node failures can be dealt with by configuring failover with clusterware.
D. Hadoop processes data serially.
E. Hadoop supports centralized computing of large data sets on large clusters.
Answer: A
Explanation:
Explanation/Reference:
Hadoop was designed for batch processing. That means, take a large dataset in input all at once, process it, and write a large output. The very concept of MapReduce is geared towards batch and not real-time.
With growing data, Hadoop enables you to horizontally scale your cluster by adding commodity nodes and thus keep up with query. In hadoop Map-reduce does the same job it will take large amount of data and process it in batch. It will not give immediate output. It will take time as per Configuration of system,namenode,task-tracker,job-tracker etc.
Incorrect Answers:
A: Yahoo! has by far the most number of nodes in its massive Hadoop clusters at over 42,000 nodes as of July 2011.
C: Hadoop supports distributed computing of large data sets on large clusters E: Hadoop processes data in parallel.
References: https://www.quora.com/What-is-batch-processing-in-hadoop
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