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I want to define a column with null values in my dataframe using pyspark. This column will later be used for other calculations.What is the difference between creating it in these two different ways?df.withColumn("New_Column", lit(None))df.withColumn...
For me df.withColumn("New_Column", lit(None).cast(StringType())) this didn't work.I used this instead df.withColumn("New_Column", lit(null).cast(StringType))
Understanding Rename in DatabricksNow there are multiple ways to rename Spark Data Frame Columns or Expressions.We can rename columns or expressions using alias as part of selectWe can add or rename columns or expressions using withColumn on top of t...
Hi,Currently, I'm using structure streaming to insert/update/delete to a table. A row will be deleted if value in 'Operation' column is 'deleted'. Everything seems to work fine until there's a new column.Since I don't need 'Operation' column in the t...
Hi AllI am loading some data using auto loader but am having trouble with Schema evolution.A new column has been added to the data I am loading and I am getting the following error:StreamingQueryException: Encountered unknown field(s) during parsing:...
I agree that hints are the way to go if you have the schema available but the whole point of schema evolution is that you might not always know the schema in advance.I received a similar error with a similar streaming query configuration. The issue w...
Hello,My table has primary key constraint on a perticular column, Im loosing primary key constaint on that column each time I overwrite the table , What Can I do to preserve it? Any Heads up would be appreciatedTried Belowdf.write.option("truncate", ...
@Abeeya . , Mode "truncate", is correct to preserve the table. However, when you want to add a new column (mismatched schema), it wants to drop it anyway.
Hi @ahana ahana ,Did any of the replies helped you solve this issue? would you be happy to mark their answer as best so that others can quickly find the solution?Thank you
1. I have data x,I would like to create a new column with the condition that the value are 1, 2 or 32. The name of the column is SHIFT where this SHIFT column will be filled automatically if the TIME_CREATED column meets the conditions.3. the conditi...
You an do something like this in pandas. Note there could be a more performant way to do this too. import pandas as pd
import numpy as np
df = pd.DataFrame({'a':[1,2,3,4]})
df.head()
> a
> 0 1
> 1 2
> 2 3
> 3 4
conditions = [(df['a'] <=2...
