How to apply a function to a column in PySpark? By using withColumn(), sql(), select() you can apply a built-in function or custom function to a column. In order to…

PySpark max() function is used to get the maximum value of a column or get the maximum value for each group. PySpark has several max() functions, depending on the use…

PySpark sum() is an aggregate function that returns the SUM of selected columns, This function should be used on a numeric column. The sum of a column is also referred…

The pyspark.sql.DataFrame.unionByName() to merge/union two DataFrames with column names. In PySpark you can easily achieve this using unionByName() transformation, this function also takes param allowMissingColumns with the value True if…

The PySpark between(lowerBound,upperBound) is used to get the rows between two values. The Columns.between() returns either True or False (boolean expression), it is evaluated to true if the value of…

The pyspark.sql.DataFrame.toDF() function is used to create the DataFrame with the specified column names it create DataFrame from RDD. Since RDD is schema-less without column names and data type, converting…

PySpark persist is a way of caching the intermediate results in specified storage levels so that any operations on persisted results would improve the performance in terms of memory usage…

Broadcast join is an optimization technique in the PySpark SQL engine that is used to join two DataFrames. This technique is ideal for joining a large DataFrame with a smaller…

The pyspark.sql.functions.lag() is a window function that returns the value that is offset rows before the current row, and defaults if there are less than offset rows before the current row. This is equivalent to the…