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kafka-streams

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This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.
  • Updated Oct 13, 2020
  • Java

Real Time Big Data / IoT Machine Learning (Model Training and Inference) with HiveMQ (MQTT), TensorFlow IO and Apache Kafka - no additional data store like S3, HDFS or Spark required
  • Updated Nov 5, 2020
  • Jupyter Notebook
azkarra-streams
fhussonnois
fhussonnois commented May 12, 2020

Currenlty a StreamsExecutionEnvironment instance can be registed directly through the AzkarraContext#addExecutionEnvironment method and from the configuration.

The following example shows how to define an environment using configuration :

azkarra {
  // Create a environment for running the WordCountTopology
  environments = [
    {
      name: "dev"
      config = {}
      jo

Scalable stream processing platform for advanced realtime analytics on top of Kafka and Spark. LogIsland also supports MQTT and Kafka Streams (Flink being in the roadmap). The platform does complex event processing and is suitable for time series analysis. A large set of valuable ready to use processors, data sources and sinks are available.
  • Updated Oct 27, 2020
  • Java

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