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NEW QUESTION: 1
会社のデータセンターにMicrosoft SOL Serverデータベースがあり、データをAmazon Aurora MySQLに移行することを計画しています。同社はすでにVie AWSスキーマ変換ツールを使用して、トリガー、ストアドプロシージャ、その他のスキーマオブジェクトをAurora MySQLに移行しています。データベースには1 TBのデータが含まれ、1日あたり1 M6を超えます。会社のデータセンターは、専用の1Gbpsを介してAWSに接続されていますAWS Direct Connect接続。
同社はデータをAurora MySQLに移行し、アプリケーションのダウンタイムを最小限に抑えて再構成を実行したいと考えています。
どのソリューションが会社の要件を満たしていますか？
A. AWS DMSレプリケーションインスタンスとタスクを作成して、既存のデータと進行中のレプリケーションをSQL ServerからAurora MySQLに移行するアプリケーションテストを実行し、データを新しいデータベースエンドポイントに移行する
B. Amazon S3でSQL Serverネイティブバックアップファイルを作成するAWS DMSレプリケーションインスタンスとタスクを作成し、SQL ServerバックアップファイルをAurora MySQLに復元するSQL ServerからAurora MySQLへの継続的なレプリケーション用に別のAWS DMSタスクを作成するアプリケーションテストを実行して移行する新しいデータベースエンドポイントへのデータ
C. Amazon S3でSQL Serverのデータベーススナップショットを作成するAmazon S3からAurora MySQLにデータベーススナップショットを復元するSQL ServerからAurora MySQLへの進行中のレプリケーションにAWS DMSレプリケーションインスタンスとタスクを作成するアプリケーションテストを実行し、データを新しいデータベースに移行する終点
D. 週末にアプリケーションをシャットダウンするAWS QMSレプリケーションインスタンスとタスクを作成し、SQL ServerからAurora MySQLに既存のデータを移行しますアプリケーションのテストと移行を実行します（データを新しいデータベースエンドポイントに移行します）
Answer: A
NEW QUESTION: 2
A customer is experiencing performance issues for an analytics workload.
Which IBM Storwize V7000 feature could most improve performance for the customer?
A. Thin provisioning
B. Storage Pool Balancing
C. Volume Mirror
D. Easy Tier
Answer: D
Explanation:
Explanation
Automated storage tiering with Easy Tier can help improve performance and lower costs by enabling more efficient use of flash storage or multiple tiers of disk drives. Easy Tier automatically identifies more active data and moves that data to faster storage such as flash. This helps organizations leverage flash storage for the data that can benefit the most. In fact, Easy Tier can deliver up to three times performance improvement with only five percent flash storage capacity.
Easy Tier can use any supported flash storage to accelerate any other storage. This approach delivers greater benefits from flash storage than tiering systems that are limited to just a single disk system
NEW QUESTION: 3
管理者がAmazon S3に500 GBのファイルを持っています。管理者は夜間のCOPYコマンドを10ノードのAmazon Redshiftクラスターに実行します。管理者は、COPYコマンドのパフォーマンスを最適化するためにデータを準備したいと考えています。
管理者はどのようにデータを準備する必要がありますか？
A. ファイルを同じサイズの10個のファイルに分割します。
B. ファイル形式をAVROに変換します。
C. ファイルを500個の小さなファイルに分割します。
D. gz圧縮を使用してファイルを圧縮します。
Answer: C
Explanation:
The critical aspect of this question is running the COPY command with the maximum amount of parallelism. The two options that will increase parallelism are B and
D. Option D will load one file per node in parallel, which will increase performance, but option B will have a greater effect because it will allow Amazon Redshift to load multiple files per instance in parallel (COPY can process one file per slice on each node). Compressing the files (option
A. is a recommended practice and will also increase performance, but not to the same extent as loading multiple files in parallel.
NEW QUESTION: 4
Sie analysieren die Leistung einer Datenbankumgebung.
Sie vermuten, dass in der aktuellen Datenbank mehrere Indizes fehlen.
Sie müssen eine priorisierte Liste der fehlenden Indizes für die aktuelle Datenbank zurückgeben.
Wie soll die Transact-SQL-Anweisung ausgefüllt werden? Ziehen Sie zum Beantworten die entsprechenden Transact-SQL-Segmente an die richtigen Positionen. Jedes Transact-SQL-Segment kann einmal, mehrmals oder gar nicht verwendet werden.
Möglicherweise müssen Sie die geteilte Leiste zwischen den Fenstern ziehen oder einen Bildlauf durchführen, um den Inhalt anzuzeigen.
Answer:
Explanation:
Erläuterung
Box 1: sys.db_db_missing_index_group_stats
Die Tabelle sys.db_db_missing_index_group_stats enthält die erforderlichen Spalten für die Hauptabfrage:
avg_total_user_cost, avg_user_impact, user_seeks und user scans.
Box 2: group_handle
Beispiel: Die folgende Abfrage ermittelt, welche fehlenden Indizes eine bestimmte fehlende Indexgruppe enthalten, und zeigt deren Spaltendetails an. In diesem Beispiel ist das fehlende Indexgruppenhandle 24.
SELECT migs.group_handle, mid. *
FROM sys.dm_db_missing_index_group_stats AS migs
INNER JOIN sys.dm_db_missing_index_groups AS mig
ON (migs.group_handle = mig.index_group_handle)
INNER JOIN sys.dm_db_missing_index_details AS mid
ON (mig.index_handle = mid.index_handle)
WO migs.group_handle = 24;
Box 3: sys.db_db_missing_index_group_stats
Die Tabelle sys.db_db_missing_index_group_stats enthält die erforderlichen Spalten für die Unterabfrage:
avg_total_user_cost und avg_user_impact.
Beispiel: Ermitteln der 10 fehlenden Indizes mit der höchsten erwarteten Verbesserung für Benutzerabfragen Mit der folgenden Abfrage wird ermittelt, welche 10 fehlenden Indizes in absteigender Reihenfolge die höchste erwartete kumulative Verbesserung für Benutzerabfragen bewirken.
TOP 10 AUSWÄHLEN *
FROM sys.dm_db_missing_index_group_stats
BESTELLEN NACH avg_total_user_cost * avg_user_impact * (user_seeks + user_scans) DESC;