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NEW QUESTION: 1
When a new block is mined:
A. a list of transactions is incorporated in that block. Gas used during the execution is attached to the executing contracts while the block reward is automatically spread across the mining pool to ensure a fair spread. Consensus is reached by a special form of hash code.
B. a list of transactions as well as uncles is incorporated in the block. All gas that is used during those transactions is added to the miners' balance. Also, the block reward is added to the miner. Then the same transactions are run again by every participating node in the network to achieve consensus.
Answer: B
NEW QUESTION: 2
A. Option C
B. Option A
C. Option D
D. Option B
Answer: C
NEW QUESTION: 3
ASP.NET MVCアプリケーションを開発します。 リアルタイムプッシュ通知のためにASP.NET SignalRを実装する予定です。 このアプリケーションには、次のクラスが含まれます。
メッセージを表示する必要があります。
関連するコードセグメントをどのように完成させるべきですか？ 答えを得るには、適切なコードセグメントを正しい場所にドラッグします。 各コードセグメントは、1回、複数回、またはまったく使用されないことがあります。 コンテンツを表示するには、分割バーをペインの間にドラッグするかスクロールする必要があります。
Answer:
Explanation:
Explanation:
Box 1: $.hubconnection();
Create a connection.
Box 2: con.createHubProyxy('MyHub');
Declare a proxy to reference the hub.
Box 3: hub.start()('function', function(hello) {
Start the connection
References: https://www.asp.net/signalr/overview/getting-started/tutorial-getting-started-with-signalr
NEW QUESTION: 4
서버에서 데이터를 일괄 처리하여 처리량을 위해 제출하기 전에 응용 프로그램을 구성했습니다. 프런트 엔드 또는 응용 프로그램 서버에 오류가 발생하여 로그 데이터가 손실되었습니다. 어떻게 이것이 미래에 발생하지 않도록 할 수 있습니까?
정답을 선택하십시오.
A. 시스템 및 응용 프로그램 로그를 Amazon EMR에 제출하고 초 이내에 처리 할 수 있도록 데이터에 액세스하십시오.
B. Amazon Machine Learning을 사용하여 기록 로그 정보를 입력하고 Redshift를 사용하여 로그 분석 및 저장
C. 시스템 및 응용 프로그램 로그를 Amazon Kinesis Stream에 제출하고 초 이내에 처리 할 수 있도록 스트림에 액세스합니다.
D. 람다를 트리거하여 로그 파일이 Amazon S3에 업로드되거나 수정 된 프로세스를 호출합니다.
Answer: C
Explanation:
설명:
Amazon Kinesis Streams를 사용하면 제작자가 데이터를 Amazon Kinesis 스트림에 직접 푸시 할 수 있습니다. 예를 들어 Amazon Kinesis Streams에 시스템 및 응용 프로그램 로그를 제출하고 몇 초 내에 스트림을 처리하여 처리 할 수 있습니다. 이렇게하면 프런트 엔드 또는 응용 프로그램 서버가 실패 할 경우 로그 데이터가 손실되는 것을 방지하고 원본의 로컬 로그 저장소를 줄입니다.
Amazon Kinesis Streams는 서버에 데이터를 입력하기 전에 데이터를 일괄 처리하지 않기 때문에 데이터를 빠르게 받아 들일 수 있습니다.
참고:
https://d0.awsstatic.com/whitepapers/Big_Data_Analytics_Options_on_AWS.pdf