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NEW QUESTION: 1
注：この質問は同じシナリオを提示する一連の質問の一部です。シリーズの各質問には固有の解決策が含まれています。解決策が規定の目標を満たしているかどうかを判断します。
複数のデータベースでMicrosoft SQL Server環境を管理します。
クエリが統計データを使用し、ローカル変数の値を初期化しないようにする必要があります。
解決策：データベースに対してLEGACY_CARDINALITY_ESTIMATIONオプションを有効にします。
解決策は目標を満たしていますか？
A. いいえ
B. はい
Answer: A
Explanation:
Explanation
LEGACY_CARDINALITY_ESTIMATION = { ON | OFF | PRIMARY }
Enables you to set the query optimizer cardinality estimation model to the SQL Server 2012 and earlier version independent of the compatibility level of the database. This is equivalent to Trace Flag 9481.
References:https://msdn.microsoft.com/en-us/library/mt629158.aspx
NEW QUESTION: 2
A. Option C
B. Option E
C. Option B
D. Option D
E. Option A
Answer: B,C,E
NEW QUESTION: 3
製造会社のデータエンジニアは、大量の非構造化データを受け取るデータ処理プラットフォームを設計しています。データエンジニアは、Amazon Redshiftで適切に構造化されたスタースキーマを作成する必要があります。
この目的のための最も効率的なアーキテクチャ戦略は何ですか？
A. Amazon EMRを使用して非構造化データを変換し、CSVデータを生成します。 Redshift内の分析スキーマにデータをコピーします。
B. AWS Marketplace ETLツールを使用してデータを正規化し、結果をAmazon S3に永続化し、AWS Lambdaを使用してデータをRedshiftに挿入します。
C. 非構造化データをRedshiftにロードし、文字列ペアリング関数を使用して、分析スキーマに挿入するための構造化データを抽出します。
D. データがAmazon S3に保存されるとき。 S3イベント通知とAWS Lambdaを使用して、ファイルコンテンツを変換します。 Redshiftの分析スキーマにデータを挿入します。
Answer: A
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