I am trying a logic to return an empty column if column does not exist in dataframe.
Schema changes very frequent, sometime the whole struct will be missing (temp1) or array inside struct will be missing (suffix)
Schema looks like this:
root
|-- id: string (nullable = true)
|-- temp: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- temp1: struct (nullable = true)
| | | |-- code: string (nullable = true)
| | | |-- code1: array (nullable = true)
| | | | |-- element: string (containsNull = true)
| | |-- temp2: struct (nullable = true)
| | | |-- name1: array (nullable = true)
| | | | |-- element: string (containsNull = true)
| | | |-- suffix: array (nullable = true)
| | | | |-- element: string (containsNull = true)
|-- timestamp: timestamp (nullable = true)
Or like this:
root
|-- id: string (nullable = true)
|-- temp: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- temp2: struct (nullable = true)
| | | |-- name1: array (nullable = true)
| | | | |-- element: string (containsNull = true)
|-- timestamp: timestamp (nullable = true)
When I am trying the below logic for the second schema, getting an exception that Struct not found
def has_Column(df: DataFrame, path: String) = Try(df(path)).isSuccess
df.withColumn("id", col("id")).
withColumn("tempLn", explode(col("temp"))).
withColumn("temp1_code1", when(lit(has_Column(df, "tempLn.temp1.code1")), concat_ws(" ",col("tempLn.temp1.code1"))).otherwise(lit("").cast("string"))).
withColumn("temp2_suffix", when(lit(has_Column(df, "tempLn.temp2.suffix")), concat_ws(" ",col("tempLn.temp2.suffix"))).otherwise(lit("").cast("string")))
Error:
org.apache.spark.sql.AnalysisException: No such struct field temp1;