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The developer to load webpage click and view data (customer id, timestamp, action, url) into a partitioned fileset. After loading the data, the developer wants to de-duplicate records and calculate how many times each customer clicked and viewed over the past hour, past day, and past month. 

User Stories:

1. (3.4) A developer should be able to create pipelines that contain aggregations (GROUP BY -> count/sum/unique)
2. (3.5) A developer should be able to create a pipeline with multiple sources, with one happening after the otherA control some parts of the pipeline running before others. For example, one source -> sink branch running before another source -> sink branch.
3. (3.5) A developer should be able to use a Spark ML job as a pipeline stage
4. A (3.4) A developer should be able to rerun failed pipeline runs without reconfiguring the pipeline
5. A (3.4) A developer should be able to de-duplicate records in a pipeline
6. A (3.5) A developer should be able to join multiple branches of a pipeline
7. A (3.5) A developer should be able to use an Explore action as a pipeline stage
8. A (3.5) A developer should be able to create pipelines that contain Spark Streaming jobs
9. A (3.5) A developer should be able to create pipelines that run based on various conditions, including input data availability and Kafka events

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