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www.altexsoft.com | ||
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www.onehouse.ai
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| | | | | Learn how Apache Flink?, Apache Kafka? Streams, and Apache Spark? Structured Streaming stack up against each other in terms of engine design, development experience, and more. | |
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timilearning.com
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| | | | | In the first lecture of this series, I wrote about MapReduce as a distributed computation framework. MapReduce partitions the input data across worker nodes, which process data in two stages: map and reduce. While MapReduce was innovative, it was inefficient for iterative and more complex computations. Researchers at UC Berkeley invented Spark to deal with these limitations. | |
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www.madewithtea.com
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| | | | | This article is about aggregates in stateful stream processing in general. I write about the differences between Apache Spark and Apache Kafka Streams along concrete code examples. Further, I list the requirements which we might like to see covered by a stream processing framework. | |
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compositecode.blog
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| | | I've worked with (** references at end of article) a number of Apache projects over the years, often pretty closely; Apache Cassandra, Apache Flink, Apache Kafka, Apache Zookeeper and numerous others. But the last few years I've not been immediately hands on with the technology. A few questions popped up recently, that fortunately I was... | ||
