PySpark’s toDF() function is used to convert RDD to DataFrame, which is necessary because DataFrame offers numerous advantages over RDDs. For example, DataFrames are distributed data collections organized into named columns similar to database tables, and they offer optimization and performance improvements. To begin with, we can create a PySpark RDD by passing a Python …
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This article aims to provide instructions on creating an empty PySpark DataFrame or RDD, either with or without a defined schema (column names), using various methods. Additionally, the article explores a common scenario where it is necessary to create an empty DataFrame. In some cases, while working with files, there may be instances where no …
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Most of the time, while cleaning the data, you have to make some choices based on the usability of the data. If a dataset that you are working on contains null values, you need to decide the most feasible way of doing it. Undoubtedly, you can either replace null values with some alternative or completely …
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Why replace null values in PySpark DataFrame? In huge datasets, there can be thousands of rows and hundreds of columns. Out of these columns, there may exist some containing null values or None in more than one cell. Null values in pyspark are nothing but no values in certain rows of String or Integer datatype …
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