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NEW QUESTION: 1
A client has configured a log source to forward events to IBM Security QRadar SIEM V7.2.7. It is recommended that the log source level be configured at the notice level by the DSM Guide, but the client has a policy to log all events at a debug level.
The Deployment Professional notices that the configured DSM is parsing most events, but some are being labeled as stored. The client is very interested in correlating some of the events that are being stored.
What should be created to meet this client's goal?
A. Custom event property
B. Custom DSM for parsing enhancement
C. Custom flow property
D. Custom DSM for parsing overrule
Answer: B
Explanation:
Explanation/Reference:
Parsing Enhancement - When the DSM is unable to parse correctly and the event is categorized as stored, the selected log source extension extends the failing parsing by creating a new event as if the new event came from the DSM.
References: IBM Security QRadar SIEM Version 7.1.0 MR1, Log Sources User Guide, page 6

NEW QUESTION: 2
You have the following Azure Stream Analytics query.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:
Explanation

Box 1: Yes
You can now use a new extension of Azure Stream Analytics SQL to specify the number of partitions of a stream when reshuffling the data.
The outcome is a stream that has the same partition scheme. Please see below for an example:
WITH step1 AS (SELECT * FROM [input1] PARTITION BY DeviceID INTO 10),
step2 AS (SELECT * FROM [input2] PARTITION BY DeviceID INTO 10)
SELECT * INTO [output] FROM step1 PARTITION BY DeviceID UNION step2 PARTITION BY DeviceID Note: The new extension of Azure Stream Analytics SQL includes a keyword INTO that allows you to specify the number of partitions for a stream when performing reshuffling using a PARTITION BY statement.
Box 2: Yes
When joining two streams of data explicitly repartitioned, these streams must have the same partition key and partition count.
Box 3: Yes
Streaming Units (SUs) represents the computing resources that are allocated to execute a Stream Analytics job. The higher the number of SUs, the more CPU and memory resources are allocated for your job.
In general, the best practice is to start with 6 SUs for queries that don't use PARTITION BY.
Here there are 10 partitions, so 6x10 = 60 SUs is good.
Note: Remember, Streaming Unit (SU) count, which is the unit of scale for Azure Stream Analytics, must be adjusted so the number of physical resources available to the job can fit the partitioned flow. In general, six SUs is a good number to assign to each partition. In case there are insufficient resources assigned to the job, the system will only apply the repartition if it benefits the job.
Reference:
https://azure.microsoft.com/en-in/blog/maximize-throughput-with-repartitioning-in-azure-stream-analytics/
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption

NEW QUESTION: 3

A. protected field
B. public static field
C. public static property
D. public property
Answer: D
Explanation:
Explanation
For a public the type or member can be accessed by any other code in the same assembly or another assembly that references it.
Reference: Access Modifiers (C# Programming Guide)
https://msdn.microsoft.com/en-us/library/ms173121.aspx