TypeError: 'Column' object is not callable using WithColumn

Question

I would like append a new column on dataframe \"df\" from function get_distance:

def get_distance(x, y):
         


        

Answer 1

Spark should know the function that you are using is not ordinary function but the UDF.

So, there are 2 ways by which we can use the UDF on dataframes.

Method-1: With @udf annotation

@udf
def get_distance(x, y):
    dfDistPerc = hiveContext.sql("select column3 as column3, \
                                  from tab \
                                  where column1 = '" + x + "' \
                                  and column2 = " + y + " \
                                  limit 1")

    result = dfDistPerc.select("column3").take(1)
    return result

df = df.withColumn(
    "distance",
    lit(get_distance(df["column1"], df["column2"]))
)

Method-2: Regestering udf with pyspark.sql.functions.udf

def get_distance(x, y):
    dfDistPerc = hiveContext.sql("select column3 as column3, \
                                  from tab \
                                  where column1 = '" + x + "' \
                                  and column2 = " + y + " \
                                  limit 1")

    result = dfDistPerc.select("column3").take(1)
    return result

calculate_distance_udf = udf(get_distance, IntegerType())

df = df.withColumn(
    "distance",
    lit(calculate_distance_udf(df["column1"], df["column2"]))
)