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Learning Real-time Processing with Spark Streaming by Sumit Gupta

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Preface

Processing large data and producing business insights is one of the popular use cases, performed for deriving business intelligence (BI) over the historical data. Enterprises have been focusing on developing data warehouses (https://en.wikipedia.org/wiki/Data_warehouse) where they want to store the data fetched from every possible data source and leverage various BI tools for providing analytics/analysis over the data stored in these data warehouses. But developing data warehouses is a complex, time-consuming, and costly process. It may take months or sometimes years too.

No doubt the emergence of Hadoop and its ecosystem has provided a new architecture for solving large data problems. It provides a low cost and scalable solution, which ...

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