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NEW QUESTION: 1
You work as the developer in an IT company. Recently your company has a big customer. The customer runs a large supermarket chain. You're appointed to provide technical support for the customer. Now according to the customer requirement, you are developing a server application. The application will transmit sensitive information on a network. An X509Certificate object named certificate and a TcpClient object named client have been created. Now you have to create an SslStream to communicate by using the Transport Layer Security 1.0 protocol. In the options below, which code segment should you use?
A. SslStream ssl = new SslStream(client.GetStream());ssl.AuthenticateAsServer( certificate, false, SslProtocols.None, true);
B. SslStream ssl = new SslStream(client.GetStream());ssl.AuthenticateAsServer( certificate, false, SslProtocols.Ssl2, true);
C. SslStream ssl = new SslStream(client.GetStream()); ssl.AuthenticateAsServer( certificate, false, SslProtocols.Tls, true);
D. SslStream ssl = new SslStream(client.GetStream());ssl.AuthenticateAsServer( certificate, false, SslProtocols.Ssl3, true);
Answer: C

NEW QUESTION: 2
The Hadoop framework provides a mechanism for coping with machine issues such as faulty configuration or impending hardware failure. MapReduce detects that one or a number of machines are performing poorly and starts more copies of a map or reduce task. All the tasks run simultaneously and the task finish first are used. This is called:
A. Combine
B. IdentityMapper
C. IdentityReducer
D. Speculative Execution
E. Default Partitioner
Answer: D
Explanation:
Explanation/Reference:
Speculative execution: One problem with the Hadoop system is that by dividing the tasks across many nodes, it is possible for a few slow nodes to rate-limit the rest of the program. For example if one node has a slow disk controller, then it may be reading its input at only 10% the speed of all the other nodes. So when 99 map tasks are already complete, the system is still waiting for the final map task to check in, which takes much longer than all the other nodes.
By forcing tasks to run in isolation from one another, individual tasks do not know where their inputs come from. Tasks trust the Hadoop platform to just deliver the appropriate input. Therefore, the same input can be processed multiple times in parallel, to exploit differences in machine capabilities. As most of the tasks in a job are coming to a close, the Hadoop platform will schedule redundant copies of the remaining tasks across several nodes which do not have other work to perform. This process is known as speculative execution. When tasks complete, they announce this fact to the JobTracker. Whichever copy of a task finishes first becomes the definitive copy. If other copies were executing speculatively, Hadoop tells the TaskTrackers to abandon the tasks and discard their outputs. The Reducers then receive their inputs from whichever Mapper completed successfully, first.
Reference: Apache Hadoop, Module 4: MapReduce
Note:
* Hadoop uses "speculative execution." The same task may be started on multiple boxes. The first one to finish wins, and the other copies are killed.
Failed tasks are tasks that error out.
* There are a few reasons Hadoop can kill tasks by his own decisions:
a) Task does not report progress during timeout (default is 10 minutes) b) FairScheduler or CapacityScheduler needs the slot for some other pool (FairScheduler) or queue (CapacityScheduler).
c) Speculative execution causes results of task not to be needed since it has completed on other place.
Reference: Difference failed tasks vs killed tasks

NEW QUESTION: 3
Stephen is the project manager of the GBB project. He has worked with two subject matter experts and his project team to complete the risk assessment technique. There are approximately 47 risks that have a low probability and a low impact on the project. Which of the following answers best describes what Stephen should do with these risk events?
A. Because they are low probability and low impact, the risks can be dismissed.
B. Because they are low probability and low impact, Stephen should accept the risks.
C. The low probability and low impact risks should be added to awatchlist for future monitoring.
D. The low probability and low impact risks should be added to the risk register.
Answer: C

NEW QUESTION: 4
AWSアカウントの所有者が複数のIAMユーザーを設定しました。
1人のIAMユーザーにはCloudWatchアクセスのみがあります。
彼は、CPU使用率がしきい値制限を下回ったときにEC2インスタンスを停止させるアラームアクションを設定しました。
この場合はどうなりますか？
A. CloudWatchアラームを使用してインスタンスを停止することはできません
B. ユーザーはアクションを設定できますが、ユーザーにEC2権限がない場合は実行されません
C. CloudWatchはアクションが実行されるとインスタンスを停止します
D. 権限がないため、ユーザーはEC2にアラームを設定できません
Answer: B
Explanation:
Amazon CloudWatchアラームは、ユーザーが指定した期間に渡って単一のメトリクスを監視し、一定期間内の特定のしきい値に対するメトリクスの値に基づいて1つ以上のアクションを実行します。ユーザーは、一定期間CPU使用率が一定のしきい値を下回ったときにインスタンスを停止するアクションを設定できます。 EC2アクションは、EC2アクションの一部としてインスタンスを終了または停止することができます。 IAMユーザーがAmazon CloudWatchに対する読み取り/書き込み権限を持っているがAmazon EC2に対する権限を持っていない場合でも、彼はアラームを作成できます。
ただし、停止または終了アクションはAmazon EC2インスタンスでは実行されません。