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date: Sat, 11 Oct 2025 12:28:38 GMT
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from pyspark.sql.types import *import pyspark.sql.functions as Fschema = S - Pastebin.com
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- FROM pyspark.sql.types import *
- import pyspark.sql.functions AS F
- schema = StructType([
- StructField('name', StringType(), nullable=FALSE),
- StructField("business", ArrayType(StringType())),
- StructField('total', IntegerType(), nullable=FALSE)
- ])
- test_list = ['a',['Hello', 'world'],200], ['a',['I', 'am', 'fine'],300],['b',[],500]
- df = spark.createDataFrame(test_list,schema=schema)
- df1=df.groupBy('name','business').agg(F.when(F.size('business')>1,F.SUM('total')/F.size('business')).otherwise(F.SUM('total')).alias('total'))
- df1 = df1.withColumn('business',F.explode_outer('business'))
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