From the course: Stream Processing Design Patterns with Kafka Streams

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Leaderboards: Review

Leaderboards: Review

- We have set up the Leaderboard pipeline and the helper functions. Now let's run the pipeline and review the results. We start with reviewing the typology that is built for leaderboard. We can see the Gaming Data Generator sending key value pairs for the scores updates. This data is retrieved from the topic and printed by the pipeline. We also see that the Leaderboard snapshot is printed every five seconds. The Leaderboard keeps changing with updated scores and leader positions as new data comes in. a real-time dashboard can now query this key from Redis and provide visualizations around it. A Leaderboard pipeline typically does not exist in vacuum. It is usually combined with other patterns discussed in this course. Also the Leaderboard snapshots can be published to another outgoing Kafka queue, for more downstream processing and analysis. We will now look at doing predictive analytics on streaming data in the next…

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