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NEW QUESTION: 1
Your company uses Azure Stream Analytics to monitor devices.
The company plans to double the number of devices that are monitored.
You need to monitor a Stream Analytics job to ensure that there are enough processing resources to handle the additional load.
Which metric should you monitor?
A. Early Input Events
B. Late Input Events
C. Input Deserialization Errors
D. Watermark delay
Answer: D
Explanation:
There are a number of other resource constraints that can cause the streaming pipeline to slow down. The watermark delay metric can rise due to:
* Not enough processing resources in Stream Analytics to handle the volume of input events.
* Not enough throughput within the input event brokers, so they are throttled.
* Output sinks are not provisioned with enough capacity, so they are throttled. The possible solutions vary widely based on the flavor of output service being used.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-time-handling
NEW QUESTION: 2
Refer to the exhibit.
Based on the exhibited routing table, how will packets from a host within the 192.168.10.192/26 LAN be forwarded to 192.168.10.1?
A. The router will forward packets from R3 to R2 to R1.
B. The router will forward packets from R3 to R2 to R1 AND from R3 to R1.
C. The router will forward packets from R3 to R1 to R2.
D. The router will forward packets from R3 to R1.
Answer: B
Explanation:
From the routing table we learn that network 192.168.10.0/30 is learned via 2 equal-cost paths (192.168.10.9 &192.168.10.5) -> traffic to this network will be load-balancing.
NEW QUESTION: 3
Hadoop environments are optimized for:
A. Batch processing on large files.
B. Intensive calculation with little data.
C. Low latency data access.
D. Processing transactions (random access).
Answer: A
NEW QUESTION: 4
Answer:
Explanation:
