How to find the size or shape of a DataFrame in PySpark?

I am trying to find out the size/shape of a DataFrame in PySpark. I do not see a single function that can do this.

In Python, I can do this:

data.shape() 

Is there a similar function in PySpark? This is my current solution, but I am looking for an element one

row_number = data.count() column_number = len(data.dtypes) 

The computation of the number of columns is not ideal...

6 Answers

You can get its shape with:

print((df.count(), len(df.columns))) 

Use df.count() to get the number of rows.

Add this to the your code:

import pyspark def spark_shape(self): return (self.count(), len(self.columns)) pyspark.sql.dataframe.DataFrame.shape = spark_shape 

Then you can do

>>> df.shape() (10000, 10) 

But just remind you that .count() can be very slow for very large table that has not been persisted.

print((df.count(), len(df.columns))) 

is easier for smaller datasets.

However if the dataset is huge, an alternative approach would be to use pandas and arrows to convert the dataframe to pandas df and call shape

spark.conf.set("spark.sql.execution.arrow.enabled", "true") spark.conf.set("spark.sql.crossJoin.enabled", "true") print(df.toPandas().shape) 

I think there is not similar function like data.shape in Spark. But I will use len(data.columns) rather than len(data.dtypes)

I have solved this problem using this code block. Please try it, it works.

import pyspark def sparkShape(dataFrame): return (dataFrame.count(), len(dataFrame.columns)) pyspark.sql.dataframe.DataFrame.shape = sparkShape print(<Input the Dataframe name which you want the output of>.shape())