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NEW QUESTION: 1

必要に応じて、次のログイン資格情報を使用します。
Azureユーザー名：xxxxx
Azureパスワード：xxxxx
次の情報は、テクニカルサポートのみを目的としています。
ラボインスタンス：10277521
Azure Blobストレージにコピーされる大量のリアルタイムデータを生成する予定です。
Azure Cosmos DBデータベースからデータを読み取るレポートを作成する予定です。
storage10277521という名前のblobストレージからCosmos DBデータベースにデータを入力するAzure Stream Analyticsジョブを作成する必要があります。
このタスクを完了するには、Azureポータルにサインインします。
Answer:
Explanation:
See the explanation below.
Explanation
Step 1: Create a Stream Analytics job
1. Sign in to the Azure portal.
2. Select Create a resource in the upper left-hand corner of the Azure portal.
3. Select Analytics > Stream Analytics job from the results list.
4. Fill out the Stream Analytics job page.

5. Check the Pin to dashboard box to place your job on your dashboard and then select Create.
6. You should see a Deployment in progress... notification displayed in the top right of your browser window.
Step 2: Configure job input
1. Navigate to your Stream Analytics job.
2. Select Inputs > Add Stream input > Azure Blob storage

3. In the Azure Blob storage setting choose: storage10277521. Leave other options to default values and select Save to save the settings.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-quick-create-portal

NEW QUESTION: 2
Which descriptions of ClientMatch are accurate? (Choose two.)
A. Sends QRT frames to neighbor APs to read RSSI of APs
B. Performs band-steering for clients across APs
C. Moves higher traffic clients to adjacent APs
D. Performs client load balance across APs
E. Performs spectrum load balancing across APs
Answer: B,D
Explanation:
Explanation/Reference:
Reference: https://www.arubanetworks.com/techdocs/ArubaOS_64_Web_Help/Content/ ArubaFrameStyles/ARM/Client_Match.htm

NEW QUESTION: 3
Refer to the exhibit.

Drag and drop the steps from the left into the correct order of operation on the right for a successful OAuth2 three-legged authorization code grant flow.

Answer:
Explanation:



NEW QUESTION: 4
유틸리티 회사는 사용 시간 계량을 용이하게 하기 위해 스마트 계량기에서 5 분마다 사용량 데이터를 수집하려고 합니다. 계측기가 AWS로 데이터를 보내면 데이터가 Amazon API Gateway로 전송되고 AWS Lambda 함수로 처리되어 Amazon에 저장됩니다. DynamoDB 테이블 파일럿 단계에서 Lambda 기능을 완료하는 데 3 ~ 5 초가 걸렸습니다. 더 많은 스마트 미터가 배포됨에 따라 엔지니어들은 Lambda 기능을 완료하는 데 1 ~ 2 분이 걸린다는 것을 알았습니다. 디바이스에서 수집 된 메트릭 수 DynamoDB에서 PUT 작업을 수행하는 동안 많은 ProvisionedThroughputExceededException 오류가 있으며 Lambda의 TooMany Requests Exception 오류도 많습니다.
이러한 문제를 해결할 수있는 변경 조합은 무엇입니까? (2 개 선택)
A. 더 많은 데이터를 보내려면 스마트 미터에서 페이로드 크기를 늘리십시오.
B. Lambda 함수에 사용 가능한 메모리를 늘리십시오
C. Amazon SQS FIFO 대기열에서 데이터를 수집하여 Lambda 함수를 트리거하여 각 메시지를 처리합니다.
D. API Gateway에서 Amazon Kinesis 데이터 스트림으로 데이터를 스트리밍하고 데이터를 일괄 처리
E. DynamoDB 테이블에 대한 쓰기 용량 단위를 늘립니다.
Answer: B,E