close

[Solved] pyspark: ValueError: Some of types cannot be determined after inferring

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error pyspark: ValueError: Some of types cannot be determined after inferring in python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How pyspark: ValueError: Some of types cannot be determined after inferring Error Occurs?

Today I get the following error pyspark: ValueError: Some of types cannot be determined after inferring in python.

How To Solve pyspark: ValueError: Some of types cannot be determined after inferring Error ?

  1. How To Solve pyspark: ValueError: Some of types cannot be determined after inferring Error ?

    To Solve pyspark: ValueError: Some of types cannot be determined after inferring Error In order to infer the field type, PySpark looks at the non-none records in each field. If a field only has None records, PySpark can not infer the type and will raise that error.

  2. pyspark: ValueError: Some of types cannot be determined after inferring

    To Solve pyspark: ValueError: Some of types cannot be determined after inferring Error In order to infer the field type, PySpark looks at the non-none records in each field. If a field only has None records, PySpark can not infer the type and will raise that error.

Solution 1

In order to infer the field type, PySpark looks at the non-none records in each field. If a field only has None records, PySpark can not infer the type and will raise that error.

Manually defining a schema will resolve the issue

>>> from pyspark.sql.types import StructType, StructField, StringType
>>> schema = StructType([StructField("foo", StringType(), True)])
>>> df = spark.createDataFrame([[None]], schema=schema)
>>> df.show()
+----+
|foo |
+----+
|null|
+----+

Solution 2

If you are using the RDD[Row].toDF() monkey-patched method you can increase the sample ratio to check more than 100 records when inferring types:

# Set sampleRatio smaller as the data size increases
my_df = my_rdd.toDF(sampleRatio=0.01)
my_df.show()

Assuming there are non-null rows in all fields in your RDD, it will be more likely to find them when you increase the sampleRatio towards 1.0.

Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

Also, Read