A. Option A
B. Option B
C. Option D
D. Option E
E. Option C
Answer: A
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NEW QUESTION: 1
Ein Netzwerktechniker unterstützt einen Benutzer, der Probleme beim Zugriff auf eine bestimmte Website hat. Andere Benutzer melden, dass die Website außerhalb des Büros zugänglich ist. Der Techniker vermutet, dass das Problem an der Firewall des Unternehmens liegt. Welche der folgenden Optionen sollte der Techniker zur Fehlerbehebung verwenden?
A. Dig
B. WiFi Analyzer
C. Packet Sniffer
D. Bandbreitentester
Answer: C
NEW QUESTION: 2
A. Option A
B. Option B
C. Option D
D. Option E
E. Option C
Answer: A
NEW QUESTION: 3
Which of the following are some of the commonly used SSL VPN technologies?
A. Port-forwarding technology and smart tunnels
B. Tor browser
C. SSL VPN tunnel client (such as the AnyConnect Secure Mobility Client)
D. Reverse proxy technology
Answer: A,C,D
NEW QUESTION: 4
Answer:
Explanation:
Explanation
From scenario: Topics are considered to be trending if they generate many mentions in a specific country during a 15-minute time frame.
Box 1: TimeStamp
Azure Stream Analytics (ASA) is a cloud service that enables real-time processing over streams of data flowing in from devices, sensors, websites and other live systems. The stream-processing logic in ASA is expressed in a SQL-like query language with some added extensions such as windowing for performing temporal calculations.
ASA is a temporal system, so every event that flows through it has a timestamp. A timestamp is assigned automatically based on the event's arrival time to the input source but you can also access a timestamp in your event payload explicitly using TIMESTAMP BY:
SELECT * FROM SensorReadings TIMESTAMP BY time
Box 2: GROUP BY
Example: Generate an output event if the temperature is above 75 for a total of 5 seconds SELECT sensorId, MIN(temp) as temp FROM SensorReadings TIMESTAMP BY time GROUP BY sensorId, SlidingWindow(second, 5) HAVING MIN(temp) > 75 Box 3: SlidingWindow Windowing is a core requirement for stream processing applications to perform set-based operations like counts or aggregations over events that arrive within a specified period of time. ASA supports three types of windows: Tumbling, Hopping, and Sliding.
With a Sliding Window, the system is asked to logically consider all possible windows of a given length and output events for cases when the content of the window actually changes - that is, when an event entered or existed the window.