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NEW QUESTION: 1
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You have a table that has a clustered index and a nonclustered index. The indexes use different columns from the table. You have a query named Query1 that uses the nonclustered index.
Users report that Query1 takes a long time to report results. You run Query1 and review the following statistics for an index seek operation:

You need to resolve the performance issue.
Solution: You update statistics for the nonclustered index.
Does the solution meet the goal?
A. Yes
B. No
Answer: A
Explanation:
We see Actual Number of Row is 3571454, while Estimated Number of Rows is 0.
This indicates that the statistics are old, and need to be updated.

NEW QUESTION: 2
In a MapReduce job, the reducer receives all values associated with the same key. Which statement is most accurate about the ordering of these values?
A. The values are arbitrarily ordered, but multiple runs of the same MapReduce job will always have the same ordering.
B. The values are in sorted order.
C. Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
D. The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
Answer: C
Explanation:
Note:
*The Mapper outputs are sorted and then partitioned per Reducer.
*The intermediate, sorted outputs are always stored in a simple (key-len, key, value-len, value)
format.
*Input to the Reducer is the sorted output of the mappers. In this phase the framework fetches the
relevant partition of the output of all the mappers, via HTTP.
*A MapReduce job usually splits the input data-set into independent chunks which are processed
by the map tasks in a completely parallel manner. The framework sorts the outputs of the maps,
which are then input to the reduce tasks.
*The MapReduce framework operates exclusively on <key, value> pairs, that is, the framework
views the input to the job as a set of <key, value> pairs and produces a set of <key, value> pairs
as the output of the job, conceivably of different types.
The key and value classes have to be serializable by the framework and hence need to implement
the Writable interface. Additionally, the key classes have to implement the WritableComparable
interface to facilitate sorting by the framework.
Reference:MapReduce Tutorial

NEW QUESTION: 3
Click the Exhibit button.

You work for ISP A, as shown in the exhibit, and must configure R1 to use load balancing across both available links for all routes to ISP B's network. You start by configuring this policy:
policy-statement load-balance {
then {
load-balance per-packet;
}
}
Which two commands do you use to finish the configuration? (Choose two.)
A. set protocols bgp group isp-b multihop
B. set routing-options forwarding-table export load-balance
C. set protocols bgp group isp-b multipath
D. set routing-options forwarding-table import load-balance
Answer: B,C