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+title = "Why use Spark?"
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+date = 2020-06-08T21:00:00
+draft = false
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+authors = ["Gabriel Teotonio"]
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+tags = ["spark", "hadoop"]
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+summary = ""
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+When I started my professional career as a Data Scientist two years ago, the first challenge introduced was be able to deal with large data sets in a cloud platform. Among many tooling frameworks to get started by the time, [Spark](https://spark.apache.org/) played a big role and there are many reasons for that. Spark is considered as a *unified analytics engine for large-scale data processing* and its generality combining SQL, streaming, and complex analytics brings up this popularity.  
+In the end of last year, the book [_Mastering Spark with R_](https://therinspark.com/) was realesed and as a R user I got engaged to understand more about sparklyr package environment and the union of Spark and R.  With this in mind I will write a series of posts summarizing the learning and topics covered in the book.  
+![Mastering Spark with R](gallery/therinspark.jpg =150x100)  
+To understand more about how Spark became reference in the big data scenario it's good to see the history behind.
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