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NEW QUESTION: 1
A router is configured with the command "configure router ecmp 4". There are two best paths to a given destination with an equal cost in the IGP. Which of the following best describes the handling of traffic to this destination?
A. The router installs four routes for the destination with four different next hops. A hashing algorithm is used to distribute traffic over the four paths.
B. The router installs two routes for the destination with two different next hops. A hashing algorithm is used to distribute traffic over the two paths.
C. The router installs four routes for the destination with four different next hops. Traffic is evenly distributed over the four paths.
D. The router installs two routes for the destination with two different next hops. Traffic is evenly distributed over the two paths.
E. The router installs one route for the destination. Traffic is evenly distributed over the two paths.
Answer: B
NEW QUESTION: 2
Throughout IBM Marketing Operations, there are standard and custom tabs, and each of these contain fields. Any fields that are required have a red, double asterisk (**) next to them. What happens if you do not complete these fields?
A. Error Message displays
B. Default is used
C. It is left blank with no error message.
D. Alert appears
Answer: A
NEW QUESTION: 3
한 회사가 AWS에서 호스팅되는 비디오 변환 애플리케이션을 개발하고 있습니다. 이 애플리케이션은 프리 티어와 유료 티어의 두 가지 계층으로 제공됩니다. 유료 계층의 사용자는 먼저 비디오를 변환 한 다음 트리 계층 사용자는 비디오를 변환합니다.
이러한 요구 사항을 충족하고 가장 비용 효율적인 솔루션은 무엇입니까?
A. 유료 티어 용 FIFO 대기열 1 개와 프리 티어 용 표준 대기열 1 개
B. 모든 파일 유형에 대한 단일 표준 Amazon Simple Queue Service (Amazon SQS) 대기열
C. 두 개의 표준 Amazon Simple Queue Service (Amazon SQS) 대기열, 하나는 유료 티어 용이고 다른 하나는 프리 티어 용
D. 모든 파일 유형에 대한 단일 FIFO Amazon Simple Queue Service (Amazon SQS) 대기열
Answer: A
NEW QUESTION: 4
Azure loT Edgeデバイスからデータを取り込み、Azure Machine Learningでデータを前処理し、その後の処理のためにデータをAzure HDInsightに移動するソリューションを設計しています。
ソリューションに何を含めるべきですか？回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: Export Data
The Export data to Hive option in the Export Data module in Azure Machine Learning Studio. This option is useful when you are working with very large datasets, and want to save your machine learning experiment data to a Hadoop cluster or HDInsight distributed storage.
Box 2: Apache Hive
Apache Hive is a data warehouse system for Apache Hadoop. Hive enables data summarization, querying, and analysis of data. Hive queries are written in HiveQL, which is a query language similar to SQL.
Box 3: Azure Data Lake
Default storage for the HDFS file system of HDInsight clusters can be associated with either an Azure Storage account or an Azure Data Lake Storage.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/export-to-hive-query
https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/hdinsight-use-hive