Apache Kafka and KSQL in Action : Let’s Build a Streaming Data Pipeline! by Robin Moffatt скачать в хорошем качестве

Apache Kafka and KSQL in Action : Let’s Build a Streaming Data Pipeline! by Robin Moffatt

Subscribe to Devoxx on YouTube @ https://bit.ly/devoxx-youtube Like Devoxx on Facebook @   / devoxxcom   Follow Devoxx on Twitter @   / devoxx   Have you ever thought that you needed to be a programmer to do stream processing and build streaming data pipelines? Think again! Apache Kafka is a distributed, scalable, and fault-tolerant streaming platform, providing low-latency pub-sub messaging coupled with native storage and stream processing capabilities. Integrating Kafka with RDBMS, NoSQL, and object stores is simple with Kafka Connect, which is part of Apache Kafka. KSQL is the open-source SQL streaming engine for Apache Kafka, and makes it possible to build stream processing applications at scale, written using a familiar SQL interface. In this talk we’ll explain the architectural reasoning for Apache Kafka and the benefits of real-time integration, and we’ll build a streaming data pipeline using nothing but our bare hands, Kafka Connect, and KSQL. Gasp as we filter events in real time! Be amazed at how we can enrich streams of data with data from RDBMS! Be astonished at the power of streaming aggregates for anomaly detection! Robin Moffatt From Confluent Robin is a Developer Advocate at Confluent, the company founded by the creators of Apache Kafka, as well as an Oracle ACE Director and Developer Champion. His career has always involved data, from the old worlds of COBOL and DB2, through the worlds of Oracle and Hadoop, and into the current world with Kafka. His particular interests are analytics, systems architecture, performance testing and optimization. He blogs at http://cnfl.io/rmoff and http://rmoff.net/ (and previously http://ritt.md/rmoff) and can be found tweeting grumpy geek thoughts as @rmoff. Outside of work he enjoys drinking good beer and eating fried breakfasts, although generally not at the same time.