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NEW QUESTION: 1
During an investigation, a computer is being seized. Which of the following is the FIRST step the analyst
should take?
A. Unplug the network cable and take screenshots of the desktop.
B. Initiate chain-of-custody documentation.
C. Perform a physical hard disk image.
D. Power off the computer and remove it from the network.
Answer: D

NEW QUESTION: 2
In welchem Anwendungsfall kann QRadar Vulnerability Manager zum Erkennen einer bestimmten Sicherheitsanfälligkeit und zur Behebung von Problemen verwendet werden?
QRadar Vulnerability Manager:
A. Patchen von Systemen für Sicherheitslücken mit hohem Risiko.
B. um Ereignisse von und zu einer bekannten Botnet-Site zu analysieren.
C. um zu suchen, welche Systeme für einen bestimmten Exploit anfällig sind und welche Intrusion Preventions-Systeme verwendet werden können, um diesen zu beheben.
D. um Pakete zu extrahieren und die Netzwerkverkehrssitzung zu rekonstruieren.
Answer: C

NEW QUESTION: 3
A patient presented to medical emergency with hyperglycemia. If we want to lower the blood sugar levels immediately, which type of insulin will we prefer?
A. NPH
B. Regular
C. Ultralente
D. Humalog (lispro H)
Answer: D
Explanation:
Explanation: In order to lower blood levels immediately, humalog (lispro H) is preferred because it is a fast acting, short duration insulin that acts within 5 to 15 minutes, peaking between 45to 90 minutes and lasting 3 to 4 hours.

NEW QUESTION: 4
You manage a process that performs analysis of daily web traffic logs on an HDInsight cluster. Each of the
250 web servers generates approximately 10megabytes (MB) 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. Move the log files into folders so that each day's logs are in their own folder
B. Combine the daily log files for all servers into one file
C. Increase the value of the hive.tez.containerize parameter
D. Increase the value of the mapreduce map memory parameter
E. Increase the number of worker nodes
Answer: A,B
Explanation:
Explanation
A: Typically, analytics engines such as HDInsight and Azure Data Lake Analytics has a per-five 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 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.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-performance-tuning-guidance