kafka

Contributing to Open Source Big Data Tech

abgoswam beam, flink, kafka, mahout, spark

There are 6 projects that I have on my list of Open Source Technologies in the Big Data space that I want to contribute to :

(in no particular order)

  • Spark
  • Kafka
  • Beam
  • Flink
  • Mahout
  • Streams

 

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Understanding Kafka Streaming using the WordCountDemo

abgoswam kafka

I have been spending some time this weekend trying to understand Kafka.

Kafka has four core APIs:

  • The Producer API :
    • allows an application to publish a stream records to one or more Kafka topics.
  • The Consumer API
    • allows an application to subscribe to one or more topics and process the stream of records produced to them.
    • the Producer + Consumer API’s are essentially achieving the functionality provided by Azure’s EventHub
  • The Streams API :
    • allows an application to act as a stream processor, consuming an input stream from one or more topics and producing an output stream to one or more output topics, effectively transforming the input streams to output streams.
    • the Streams API is achieving what Azure’s ASA does.
  • The Connector API
    • allows building and running reusable producers or consumers that connect Kafka topics to existing applications or data systems. For example, a connector to a relational database might capture every change to ? 🙂
    • the Connector API is achieving what Azure’s ADF does.

 

The documentation uses the WordCountDemo as the motivating example for the Streaming scenario. So I decided to spend some time over the weekend understanding this API better.

References:

Code: