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NEW QUESTION: 1
ある顧客が自律型データベース（ADB）への移行を望んでいますが、許容されるダウンタイムはごくわずかです。ゴールデンゲートは、移行中に使用することをお勧めしました。エンドユーザーを最大限に安心させるために、お客様は移行後の最初の6か月間のフォールバックシナリオとしてゴールデンゲートを使用することも希望しています。顧客が不満を述べた場合、オンプレミスのデータをADBインスタンスと同期してスイッチバックできます。
ゴールデンゲートを使用した移行についての正しい説明はどれですか。
A. キャプチャプロセスをADBにインストールできないため、ゴールデンゲートを使用したフォールバックシナリオは不可能です。
B. 説明されているシナリオは正しく、移行シナリオとフォールバックシナリオに使用できます。
C. ゴールデンゲートのオンプレミスインストールからはADBへの移行のみが可能です。
D. ゴールデンゲートクラウドサービスが存在するため、オンプレミスのゴールデンゲートはADBで認定されていません。
E. ADBに適用プロセスをインストールできないため、Golden Gateを使用してADBに移行することはできません。
Answer: A
Explanation:
Explanation
You can replicate data to Oracle Autonomous Data Warehouse Cloud and Autonomous Transaction Processing using Oracle GoldenGate On Premises and Oracle GoldenGate Cloud Service.
- You can configure the Autonomous Database instance as a target database for Oracle GoldenGate On Premises.
- You can't set up Oracle Autonomous Database Cloud database as a source database for Oracle GoldenGate On Premises.
https://www.oracle.com/database/technologies/datawarehouse-bigdata/adb-faqs.html#MIGRATION-BOOKMAR
NEW QUESTION: 2
Which statement is true about HSRP?
A. HSRP uses multicast address 224.0.0.2 and uses UDP port 1985.
B. HSRP uses multicast address 224.0.0.22 with TCP port 1122
C. HSRP uses broadcast address 224.0.0.22 with UDP port 32229
D. HSRP uses broadcast address 224.0.0.2 with UDP port 1985
Answer: A
NEW QUESTION: 3
エンジニアは、5分前にアクセス可能なデバイスをリモートで接続しようとします。
ネットワークに変更はありません。
接続の問題の理由はどれですか？
A. exec-timeout 0 0コマンドが設定されました
B. 誰かがコンソールに接続されています
C. SSHは有効になっていません
D. VTY回線は容量にあります
Answer: D
NEW QUESTION: 4
A Data Scientist needs to migrate an existing on-premises ETL process to the cloud. The current process runs at regular time intervals and uses PySpark to combine and format multiple large data sources into a single consolidated output for downstream processing.
The Data Scientist has been given the following requirements to the cloud solution:
- Combine multiple data sources.
- Reuse existing PySpark logic.
- Run the solution on the existing schedule.
- Minimize the number of servers that will need to be managed.
Which architecture should the Data Scientist use to build this solution?
A. Write the raw data to Amazon S3. Create an AWS Glue ETL job to perform the ETL processing against the input data. Write the ETL job in PySpark to leverage the existing logic. Create a new AWS Glue trigger to trigger the ETL job based on the existing schedule. Configure the output target of the ETL job to write to a "processed" location in Amazon S3 that is accessible for downstream use.
B. Use Amazon Kinesis Data Analytics to stream the input data and perform real-time SQL queries against the stream to carry out the required transformations within the stream. Deliver the output results to a "processed" location in Amazon S3 that is accessible for downstream use.
C. Write the raw data to Amazon S3. Schedule an AWS Lambda function to submit a Spark step to a persistent Amazon EMR cluster based on the existing schedule. Use the existing PySpark logic to run the ETL job on the EMR cluster. Output the results to a "processed" location in Amazon S3 that is accessible for downstream use.
D. Write the raw data to Amazon S3. Schedule an AWS Lambda function to run on the existing schedule and process the input data from Amazon S3. Write the Lambda logic in Python and implement the existing PySpark logic to perform the ETL process. Have the Lambda function output the results to a "processed" location in Amazon S3 that is accessible for downstream use.
Answer: A
Explanation:
Kinesis Data Analytics can not directly stream the input data.