Filtering based on a float value with more than one decimal place not working correctly in Pyspark dataframe

[Meethu Mathew]

Hi all,

I tried the following code and the output was not as expected.

schema = StructType([StructField('Id', StringType(), False),
>                      StructField('Value', FloatType(), False)])
> df_test = spark.createDataFrame([('a',5.0),('b',1.236),('c',-0.31)],schema)

df_test


Output :  DataFrame[Id: string, Value: float]
[image: image.png]
But when the value is given as a string, it worked.

[image: image.png]
Again tried with a floating point number with one decimal place and it
worked.
[image: image.png]
And when the equals operation is changed to greater than or less than, its
working with more than one decimal place numbers
[image: image.png]
Is this a bug?

Regards,
Meethu Mathew