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Writing an UDF for withColumn in PySpark
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| from pyspark.sql.types import StringType | |
| from pyspark.sql.functions import udf | |
| maturity_udf = udf(lambda age: "adult" if age >=18 else "child", StringType()) | |
| df = sqlContext.createDataFrame([{'name': 'Alice', 'age': 1}]) | |
| df.withColumn("maturity", maturity_udf(df.age)) |
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