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Exam DP-203 topic 4 question 31 discussion

Actual exam question from Microsoft's DP-203

Question #: 31
Topic #: 4

HOTSPOT -
You have an Azure event hub named retailhub that has 16 partitions. Transactions are posted to retailhub. Each transaction includes the transaction ID, the individual line items, and the payment details. The transaction ID is used as the partition key.
You are designing an Azure Stream Analytics job to identify potentially fraudulent transactions at a retail store. The job will use retailhub as the input. The job will output the transaction ID, the individual line items, the payment details, a fraud score, and a fraud indicator.
You plan to send the output to an Azure event hub named fraudhub.
You need to ensure that the fraud detection solution is highly scalable and processes transactions as quickly as possible.
How should you structure the output of the Stream Analytics job? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

Show Suggested Answer

Suggested Answer:

Box 1: 16 -
For Event Hubs you need to set the partition key explicitly.
An embarrassingly parallel job is the most scalable scenario in Azure Stream Analytics. It connects one partition of the input to one instance of the query to one partition of the output.

Box 2: Transaction ID -
Reference:
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-features#partitions

by rumosgf at May 31, 2021, 10:26 a.m.

Comments

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Preben

Highly Voted 3 years, 6 months ago

Correct. https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization Embarrassingly parallel jobs Step 3 and 4.

upvoted 44 times

Liz42

3 years, 1 month ago

The step 4 you’ve mentioned, @Preben, says: “The number of input partitions must equal the number of output partitions”. The documentation continues to talk about scenarios that are not embarrassingly parallel like @Maunik has mentioned below

upvoted 1 times

Liz42

3 years, 1 month ago

Disregard my above comment… meant to respond to another

upvoted 2 times

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Momoanwar

Highly Voted 11 months, 2 weeks ago

Correct cgatpgt : For high scalability and quick processing in Azure Stream Analytics, it's important to align the output event hub partitions with the input source. Since the input event hub `retailhub` has 16 partitions, the output event hub `fraudhub` should also have 16 partitions to match. This ensures that the partitioning scheme is consistent and can handle the volume of transactions efficiently. The partition key should be the `Transaction ID`, as this will ensure that all the events for a particular transaction will go to the same partition, maintaining the order of events which is crucial for transactional data and fraud detection scenarios. So the correct answers are: Number of partitions: 16 Partition key: Transaction ID

upvoted 5 times

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kkk5566

Most Recent 1 year, 3 months ago

correct

upvoted 1 times

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_Lukas_

1 year, 4 months ago

Number of partitions: Since the input event hub retailhub has 16 partitions, it makes sense to have the same number of partitions in the output event hub fraudhub to align the partitions. So the number of partitions should be 16. Partition key: Since the transaction ID was used as the partition key in the input event hub, using the same partition key in the output event hub ensures that the data for the same transaction ID is processed by the same partition in both event hubs. This makes the flow of data from one event hub to the other more efficient. So the partition key should be the Transaction ID.

upvoted 2 times

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Deeksha1234

2 years, 3 months ago

correct

upvoted 3 times

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nelineli

2 years, 5 months ago

"A per-device or user unique identity makes a good partition key, but other attributes such as geography can also be used to group related events into a single partition."

upvoted 3 times

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sdokmak

2 years, 6 months ago

Event Hub -> Event Hub: x:x partitions Event Hub -> Blob Storage: x:1 partitions or x:y partitions Blob Storage -> Event Hub: x:x partitions Blob Storage -> Blob Storage: x:1 partitions

upvoted 2 times

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Maunik

3 years, 2 months ago

Example of scenarios that are not embarrassingly parallel Mismatched partition count Input: Event hub with 8 partitions Output: Event hub with 32 partitions https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization Should be 8 partitions based on link above

upvoted 2 times

Aditya0891

2 years, 6 months ago

Maunik it did mention there that it results to "some level of parallelization". So I don't think this is the best option to choose if you have equal number of partitions (i.e 16 here) in your options

upvoted 1 times

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nichag

3 years, 4 months ago

Shouldn't the number of partitions only be 8, since the question only asks about the output?

upvoted 1 times

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rumosgf

3 years, 6 months ago

Why 16? Don't understand...

upvoted 2 times

wwdba

2 years, 9 months ago

An embarrassingly parallel job is the most scalable scenario in Azure Stream Analytics. It connects one partition of the input to one instance of the query to one partition of the output. The number of input partitions must equal the number of output partitions.

upvoted 2 times

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Davico93

2 years, 5 months ago

There are 2 eventhub, first has 16 partitions and the number of partitions asked is for the second eventhub, and both must be equals for better performance

upvoted 2 times

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mbravo

3 years, 6 months ago

Embarrassingly parallel jobs

upvoted 10 times

captainbee

3 years, 5 months ago

It's not THAT embarrassing

upvoted 10 times

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