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So, how do you actually build a **_streaming data pipeline_** in Databricks? Let's break it down. First, you'll need to define your data source. This could be anything from a Kafka topic to a cloud storage bucket. Next, you'll write a streaming query using Structured Streaming. This query will specify how the data should be processed and transformed. For iimetro exodus can i kill traders example, you might want to filter the data, aggregate it, or join it with other datasets. Databricks makes this easy with a user-friendly interface and a wide range of built-in functions. The data transformations are performed using Spark's powerful processing engine. Spark is optimized for processing large volumes of data in real-time, making it the perfect choice for streaming workloads.
