In this webinar we explain which are some of the problems of streaming analytics, and why they are different to batch/big data analytics. Then we go into introducing some basic streaming concepts, like event queues, event processors, event vs processing time, and delivery guarantees. We end this first part of the series presenting a few of the most common open source components for streaming (Kafka, Spark, Flink, Cassandra, or ElasticSearch) and we mention the different options you have to run them on AWS.
17. Probably less than you think
~20 lines of JAVA code (plus a
few hundreds with imports,
POJOs, and boilerplate, because
JAVA)
a simple GROUP BY statement in
SQL with streaming extensions
(plus a few lines of boilerplate for
schema definition)
OR