Part I: Develop stream processing apps using Kafka Streams on Oracle Cloud


In simple words, Kafka Streams is a library which you can include in your Java based applications to build stream processing applications on top of Apache Kafka. Other distributed computing platforms like Apache Spark, Apache Storm etc. are widely used in the big data stream processing world, but Kafka Streams brings some unique propositions in this area Kafka Streams provides a State Store feature using which applications can store its local processing results (the state). RocksDB is used as the default state store and it can be used in persistent or in-memory mode. In our sample application, the state which we care about is the count of occurrences of the keywords which we chose to follow -- how is it implemented? Oracle Application Container Cloud provides access to a scalable in-memory cache and it's used the custom state store in our use case It's possible to scale our stream processing service both ways (details in the documentation) i.e. elastically

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