August 2016
Beginner to intermediate
334 pages
8h 27m
English
So far we've mainly focused on datasets that can fit on a single machine. For larger datasets, we may need to access them through distributed file systems such as Amazon S3 or HDFS. For this purpose, we can utilize the open-source distributed computing framework PySpark (http://spark.apache.org/docs/latest/api/python/). PySpark is a distributed computing framework that uses the abstraction of Resilient Distributed Datasets (RDDs) for parallel collections of objects, which allows us to programmatically access a dataset as if it fits on a single machine. In later chapters we will demonstrate how to build predictive models in PySpark, but for this introduction we focus on data manipulation functions in PySpark.
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