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NEW QUESTION: 1
한 지역에서 AWS의 한도 증액 승인없이 g2.2xlarge 주문형 인스턴스를 얼마나 많이 실행할 수 있습니까?
A. 0
B. 1
C. 2
D. 3
Answer: C
Explanation:
설명:
일반적으로 AWS EC2를 사용하면 한 번에 20 개의 주문형 인스턴스와 100 개의 현장 인스턴스를 실행할 수 있습니다.
이 한도는 https://aws.amazon.com/contact-us/ec2-request에서 요청하여 늘릴 수 있습니다.
특정 유형의 인스턴스를 제외하면 위에서 설명한 것보다 한도가 낮습니다. g2.2xlarge의 경우 사용자는 한 번에 5 개의 주문형 인스턴스 만 실행할 수 있습니다.
http://docs.aws.amazon.com/general/latest/gr/aws_service_limits.html#limits_ec2

NEW QUESTION: 2
DRAG DROP
Click the Task button. Match the Event Source with the mechanism providing the event integration to OMi.

Answer:
Explanation:

Explanation:

NEW QUESTION: 3
An organization uses Amazon Elastic MapReduce(EMR) to process a series of extract-transform-load (ETL) steps that run in sequence. The output of each step must be fully processed in subsequent steps but will not be retained.
Which of the following techniques will meet this requirement most efficiently?
A. Load the data to be processed into HDFS, and then write the final output to Amazon S3.
B. Use the s3n URI to store the data to be processed as objects in Amazon S3.
C. Define the ETL steps as separate AWS Data Pipeline activities.
D. Use the EMR File System (EMRFS) to store the outputs from each step as objects in Amazon Simple Storage Service (S3).
Answer: B

NEW QUESTION: 4
You have an existing Azure Cognitive Search service.
You have an Azure Blob storage account that contains millions of scanned documents stored as images and PDFs.
You need to make the scanned documents available to search as quickly as possible. What should you do?
A. Split the data into multiple blob containers. Create an indexer for each container. Increase the search units. Within each indexer definition, schedule a sequential execution pattern.
B. Create a Cognitive Search service for each type of document.
C. Split the data into multiple blob containers. Create a Cognitive Search service for each container. Within each indexer definition, schedule the same runtime execution pattern.
D. Split the data into multiple virtual folders. Create an indexer for each folder. Increase the search units. Within each indexer definition, schedule the same runtime execution pattern.
Answer: D
Explanation:
Incorrect Answers:
A: Need more search units to process the data in parallel. B: Run them in parallel, not sequentially.
C: Need a blob indexer.
Note: A blob indexer is used for ingesting content from Azure Blob storage into a Cognitive Search index. Index large datasets Indexing blobs can be a time-consuming process. In cases where you have millions of blobs to index, you can speed up indexing by partitioning your data and using multiple indexers to process the data in parallel. Here's how you can set this up:
Partition your data into multiple blob containers or virtual folders Set up several data sources, one per container or folder.
Create a corresponding indexer for each data source. All of the indexers should point to the same target search index.
One search unit in your service can run one indexer at any given time. Creating multiple indexers as described above is only useful if they actually run in parallel.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-howto-indexing-azure-blob-storage

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