Author: karden

It looks like, that separation between two infrastructure layers is increasing.
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Main purpose of using microservices architecture is to increase velocity of development and reduce system complexity.
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Big data technologies nowadays are very mature. Typically you use HDFS, or another distributed file systems, like S3, for storing data, Spark as a processor engine, and YARN as a resource manager. Next steps, wich you probably would like to achieve, are implement CI/CD (continuous integration and delivery) and move workload on demand in cloud.
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Remote submit is a powerful feature of Apache Spark. Why it is needed? For example, you can experiment with different versions of Spark, independent of what you have in the cluster. Or if you have no direct access to cluster you can start your spark jobs remotely.
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Tuning spark parameters is not a trivial task. In this short post I will explain how to tune some of the important parameters.
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I think, an idea to stream data back from HDFS into some streaming component, like Kafka, is coming from concept of Enterprise Service Bus (ESB). But after some thoughts, I have come to conclusion, that this concept is not useful in Big Data world.
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