DP-203 practice questions 181–190

1. Question 181 · 370 in bank

   You need to trigger an Azure Data Factory pipeline when a file arrives in an Azure Data Lake Storage Gen2 container. Which resource provider should you enable?

   • AMicrosoft.Sql
   • BMicrosoft.Automation
   • CMicrosoft.EventGrid
   • DMicrosoft.EventHub

   Show answer

   Answer: C

   Explanation

   Correct. C Azure Event Grids – Event-driven publish-subscribe model (think reactive programming) Azure Event Hubs – Multiple source big data streaming pipeline (think telemetry data) In this case its more suitable vs Event Hubs.

   Source: Adapted from community discussion — jv2120

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   Next question

2. Question 182 · 370 in bank

   You have two Azure Data Factory instances named ADFdev and ADFprod. ADFdev connects to an Azure DevOps Git repository. You publish changes from the main branch of the Git repository to ADFdev. You need to deploy the artifacts from ADFdev to ADFprod. What should you do first?

   • AFrom ADFdev, modify the Git configuration.
   • BFrom ADFdev, create a linked service.
   • CFrom Azure DevOps, create a release pipeline.
   • DFrom Azure DevOps, update the main branch.

   Show answer

   Answer: C

   References

   • Microsoft Learn

   Next question

3. Question 183 · 370 in bank

   You are designing an Azure Stream Analytics job to process incoming events from sensors in retail environments. You need to process the events to produce a running average of shopper counts during the previous 15 minutes, calculated at five-minute intervals. Which type of window should you use?

   • Asnapshot
   • Btumbling
   • Chopping
   • Dsliding

   Show answer

   Answer: C

   Explanation

   A hopping window outputs events at a regular time interval (the hop size) and can be used to produce overlapping windows.

   Source: Adapted from community discussion — bakamon

   References

   • Microsoft Learn

   Next question

4. Question 184 · 370 in bank

   HOTSPOT - You are designing a monitoring solution for a fleet of 500 vehicles. Each vehicle has a GPS tracking device that sends data to an Azure event hub once per minute. You have a CSV file in an Azure Data Lake Storage Gen2 container. The file maintains the expected geographical area in which each vehicle should be. You need to ensure that when a GPS position is outside the expected area, a message is added to another event hub for processing within 30 seconds. The solution must minimize cost. What should you include in the solution? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. Hot Area:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Box 1: Azure Stream Analytics - Box 2: Hopping - Hopping window functions hop forward in time by a fixed period. It may be easy to think of them as Tumbling windows that can overlap and be emitted more often than the window size. Events can belong to more than one Hopping window result set. To make a Hopping window the same as a Tumbling window, specify the hop size to be the same as the window size. Box 3: Point within polygon - Reference: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions

   Source: Adapted from community discussion — Alekx42

   References

   • Microsoft Learn
   • Microsoft Learn

   

   Next question

5. Question 185 · 370 in bank

   You are designing an Azure Databricks table. The table will ingest an average of 20 million streaming events per day. You need to persist the events in the table for use in incremental load pipeline jobs in Azure Databricks. The solution must minimize storage costs and incremental load times. What should you include in the solution?

   • APartition by DateTime fields.
   • BSink to Azure Queue storage.
   • CInclude a watermark column.
   • DUse a JSON format for physical data storage.

   Show answer

   Answer: B

   Explanation

   A. Partition by DataTime field Each partition will generate a file. Loading latency may reduce, but feel storage cost will increase because generate more folders and files for different partition. Is it right??? B. Sink to Azure Queue Storage. Read this document. Spark table files are stored in DBFS. Mount Azure Blob storage containers to Databricks File System (DBFS). If The Databricks ABS-AQS provides these two benefits, sounds like it is a correct answer. https://docs.microsoft.com/en-us/azure/databricks/spark/latest/structured-streaming/aqs C. Include a watermark column: For sure it is not correct Watermarks define how long your aggregate should wait around for data delay. D. User a Json format for physical data storage. - ??? Don't find any documents to compare physical data storage of JSON, CSV, and Parquet.

