Spark Structured Streaming with PySpark | DP-700 Exam Prep
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Want to understand how Spark Structured Streaming works in Microsoft Fabric? In this video, Aleksi explains how to stream data into Delta tables using PySpark notebooks and dives into the key concepts, settings, and best practices required for the DP-700 exam.
📌 What You’ll Learn:
🔷 What Spark Structured Streaming is and how it differs from batch processing
🔷 How to stream data from JSON files, Event Hub, or Kafka into Lakehouse Delta tables
🔷 Key PySpark functions like readStream, writeStream, start(), and checkpointLocation
🔷 How Spark handles micro-batches and ensures exactly-once processing
🔷 Using StreamingQuery to monitor and control streaming jobs in real time
💡 Why This Matters:
✨ Spark Structured Streaming is critical for real-time analytics and event-driven processing
✨ Understanding stream checkpoints, triggers, and session management is essential for the DP-700
✨ Learn to implement streaming logic using familiar batch-style code in Fabric notebooks
#MicrosoftFabric #DP700 #SparkStructuredStreaming #RealTimeData #DeltaLake #PySpark #StreamingData #DataEngineering #Azure #Lakehouse #DataPipelines #StreamingQuery
🏁 Timestamps:
00:00 Intro
00:45 Theory & Concepts
08:29 Demos & Tutorials
21:23 Practice Questions