Introduction to Map/Reduce, Hadoop and Cascading

April 19, 2011 @ 7:00pm – Introduction to Map/Reduce, Hadoop and Cascading


By now most people have heard of the NoSQL movement and map/reduce in particular, but most aren’t sure how to get started nor how to apply map/reduce to their business problem. In this presentation I will discuss use cases for map/reduce, the Apache implementation Hadoop and a very powerful tool to overcome some of the hadoop limitations, Cascading.


Chris Curtain

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Data Microservices with Spring Cloud Stream, Task, and Data Flow

Tuesday, July 19, 2016

Microservice based architectures are not just for distributed web applications! They are also a powerful approach for creating distributed stream and batch processing.

Spring Cloud Data Flow enables you to create and orchestrate standalone executable applications that communicate over messaging middleware such as Kafka and RabbitMQ that when run together, form a distributed stream processing application. It also allows users to create and orchestrate short lived microservices like batch jobs or boot applications that perform a task and then terminate when complete.

This allows you to scale, version and operationalize stream processing and task applications following microservice based patterns and practices on a variety of runtime platforms such as Cloud Foundry, Apache YARN and others.


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