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NEW QUESTION: 1
与えられた：

コマンドを使用して実行：
java Hello "Hello World" Hello World
出力は何ですか？
A. Hello WorldHelloWorld
B. 実行時に例外がスローされます。
C. Hello World Hello World
D. Hello WorldHello World
E. HelloHello WorldHelloWorld
Answer: C

NEW QUESTION: 2
Modular Data Center is on-demand deployment, which avoids over-investment.
A. FALSE
B. TRUE
Answer: B

NEW QUESTION: 3
You need to configure the UserRegions role.
Which Multidimensional Expressions (MDX) function should you use?
A. LOOKUPVALUE ( )
B. USERID ( )
C. CUSTOMDATA ( )
D. USERNAME ( )
E. UNIQUENAME ( )
Answer: D
Explanation:
Explanation/Reference:
Explanation:
From Scenario: A role named UserRegions has been created in the SSAS database that will be used to filter members in the Regions dimension based on the authenticated user.
The MDX function UserName feturns the domain name and user name of the current connection.
References: https://download.microsoft.com/download/0/F/B/0FBFAA46-2BFD-478F-8E56-
7BF3C672DF9D/Multidimensional%20Expressions%20-%20MDX%20-%20Reference.pdf, page 350

NEW QUESTION: 4
A Data Scientist needs to create a serverless ingestion and analytics solution for high-velocity, real-time streaming data.
The ingestion process must buffer and convert incoming records from JSON to a query-optimized, columnar format without data loss. The output datastore must be highly available, and Analysts must be able to run SQL queries against the data and connect to existing business intelligence dashboards.
Which solution should the Data Scientist build to satisfy the requirements?
A. Create a schema in the AWS Glue Data Catalog of the incoming data format. Use an Amazon Kinesis Data Firehose delivery stream to stream the data and transform the data to Apache Parquet or ORC format using the AWS Glue Data Catalog before delivering to Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena, and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.
B. Use Amazon Kinesis Data Analytics to ingest the streaming data and perform real-time SQL queries to convert the records to Apache Parquet before delivering to Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.
C. Write each JSON record to a staging location in Amazon S3. Use the S3 Put event to trigger an AWS Lambda function that transforms the data into Apache Parquet or ORC format and inserts it into an Amazon RDS PostgreSQL database. Have the Analysts query and run dashboards from the RDS database.
D. Write each JSON record to a staging location in Amazon S3. Use the S3 Put event to trigger an AWS Lambda function that transforms the data into Apache Parquet or ORC format and writes the data to a processed data location in Amazon S3. Have the Analysts query the data directly from Amazon S3 using Amazon Athena, and connect to Bl tools using the Athena Java Database Connectivity (JDBC) connector.
Answer: A