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NEW QUESTION: 1
A company is planning to do a proof of concept for a machine earning (ML) project using Amazon SageMaker with a subset of existing on-premises data hosted in the company's 3 TB data warehouse. For part of the project, AWS Direct Connect is established and tested. To prepare the data for ML, data analysts are performing data curation. The data analysts want to perform multiple step, including mapping, dropping null fields, resolving choice, and splitting fields. The company needs the fastest solution to curate the data for this project.
Which solution meets these requirements?
A. Take a full backup of the data store and ship the backup files using AWS Snowball. Upload Snowball data into Amazon S3 and schedule data curation jobs using AWS Batch to prepare the data for ML.
B. Create custom ETL jobs on-premises to curate the data. Use AWS DMS to ingest data into Amazon S3 for ML processing.
C. Ingest data into Amazon S3 using AWS DataSync and use Apache Spark scrips to curate the data in an Amazon EMR cluster. Store the curated data in Amazon S3 for ML processing.
D. Ingest data into Amazon S3 using AWS DMS. Use AWS Glue to perform data curation and store the data in Amazon 3 for ML processing.
Answer: D
NEW QUESTION: 2
アナリストは、時間とともに変化する可能性のある特定の個人グループとワークスペースを共有する必要があります。アナリストはどのプロセスに従うべきですか？
A. 管理コンソールからワークスペースをユーザーグループに追加します
B. [共有]オプションを選択し、一連のユーザー用に新しいカスタムグループを作成して、ワークスペースからそのグループとプロジェクトを共有します
C. [共有]オプションを選択し、ワークスペースからプロジェクトにアクセスする必要がある各個人を追加します
D. ワークスペース内からユーザーグループとワークスペースを共有する
Answer: A
NEW QUESTION: 3
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question os independent of the other questions in this series. Information and details provided in a question apply only to that question.
You have a database named DB1. There is no memory-optimized filegroup in the database.
You run the following query:
The following image displays the execution plan the query optimizer generates for this query:
Users frequently run the same query with different values for the local variable @lastName. The table named Person is persisted on disk.
You need to create an index on the Person.Person table that meets the following requirements:
- All users must be able to benefit from the index.
- FirstName must be added to the index as an included column.
What should you do?
A. Create a clustered index on the table.
B. Create a nonclustered columnstoreindex on the table.
C. Create a hash index on the table.
D. Create a clustered columnstore index on the table.
E. Create a nonclustered filtered index on the table.
F. Create a nonclustered index on the table.
Answer: F
Explanation:
Explanation
By including nonkey columns, you can create nonclustered indexes that cover more queries. This is because the nonkeycolumns have the following benefits:
They can be data typesnot allowed as index key columns.
They are not considered by the Database Engine when calculating the number of index key columns or index key size.