In PySpark, toDF() function of the RDD is used to convert RDD to DataFrame. We would need to convert RDD to DataFrame as DataFrame provides more advantages over RDD. For instance, DataFrame is a distributed collection of data organized into named columns similar to Database tables and provides optimization and…
You can manually create a PySpark DataFrame using toDF() and createDataFrame() methods, both these function takes different signatures in order to create DataFrame from existing RDD, list, and DataFrame. You can also create PySpark DataFrame from data sources like TXT, CSV, JSON, ORV, Avro, Parquet, XML formats by reading from…
While working in Apache Spark with Scala, we often need to Convert Spark RDD to DataFrame and Dataset as these provide more advantages over RDD. For instance, DataFrame is a distributed collection of data organized into named columns similar to Database tables and provides optimization and performance improvement. In this…
In Spark, createDataFrame() and toDF() methods are used to create a DataFrame manually, using these methods you can create a Spark DataFrame from already existing RDD, DataFrame, Dataset, List, Seq data objects, here I will examplain these with Scala examples. You can also create a DataFrame from different sources like…