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NEW QUESTION: 1
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. 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.
C. 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.
D. Create a Cognitive Search service for each type of document.
Answer: C
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
NEW QUESTION: 2
商用販売スターターキットに含まれている4つのリソースはどれですか？ （4つ選択してください）
A. ポジショニングガイド
B. セールスコネクトサイトツール
C. ファストトラックオファー
D. RFプランナー
E. シスコ構成プロフェッショナル
F. ゲームプラントレーニング
G. ルーター/スイッチセレクターツール
Answer: A,B,C,F
NEW QUESTION: 3
A DevOps Engineer is building a multi-stage pipeline with AWS CodePipeline to build, verify, stage, test, and deploy an application. There is a manual approval stage required between the test and deploy stages. The development team uses a team chat tool with webhook support. How can the Engineer configure status updates for pipeline activity and approval requests to post to the chat tool?
A. Create an AWS Lambda function that is triggered by the updating of AWS CloudTrail events. When a "CodePipeline Pipeline Execution State Change" event is detected in the updated events, send the event details to the chat webhook URL.
B. Create an AWS CloudWatch Logs subscription that filters on "detail-type": "CodePipeline Pipeline Execution State Change." Forward that to an Amazon SNS topic. Add the chat webhook URL to the SNS topic as a subscriber and complete the subscription validation.
C. Modify the pipeline code to send event details to the chat webhook URL at the end of each stage. Parametrize the URL so each pipeline can send to a different URL based on the pipeline environment.
D. Create an AWS CloudWatch Events rule that filters on "CodePipeline Pipeline Execution State Change." Forward that to an Amazon SNS topic. Subscribe an AWS Lambda function to the Amazon SNS topic and have it forward the event to the chat webhook URL.
Answer: B
NEW QUESTION: 4
A. Option B
B. Option D
C. Option C
D. Option A
Answer: B