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NEW QUESTION: 1
Which three statements are true about processing options in Web Services? (Choose three.)
A. SuppressExternalEvents and SuppressExternalRules properties can be defined only for Create, Update, and Destroy Processing Options.
B. FetchAllNames = true indicates the server that it should fetch all Names but does not fetch IDs.
C. SuppressExternalEvents and SuppressRules properties can also be defined for GetProcessingOptions.
D. SuppressExternalEvents = true and SuppressExternalRules = true indicates to the server that External Event and Business Rules should not be triggered.
E. FetchAllNames proprerty of GetProcessingOptions indicates to the server that all NameID Types should include both Name and ID.
F. SuppressExternalEvents = true and SuppressExternalRules = true indicates to the server that External Event and Business Rules should execute on operation completion.
Answer: C,D,E
Explanation:
Explanation
A: UpdateProcessingOptions include SuppressExternalEvents and SuppressRules.
B: FetchAllNames signals to the server that all NamedID types should include both the Name and the ID for that field.
C: SuppressExternalEvents is used to indicate that external events should not run after the operation completes.
SuppressRules is used to indicate that business rules should not run after the operation completes.
NEW QUESTION: 2
In a MapReduce job, you want each of you input files processed by a single map task. How do you configure a MapReduce job so that a single map task processes each input file regardless of how many blocks the input file occupies?
A. Write a custom FileInputFormat and override the method isSplittable to always return false.
B. Increase the parameter that controls minimum split size in the job configuration.
C. Set the number of mappers equal to the number of input files you want to process.
D. Write a custom MapRunner that iterates over all key-value pairs in the entire file.
Answer: A
Explanation:
Note: *// Do not allow splitting. protected boolean isSplittable(JobContext context, Path filename) { return false; } *InputSplits: An InputSplit describes a unit of work that comprises a single map task in a MapReduce program. A MapReduce program applied to a data set, collectively referred to as a Job, is made up of several (possibly several hundred) tasks. Map tasks may involve reading a whole file; they often involve reading only part of a file. By default, the FileInputFormat and its descendants break a file up into 64 MB chunks (the same size as blocks in HDFS). You can control this value by setting the mapred.min.split.size parameter in hadoop-site.xml, or by overriding the parameter in the JobConf object used to submit a particular MapReduce job. By processing a file in chunks, we allow several map tasks to operate on a single file in parallel. If the file is very large, this can improve performance significantly through parallelism. Even more importantly, since the various blocks that make up the file may be spread across several different nodes in the cluster, it allows tasks to be scheduled on each of these different nodes; the individual blocks are thus all processed locally, instead of needing to be transferred from one node to another. Of course, while log files can be processed in this piece-wise fashion, some file formats are not amenable to chunked processing. By writing a custom InputFormat, you can control how the file is broken up (or is not broken up) into splits.
NEW QUESTION: 3
Amazon EC2管理者は、複数のユーザーを含むIAMグループに関連付けられた次のポリシーを作成しました。
このポリシーの効果は何ですか？
A. ユーザーのソースIPが10.100の場合、ユーザーはus-east-1リージョンのEC2インスタンスを終了できません。
100. 254
B. ユーザーは、IPアドレス10.100のEC2インスタンスを終了できます。 us-east-1リージョンの1001
C. ユーザーはus-east-1を除くすべてのAWSリージョンのEC2インスタンスを終了できます。
D. ユーザーのソースIPが次の場合、ユーザーはus-east-1リージョンのEC2インスタンスを終了できます
10.100.100.254
Answer: A