Monitoring Car Data With Spark And Kafka

Carol McDonald builds a model to determine where Uber cars are clustered:

Uber trip data is published to a MapR Streams topic using the Kafka API. A Spark streaming application, subscribed to the topic, enriches the data with the cluster Id corresponding to the location using a k-means model, and publishes the results in JSON format to another topic. A Spark streaming application subscribed to the second topic analyzes the JSON messages in real time.

This is a fairly detailed post, well worth the read.

Related Posts

Cassandra To Kafka Connect

Mike Barlotta shows how to feed data into Kafka from Cassandra via Kafka Connect.  Part one involves basic setup: Modeling data in Cassandra must be done around the queries that are needed to access the data (see this article for details). Typically this means that there will be one table for each query and data (in our […]

Read More

Use Cases For Apache Kafka

Amy Boyle shows a few scenarios where New Relic uses Apache Kafka: The Events Pipeline team is responsible for plumbing some of New Relic’s core data streams-specifically, event data. These are fine-grained nuggets of monitoring data that record a single event at a particular moment in time. For example, an event could be an error thrown […]

Read More


January 2017
« Dec Feb »