Introduction to DataFrames with Example for beginners

Updated:05/20/2021 by Computer Hope

A Dataset is a distributed collection of data. Dataset is a new interface added in Spark 1.6 that provides the benefits of RDDs (strong typing, ability to use powerful lambda functions) with the benefits of Spark SQL’s optimized execution engine. A Dataset can be constructed from JVM objects and then manipulated using functional transformations (map, flatMap, filter, etc.). The Dataset API is available in Scala and Java. Python does not have the support for the Dataset API. But due to Python’s dynamic nature, many of the benefits of the Dataset API are already available (i.e. you can access the field of a row by name naturally row.columnName). The case for R is similar.
A DataFrame is a distributed collection of data, which is organized into named columns. Conceptually, it is equivalent to relational tables with good optimization techniques

DataFrames with Example

import org.apache.spark.SparkContext._
import org.apache.spark._
val df ="examples/src/main/resources/people.json")
df.printSchema()"name").show()$"name", $"age" + 1).show()
df.filter($"age" > 21).show()

Below is screenshot of DataFrames with Example

Introduction to DataFrames with Example for beginners

spark dataframe example