Making Apache Spark Effortless for All of Uber

Apache Spark is a foundational piece of Uber’s Big Data infrastructure that powers many critical aspects of our business. We currently run more than one hundred thousand Spark applications per day, across multiple different compute environments. Spark’s versatility, which allows us to build applications and run them everywhere that we need, makes this scale possible. However, our ever-growing infrastructure means that these environments are constantly changing, making it increasingly difficult for both new and existing users to give their applications reliable access to data sources, compute resources, and supporting tools.
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Scaling Spark Streaming for Logging Event Ingestion

Walking over a stream during an Airbnb Experience in Kuala Lumpur. Searching, viewing, and booking such Experiences will all produce logging events that will be processed by our stream processing framework. Logging events are emitted from clients (such as mobile apps and web browser) and online services with key information and context about the actions or operations. Each event carries a specific piece of information. For example, when a guest searches for a beach house in Malibu on Airbnb.
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