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Spark Streaming in a Databricks Notebook

Tomaz Kastrun shows off Spark Streaming in a Databricks notebook:

Spark Streaming is the process that can analyse not only batches of data but also streams of data in near real-time. It gives the powerful interactive and analytical applications across both hot and cold data (streaming data and historical data). Spark Streaming is a fault tolerance system, meaning due to lineage of operations, Spark will always remember where you stopped and in case of a worker error, another worker can always recreate all the data transformation from partitioned RDD (assuming that all the RDD transformations are deterministic).

Click through for the demo.