Kafka-Streams talk!
Details
Location:
Bio: Tim Renner is a data scientist/data engineer in the Big Data and Analytics practice at Intersys. He is a consultant specializing in large-scale data and predictive modeling pipelines, having built projects ranging from real-time data ingestion to time series forecasting. Prior to Intersys, Tim worked as an engineer at ExoAnalytic Solutions on multi-sensor data fusion algorithms for ballistic missile target tracking and classification.
Abstract: The recent 0.10 release of Kafka introduced a major component to the Kafka ecosystem, Kafka Streams. Kafka Streams is a stream processing library that is tightly integrated with Kafka and is designed to provide simplified stream processing. In this talk I'll give an introduction to Kafka Streams: it's primary API abstractions (KStreams and KTables, as well as the low-level Processor), it's architecture, and how it differs from other stream processing frameworks. The stream processing space has become very crowded. My hope is that this talk will provide perspective on it's intended role in the streaming data space as well as what sets Kafka Streams apart.
Kafka-Streams talk!