   Source: Adapted from community discussion — Canary_2021

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   Next question

6. Question 186 · 370 in bank

   HOTSPOT - You have a self-hosted integration runtime in Azure Data Factory. The current status of the integration runtime has the following configurations: ✑ Status: Running ✑ Type: Self-Hosted ✑ Version: 4.4.7292.1 ✑ Running / Registered Node(s): 1/1 ✑ High Availability Enabled: False ✑ Linked Count: 0 ✑ Queue Length: 0 ✑ Average Queue Duration. 0.00s The integration runtime has the following node details: ✑ Name: X-M ✑ Status: Running ✑ Version: 4.4.7292.1 ✑ Available Memory: 7697MB ✑ CPU Utilization: 6% ✑ Network (In/Out): 1.21KBps/0.83KBps ✑ Concurrent Jobs (Running/Limit): 2/14 ✑ Role: Dispatcher/Worker ✑ Credential Status: In Sync Use the drop-down menus to select the answer choice that completes each statement based on the information presented. NOTE: Each correct selection is worth one point. Hot Area:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Box 1: fail until the node comes back online We see: High Availability Enabled: False Note: Higher availability of the self-hosted integration runtime so that it's no longer the single point of failure in your big data solution or cloud data integration with Data Factory. Box 2: lowered - We see: Concurrent Jobs (Running/Limit): 2/14 CPU Utilization: 6% Note: When the processor and available RAM aren't well utilized, but the execution of concurrent jobs reaches a node's limits, scale up by increasing the number of concurrent jobs that a node can run Reference: https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime

   Source: Adapted from community discussion — MirandaL

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   

   Next question

7. Question 187 · 370 in bank

   You have an Azure Databricks workspace named workspace1 in the Standard pricing tier. You need to configure workspace1 to support autoscaling all-purpose clusters. The solution must meet the following requirements: ✑ Automatically scale down workers when the cluster is underutilized for three minutes. ✑ Minimize the time it takes to scale to the maximum number of workers. ✑ Minimize costs. What should you do first?

   • AEnable container services for workspace1.
   • BUpgrade workspace1 to the Premium pricing tier.
   • CSet Cluster Mode to High Concurrency.
   • DCreate a cluster policy in workspace1.

   Show answer

   Answer: B

   Explanation

   B is the correct answer. Automated (job) clusters always use optimized autoscaling. The type of autoscaling performed on all-purpose clusters depends on the workspace configuration. Standard autoscaling is used by all-purpose clusters in workspaces in the Standard pricing tier. Optimized autoscaling is used by all-purpose clusters in the Azure Databricks Premium Plan. https://docs.databricks.com/clusters/cluster-config-best-practices.html

   Source: Adapted from community discussion — ROBERSONWM

   References

   • Databricks documentation
   • Microsoft Learn

   Next question

8. Question 188 · 370 in bank

   Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are designing an Azure Stream Analytics solution that will analyze Twitter data. You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once. Solution: You use a tumbling window, and you set the window size to 10 seconds. Does this meet the goal?

   • AYes
   • BNo

   Show answer

   Answer: A

   Explanation

   this question appears at topic 2 question 18 and it said the correct answer was hopping window with 10'' window... so, what's the right correct answer?

   Source: Adapted from community discussion — praticewizards

   References

   • Microsoft Learn
   • Microsoft Learn

   Next question

9. Question 189 · 370 in bank

   Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are designing an Azure Stream Analytics solution that will analyze Twitter data. You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once. Solution: You use a session window that uses a timeout size of 10 seconds. Does this meet the goal?

   • AYes
   • BNo

   Show answer

   Answer: B

   Explanation

   The important thing to remember in a session window is the maximum duration. So theoretically a 10 second timout can still result in a window of 20 minutes for example (if every 9 seconds a new event comes in and the window never "closes"). If the maximum duration would be 10 seconds, I would agree. But as the question is worded right now, the answer is NO. https://docs.microsoft.com/en-us/stream-analytics-query/session-window-azure-stream-analytics

   Source: Adapted from community discussion — RyuHayabusa

   References

   • Microsoft Learn

   Next question

10. Question 190 · 370 in bank

    You use Azure Stream Analytics to receive data from Azure Event Hubs and to output the data to an Azure Blob Storage account. You need to output the count of records received from the last five minutes every minute. Which windowing function should you use?

    • ASession
    • BTumbling
    • CSliding
    • DHopping

    Show answer

    Answer: D

    Explanation

    A hopping window would not be the best option for this scenario because it does not allow you to set a sliding interval that is less than the window size. In a hopping window, the window size is fixed, and the window "hops" forward by a specified number of intervals. For example, if you set a hopping window size of five minutes and a hop size of one minute, then the first window would include data from the first five minutes, the second window would include data from the second through sixth minutes, the third window would include data from the third through seventh minutes, and so on. In this scenario, if you set the hopping window size to five minutes, you would only output the count of records every five minutes, which does not meet the requirement of outputting the count of records every minute. Therefore, a sliding window would be a better choice as it allows you to output data at smaller sliding intervals, which is required in this scenario.

    Source: Adapted from community discussion — Rossana

    Next question

Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page

DP-203 practice, question 181. 370 questions available.