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•Solution Architect
•Hadoop - developer
•Maker
@igfasouza
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
7
From batch to stream processing
Copyright Š 2019 Oracle and/or its affiliates.
Copyright Š 2019 Oracle and/or its affiliates.
Copyright Š 2019 Oracle and/or its affiliates.
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
learn Kafka and Event Streams with fun
Thank you
Igor De Souza
Solution Architect
@igfasouza
igfasouza@gmail.com
www.igfasouza.com/blog

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learn Kafka and Event Streams with fun

Editor's Notes

  • #2: Stream processing and Kafka with Fun Introduction
  • #3: Stream processing is becoming something like a “grand unifying paradigm” for data processing. Stream processing is the act of continuous incorporate new data to compute a result. Event stream processing (ESP) is the practice of taking action on a series of data points that originate from a system that continuously creates data.
  • #5: Streaming is processing of data in motion Streaming is data that is continuously generated by different sources. Streaming is the continuous high-speed transfer of large amounts of data from a source system to a target. Programming paradigm that allows some applications to more easily exploit a limited form of parallel processing.
  • #6: Kafka core Kafka connect Kafka stream KSQL
  • #11: ksqlDB Rocksdb – key value store
  • #13: The idea here is to focus on scenarios where the Kafka clients and the Kafka brokers are running on the edge. This enables edge processing, integration, decoupling, low latency, and cost-efficient data processing.
  • #16: Real-Time Locating System (RTLS) enables identifying and tracking the location of objects or people in real-time. It is used everywhere in transportation and logistics across industries.
  • #17: Smart devices are all of the everyday objects made intelligent with advanced computers, including AI and machine learning, and networked to form the internet of things (IoT). Not just computers and smartphones, but everything: clocks, speakers, lights, doorbells, cameras, windows, window blinds, hot water heaters, appliances, cooking utensils, you name it.
  • #18: The term connected vehicles refer to applications, services, and technologies that connect a vehicle to its surroundings. A connected vehicle includes the different communication devices (embedded or portable) present in the vehicle, that enable in-car connectivity with other devices present in the vehicle and/or enable connection of the vehicle to external devices, networks, applications, and services.
  • #27: It is a basic, but functional setup to run experiments and collect data from our small cars