Replacing whitespace in all column names in spark

问题:

I have spark dataframe with whitespaces in some of column names, which has to be replaced with underscore.

I know a single column can be renamed using withColumnRenamed() in sparkSQL, but to rename 'n' number of columns, this function has to chained 'n' times (to my knowledge).

To automate this, i have tried:

val old_names = df.columns()        // contains array of old column names

val new_names = old_names.map { x => 
   if(x.contains(" ") == true) 
      x.replaceAll("\\s","_") 
   else x 
}                    // array of new column names with removed whitespace.

Now, how to replace df's header with new_names

回答1:

  var newDf = df
  for(col <- df.columns){
    newDf = newDf.withColumnRenamed(col,col.replaceAll("\\s", "_"))
  }

You can encapsulate it in some method so it won't be too much pollution.

回答2:

In Python, this can be done by the following code:

# Importing sql types
from pyspark.sql.types import StringType, StructType, StructField
from pyspark.sql.functions import col

# Building a simple dataframe:
schema = StructType([
             StructField("id name", StringType(), True),
             StructField("cities venezuela", StringType(), True)
         ])

column1 = ['A', 'A', 'B', 'B', 'C', 'B']
column2 = ['Maracaibo', 'Valencia', 'Caracas', 'Barcelona', 'Barquisimeto', 'Merida']

# Dataframe:
df = sqlContext.createDataFrame(list(zip(column1, column2)), schema=schema)
df.show()

exprs = [col(column).alias(column.replace(' ', '_')) for column in df.columns]
df.select(*exprs).show()

回答3:

As best practice, you should prefer expressions and immutability. You should use val and not var as much as possible.

Thus, it's preferable to use the foldLeft operator, in this case :

val newDf = df.columns
              .foldLeft(df)((curr, n) => curr.withColumnRenamed(n, n.replaceAll("\\s", "_")))

回答4:

You can do the exact same thing in python:

raw_data1 = raw_data
for col in raw_data.columns:
  raw_data1 = raw_data1.withColumnRenamed(col,col.replace(" ", "_"))

回答5:

In Scala, here is another way achieving same -

    import org.apache.spark.sql.types._

    val df_with_newColumns = spark.createDataFrame(df.rdd, 
StructType(df.schema.map(s => StructField(s.name.replaceAll(" ", ""), 
s.dataType, s.nullable))))

Hope this helps !!