In Databricks, “0E-8” represents the decimal value 0.00000000 (zero with eight decimal places). It’s a form of scientific notation, often used to express very small or very large numbers concisely.

Why You Might See “0E-8” in Databricks:

1. Casting: When casting a value (often 0) to a decimal type with many decimal places, it might be displayed as “0E-8.” For example, in PySpark:

   Python

   from pyspark.sql.types import DecimalType
   df = spark.createDataFrame([(0,)], ["col"])
   df = df.withColumn("col", df["col"].cast(DecimalType(10, 8)))  
   df.show()  # Output: +--------+
               #         |     col|
               #         +--------+
               #         |0E-8   |
               #         +--------+
   

    

    

2. Reading from External Sources: Some data formats might store decimal values like 0.00000000 as “0E-8”.

3. Calculations: Intermediate results in calculations might be displayed in this format, even if the final result isn’t.

How to Handle “0E-8”:

1. Formatting: Use formatting functions to display the value as “0.00000000” instead of “0E-8.” In PySpark, you can use format_number() or round():

   Python

   from pyspark.sql.functions import format_number
   
   df = df.withColumn("col_formatted", format_number("col", 8))
   df.show()  # Output: +--------+-------------+
               #         |     col|col_formatted|
               #         +--------+-------------+
               #         |0E-8   |   0.00000000|
               #         +--------+-------------+
   

    

    

2. Casting: Be mindful when casting values to decimal types, considering the desired number of decimal places.

3. Data Cleaning: If reading from external data, check how decimal values are stored and convert them if necessary.

Additional Considerations:

• “0E-8” and 0.00000000 are mathematically equivalent.
• Depending on your use case, you might not need to change “0E-8” at all.