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NEW QUESTION: 1
What name is given to the communication mechanism that expresses the core values of the enterprise, but should be concise and to the point?
A. Practices
B. Principles
C. Frameworks
D. Policies
Answer: B

NEW QUESTION: 2


Answer:
Explanation:

NEW QUESTION: 3
You observe that the number of spilled records from map tasks for exceeds the number of map output records. You child heap size is 1 GB and your io.sort.mb value is set to 100MB. How would you tune your io.sort.mb value to achieve maximum memory to disk I/O ratio?
A. Tune io.sort.mb value until you observe that the number of spilled records equals (or is as close to equals) the number of map output records.
B. Decrease the io.sort.mb value below 100M
C. For 1GB child heap size an io.sort.mb of 128MB will always maximum memory to disk I/O.
D. Increase the IO.sort.mb as high you can, as close to 1GB as possible.
Answer: A
Explanation:
here are a few tradeoffs to consider.
1.the number of seeks being done when merging files. If you increase the merge factor too high,
then the seek cost on disk will exceed the savings from doing a parallel merge (note that OS
cache might mitigate this somewhat).
2.Increasing the sort factor decreases the amount of data in each partition. I believe the number is
io.sort.mb / io.sort.factor for each partition of sorted data. I believe the general rule of thumb is to
have io.sort.mb = 10 * io.sort.factor (this is based on the seek latency of the disk on the transfer
speed, I believe. I'm sure this could be tuned better if it was your bottleneck. If you keep these in
line with each other, then the seek overhead from merging should be minimized
3.you increase io.sort.mb, then you increase memory pressure on the cluster, leaving less
memory available for job tasks. Memory usage for sorting is mapper tasks * io.sort.mb -- so you
could find yourself causing extra GCs if this is too high
Essentially,
If you find yourself swapping heavily, then there's a good chance you have set the sort factor too
high.
If the ratio between io.sort.mb and io.sort.factor isn't correct, then you may need to change
io.sort.mb (if you have the memory) or lower the sort factor.
If you find that you are spending more time in your mappers than in your reducers, then you may
want to increase the number of map tasks and decrease the sort factor (assuming there is
memory pressure).
Reference:How could I tell if my hadoop config parameter io.sort.factor is too small or too big?
http://stackoverflow.com/questions/8642566/how-could-i-tell-if-my-hadoop-config-parameter-io-
sort-factor-is-too-small-or-to

NEW QUESTION: 4
You are the Office 365 administrator for your company.
Users report that they have received significantly more spam messages over the past month than they normally receive.
You need to analyze trends for the email messages received over the past 60 days.
From the Office 365 admin center, what should you view?
A. The Mailbox content search and hold report
B. The Office 365Malware detections in sent mail report
C. The Received mail report
D. Messages on the Service health page
Answer: C
Explanation:
Explanation/Reference:
Explanation:
An Office 365 administrator can use the Mail Protection Reports in Office 365to view data about malware, spam, and rule detections for up to the last 90 days.
The reports can be viewed as a graph to display trends for email messages over a period of time; in this question, for the last 60 days. The graph view will tell you if the amount of good mail, malware and spam detected has increased or decreased over the time period of the report.
The Received Mail report shows the received mail grouped by traffic type:
Good mail - messages that were received and not identified as spam or malware.

Spam - messages identified as spam.

Malware - messages that contained malware.

Transport rules - messages that matched at least one rule.