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Exam DP-700 topic 2 question 39 discussion

Actual exam question from Microsoft's DP-700
Question #: 39
Topic #: 2
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You need to recommend a Fabric streaming solution that will use the sources shown in the following table.



The solution must minimize development effort.

What should you include in the recommendation for each source? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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zxc01
Highly Voted 2 months, 3 weeks ago
Eventstream has 1MB max size limitation, streaming dataflow has been retired in Fabric. We just can choose between Apache Spark Structured Streaming and data pileline(normally it will be used for batch loging solution not Fabric streaming solution). I cannot understand if all of 3 sources have to match Apache Spark Structured Streaming. I have to make these answers: Source 1, semi-structured, contains a bigint column, Apache Spark Structured Streaming can match it if we choose longType. Source 2 is hard to make decision because lost details, I tend to choose data pipleline. Source 3 has image, we can use copy activity in data pipeline and set file format to Binary.In order to match "The solution must minimize development effort."
upvoted 6 times
Sr18
1 month, 1 week ago
Streaming is not exactly same as ETL Copy Activity.
upvoted 1 times
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contactodonuno
Most Recent 2 weeks, 1 day ago
| Source | Data Type | Message Size | Recommended Option | Justification | | ----------- | -------------------------- | ------------ | --------------------------------------- | ---------------------------------------------------------------------------- | | **Source1** | Semi-structured (bigint) | **10 MB** | ✅ **Apache Spark Structured Streaming** | Streaming Dataflow can't reliably handle >4 MB; Spark handles large messages | | **Source2** | Structured (19 columns) | **25 MB** | ✅ **Apache Spark Structured Streaming** | Too large for Streaming Dataflow; Spark is built for this scale | | **Source3** | Unstructured (with images) | **5 MB** | ✅ **Apache Spark Structured Streaming** | Binary data + medium size → Spark is the only suitable and scalable option |
upvoted 3 times
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contactodonuno
2 weeks, 1 day ago
Como o objetivo é minimizar o esforço de desenvolvimento, a melhor escolha costuma ser: ✅ A streaming dataflow – quando streaming é necessário mas com pouco código. ❌ Apache Spark Structured Streaming – mais código. ❌ An eventstream – requer integração adicional. ❌ A data pipeline – bom para batch, não para streaming.
upvoted 1 times
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DarioReymago
3 weeks, 6 days ago
My selection: - An eventstream - A streaming dataflow - Apache Spark Structured Streaming
upvoted 2 times
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PBridge
1 month, 1 week ago
Source1: An eventstream Source2: A streaming dataflow Source3: Apache Spark Structured Streaming Confirmed with Chatgpt
upvoted 2 times
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PBridge
1 month, 1 week ago
Source1 Apache Spark Structured Streaming Source2 An eventstream Source3 Apache Spark Structured Streaming
upvoted 2 times
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upliftinghut
1 month, 3 weeks ago
This is such a tricky question. Usually, data from streaming source is not so big. If data size is smaller than 1MB => event stream however data size > 1 MB => Apache Spark structured streaming. Data pipeline doesn't support streaming.
upvoted 4 times
Sr18
1 month, 1 week ago
Indeed very tricky, In my for all it will be Spark Structured Streaming
upvoted 3 times
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xmh5025
1 month, 3 weeks ago
eventstream has a message limit of 1 MB. Data pipeline for batch processing, streaming dataflow is retired. should be Spark Structured Streaming for all.
upvoted 3 times
DarioReymago
3 weeks, 6 days ago
streaming dataflow is not retired
upvoted 1 times
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minami1998
1 month, 3 weeks ago
Eventstream: Max message size 1 MB https://learn.microsoft.com/en-us/fabric/real-time-intelligence/event-streams/overview?tabs=enhancedcapabilities#limitations
upvoted 1 times
minami1998
1 month, 3 weeks ago
Streaming Dataflows: [Data Types] - DateTime: Date and time field in ISO format - Float: Decimal number - Int: Integer number - Record: Nested object with multiple records - String: Text https://learn.microsoft.com/en-us/power-bi/transform-model/dataflows/dataflows-streaming?utm_source=chatgpt.com#data-types
upvoted 1 times
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a85becd
2 months, 1 week ago
1. **Source1 (Semi-structured data, 10 MB)**: - **Solution**: **Eventstream** - Eventstream is optimized for handling semi-structured data and can efficiently process messages with a `bigint` column, while providing real-time streaming capabilities. 2. **Source2 (Structured data, 25 MB)**: - **Solution**: **Stream Dataflow** - Stream Dataflow is an appropriate choice for structured data. It allows easy ingestion and transformation of structured datasets, minimizing development effort. 3. **Source3 (Unstructured data with images, 5 MB)**: - **Solution**: **Spark Structured Streaming** - Spark Structured Streaming is ideal for processing unstructured data, such as images, in real-time. It provides flexibility for working with diverse data formats.
upvoted 2 times
a85becd
2 months, 1 week ago
Source1: cannot be Data pipeline as it is designed for batch processing Source2: I need to change it to Spark streaming Structure as Stream dataflow is retired in Fabric Source 3:: cannot be Eventstream as it is not designed to handle unstructured data like images or multimedia
upvoted 1 times
a85becd
2 months, 1 week ago
Source1- Event Stream (Stream Solution+ Semi Structured file handling) Source2: Spark Structured Streaming (Stream Solution + structured file Handling) Source3: Spark Structured Streaming (Stream Solution + ustructured file Handling) Cannot: Data pipeline, as it is only for batch processing, not optimized for Stream Cannot: Stream dataflow, as it is retired in Fabric
upvoted 1 times
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zxc01
2 months, 3 weeks ago
I think both Apache Spark Structured Streaming and data pipeline(if we think it can play role of Fabric streaming solution) can match it. Howerver, question said "The solution must minimize development effort", data pipeline is better? Source2 didn't give enough details, if this structured data is database and configured with CDC, then eventstream is option. Source 3 should be data pipeline.
upvoted 1 times
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