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NEW QUESTION: 1
How many monitoring panels can the user create on the overview page?
A. 0
B. 1
C. 2
D. 3
Answer: A

NEW QUESTION: 2
George is the project manager of the NHQ Project and has a budget of $778,000. The project is scheduled to last for one year with an equal amount of work completed each quarter. The second quarter of the project has ended and George has spent $325,000 but has only finished forty percent of the project. Management needs a variance report for the project schedule. What value should George report in this instance?
A. $-34,500
B. -$13,800
C. .96
D. -$77,800
Answer: D
Explanation:
Schedule variance (SV) is a measure of schedule performance on a project. The variance notifies that the schedule is ahead or behind what was planned for this period in time. The schedule variance is calculated based on the following formula: SV = Earned Value (EV) - Planned Value (PV) If the resulting schedule is negative, it indicates that the project is behind schedule. A value greater than 0 shows that the project is ahead of the planned schedule. A value of 0 indicates that the project is right on target. The earned value in this instance is forty percent of the project budget, $778,000, and the planned value is $398,000 because George is to be fifty percent done at the end of the second quarter, as the work is spread evenly across all quarters. The schedule variance is -$77,800 for the project. Answer option A is incorrect. .96 represents the cost performance index. Answer option C is incorrect. -$34,500 represents the project's variance at completion if the project continues as is. Answer option D is incorrect. -$13,800 is the cost variance for the project.

NEW QUESTION: 3
You manage a process that performs analysis of daily web traffic logs on an HDInsight cluster. Each of 250 web servers generates approximately gigabytes (GB) of log data each day. All log data is stored in a single folder in Microsoft Azure Data Lake Storage Gen 2.
You need to improve the performance of the process.
Which two changes should you make? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Combine the daily log files for all servers into one file
B. Increase the value of the mapreduce.map.memory parameter
C. Move the log files into folders so that each day's logs are in their own folder
D. Increase the value of the hive.tez.container.size parameter
E. Increase the number of worker nodes
Answer: A,C
Explanation:
Explanation
A: Typically, analytics engines such as HDInsight and Azure Data Lake Analytics have a per-file overhead. If you store your data as many small files, this can negatively affect performance. In general, organize your data into larger sized files for better performance (256MB to 100GB in size). Some engines and applications might have trouble efficiently processing files that are greater than 100GB in size.
C: For Hive workloads, partition pruning of time-series data can help some queries read only a subset of the data which improves performance.
Those pipelines that ingest time-series data, often place their files with a very structured naming for files and folders. Below is a very common example we see for data that is structured by date:
\DataSet\YYYY\MM\DD\datafile_YYYY_MM_DD.tsv
Notice that the datetime information appears both as folders and in the filename.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-performance-tuning-guidance