如果字符串在 PySpark 中包含某些 substring，则替换字符串

Question

Need to update a PySpark dataframe if the column contains the certain substring

for example:

df looks like

id      address
1       spring-field_garden
2       spring-field_lane
3       new_berry place

If the address column contains spring-field_ just replace it with spring-field .

Expected result:

id      address
1       spring-field
2       spring-field
3       new_berry place

Tried:

df = df.withColumn('address',F.regexp_replace(F.col('address'), 'spring-field_*', 'spring-field'))

Seems not working.

Answer 1

You can use like with when expression:

from pyspark.sql import functions as F

df = df.withColumn(
    'address',
    F.when(
        F.col('address').like('%spring-field_%'),
        F.lit('spring-field')
    ).otherwise(F.col('address'))
)

Answer 2

You can use the following regex:

df.withColumn(
    'address',
    F.regexp_replace('address', r'.*spring-field.*', 'spring-field')
)

Alternatively you can use the method contains :

df.withColumn(
    'address',
    F.when(
        F.col('address').contains("spring-field"), "spring-field"
    ).otherwise(F.col('address'))
)