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NEW QUESTION: 1
Infosphere Streams does not allow for the combining of high velocity real-time data with data in a warehouse for historical analysis.
A. True
B. False
Answer: B
Explanation:
Reference: ftp://ftp.software.ibm.com/software/data/db2/9/labchats/20120327-slides.pdf (Slide 31)

NEW QUESTION: 2
How does partition pruning, a 11gR2 database feature, help to improve performance on an Exadata Database Machine?
A. Partition pruning allows you to reduce a 5 TB I/O operation to a much smaller I/O operation and therefore, enables a much faster return of information.
B. Partition pruning allows you to reduce a 5 TB I/O operation to a larger I/O operation and therefore, forces the use of the Smart Scan technology.
C. Using partition pruning can force the optimizer to use that method instead of Smart Scan. Partitioning in Exadata should be used wisely,
D. Partition pruning is not a supported option in the 11gR2 database code that runs on an Exadata Machine, due to issues with Cost Based Optimizer plans.
E. Partition pruning allows you to reduce the size of the physical table by reducing fragmentation within the individual tables.
Answer: A
Explanation:
Partition pruning allows you to reduce a 5TB I/O operation to a much smaller I/O operation and therefore much faster return of the information.

NEW QUESTION: 3
The default settings for the console port of an ?chipset switch are 9600 bps/8 data-bits/one stop-bit/no parity/software flow control
A. TRUE
B. FALSE
Answer: A

NEW QUESTION: 4
会社は、AWSにデプロイされているアプリケーションにCI / CDパイプラインを実装したいと考えています。社内には、セキュリティの欠陥をチェックするオンプレミスでホストされるソースコード分析ツールもあります。このツールはまだAWSに移行されておらず、オンプレミスでのみアクセスできます。同社は、コードをコンパイルする前に、パイプラインの一部としてソースコードに対してチェックを実行したいと考えています。チェックの完了には、数分から1時間かかります。
DevOpsエンジニアはどのようにしてこれらの要件を満たすことができますか?
A. AWS CodePipelineを使用してパイプラインを作成し、カスタムアクションタイプを作成します。オンプレミスでホストされているハードウェアで実行するカスタムアクションのジョブワーカーを作成します。ジョブワーカーは、オンプレミスコード分析ツールで実行中のセキュリティチェックを処理し、ジョブの結果をCodePipelineに返します。ソースステージの後にパイプラインがカスタムアクションを呼び出すようにします。
B. AWS CodePipelineを使用してパイプラインを作成します。ソースステージの後にステップを追加して、ソースコード分析ツールでテストを呼び出すオンプレミスのホストされたWebサービスにHTTPS要求を行います。
分析が完了すると、Webサービスは結果をCodePipelineが提供するAmazon S3出力場所に配置することで結果を送り返します。
C. AWS CodePipelineを使用してパイプラインを作成します。入力ソースコードをオンプレミスの場所にコピーするシェルスクリプトを作成します。ソースコード分析ツールを呼び出して、結果をCodePipelineに返します。ソースステージの後にカスタムスクリプトアクションを追加して、シェルスクリプトを呼び出します。
D. AWS CodePipelineを使用してパイプラインを作成します。ソースステージの後にAWS Lambda関数を呼び出すアクションをパイプラインに追加します。 Lambda関数が、CodePipelineからのソース入力に対してオンプレミスでソースコード分析ツールを呼び出すようにします。次に、関数は実行の完了を待機し、指定されたAmazon S3の場所に出力を配置します。
Answer: A

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