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NEW QUESTION: 1
By default, what port does a TCP/IP printer port use?
A. 0
B. 1
C. 2
D. 3
Answer: C
Explanation:
Explanation/Reference:
Explanation:
A TCP/IP printer port is used to connect a printer directly to a network. It uses host port 9100 to communicate.

NEW QUESTION: 2
Displays text on a Visualforce page. You can customize the appearance of <apex:outputText> using CSS styles, in which case the generated text is wrapped in an HTML <span> tag. You can also escape the rendered text if it contains sensitive HTML and XML characters. This component does take localization into account.
Use with nested param tags to format the text values, where {n} corresponds to the n-th nested param tag.
The value attribute supports the same syntax as the MessageFormat class in Java. See the MessageFormat class JavaDocs for more information.
Warning:Encrypted custom fields that are embedded in the <apex:outputText> component display in clear text. The <apex:outputText> component doesn't respect the View Encrypted Data permission for users. To prevent showing sensitive information to unauthorized users, use the <apex:outputField> tag instead.
A. apex:outputText
B. apex:column
C. apex:message
D. apex:actionSupport
Answer: A

NEW QUESTION: 3
You have an Azure Stream Analytics query. The query returns a result set that contains 10,000 distinct values for a column named clusterID.
You monitor the Stream Analytics job and discover high latency.
You need to reduce the latency.
Which two actions should you perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Add a pass-through query.
B. Increase the number of streaming units.
C. Add a temporal analytic function.
D. Scale out the query by using PARTITION BY.
E. Convert the query to a reference query.
Answer: B,D
Explanation:
Explanation
C: Scaling a Stream Analytics job takes advantage of partitions in the input or output. Partitioning lets you divide data into subsets based on a partition key. A process that consumes the data (such as a Streaming Analytics job) can consume and write different partitions in parallel, which increases throughput.
E: 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. This capacity lets you focus on the query logic and abstracts the need to manage the hardware to run your Stream Analytics job in a timely manner.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption