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NEW QUESTION: 1
For this question, refer to the TerramEarth case study.
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles.
You want to run this job on all the data. What is the most cost-effective way to run this job?
A. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.
B. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job.
C. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the jo
D. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.
Answer: C
Explanation:
Explanation
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios. This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming videos, gaming or mobile applications.
References:
https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best-performance-5c847ac8f9
NEW QUESTION: 2
If the Enter key was pressed to accept the formula in cell B9, which of the following would be the result:
A. 9.3
B. A #VALUE error message
C. A #REF! error message
D. A #NAME? Error message
Answer: D
NEW QUESTION: 3
솔루션 설계자는 50TB의 NFS 데이터를 Amazon S3로 마이그레이션해야 합니다. 파일은 회사 네트워크의 여러 NFS 파일 서버에 있습니다. 이들은 수천만 개의 작은 파일을 포함하는 고밀도 파일 시스템입니다. 시스템 운영자가 AWS Snowball Edge 디바이스에서 파일 인터페이스를 구성했으며 셸 스크립트를 사용하여 데이터를 복사하고 있습니다.
개발자는 Snowball Edge 장치로 데이터를 복사하는 것이 매우 느리다고보고했습니다. 솔루션 아키텍트는 이것이 모든 작은 파일을 암호화하여 네트워크를 통해 전송하는 오버 헤드와 관련이 있을 것으로 의심합니다.
데이터 전송 속도를 높이기 위해 어떤 변경을 할 수 있습니까?
A. Snowball Edge 장치의 USB 인터레이스에 직접 연결하고 파리를 로컬로 복사
B. Snowball Edge 장치의 처리량을 늘리려면 병렬 복사 작업 수를 늘리십시오.
C. Snowball Edge 장치의 파일 인터페이스 대신 S3 어댑터를 사용하도록 솔루션 변경
D. 두 개의 Snowball Edge 장치를 함께 클러스터 하여 장치의 처리량을 증가시킵니다.
Answer: D