It has been a while since you left the easy days of batch processing behind: the lazy ETL jobs that had all night to run, the relaxed SLAs that let you take lunches like Don Draper, the languid bankers’ hours: the salad days of your data processing career. Those days are over now, and producing real-time results on streaming data is the new order of the day. Two seconds is the new overnight.
Apache Kafka is a de facto standard streaming data processing platform, being widely deployed as a messaging system, and having a robust data integration framework (Kafka Connect) and stream processing API (Kafka Streams) to meet the needs that common attend real-time message processing.
On top of that, Kafka now offers KSQL, a declarative, SQL-like stream processing language. What once took some moderately sophisticated Java code can now be done at the command line with a familiar and eminently approachable syntax. Come to this talk for an overview of KSQL with live coding on live streaming data.
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Processing Streaming Data with KSQL
Tim Berglund
Tim is a teacher, author, and technology leader with Confluent, where he serves as the Senior Director of Developer Experience.