I have below example
val df_temp1 = Seq(
("1","Adam","Angra", "Anastasia")
).toDF("id","fname", "mname", "lname")
df_temp1.createOrReplaceTempView("df_temp1")
val df1 = spark.sql("""select id,named_struct('opi1',array(named_struct('data_description','fname','data_details',fname),named_struct('data_description','mname','data_details',mname),named_struct('data_description','lname','data_details',lname))) as pi, array(named_struct('data_description','fname','data_details',fname),named_struct('data_description','mname','data_details',mname), named_struct('data_description','lname','data_details',lname)) as opi2 from df_temp1""")
df1.printSchema
df1.show(false)
df1.createOrReplaceTempView("df1")
That gives below output schema
root
|-- id: string (nullable = true)
|-- pi: struct (nullable = false)
| |-- opi1: array (nullable = false)
| | |-- element: struct (containsNull = false)
| | | |-- data_description: string (nullable = false)
| | | |-- data_details: string (nullable = true)
|-- opi2: array (nullable = false)
| |-- element: struct (containsNull = false)
| | |-- data_description: string (nullable = false)
| | |-- data_details: string (nullable = true)
And below result
--- ----------------------------------------------------- ---------------------------------------------------
|id |pi |opi2 |
--- ----------------------------------------------------- ---------------------------------------------------
|1 |{[{fname, Adam}, {mname, Angra}, {lname, Anastasia}]}|[{fname, Adam}, {mname, Angra}, {lname, Anastasia}]|
--- ----------------------------------------------------- ---------------------------------------------------
I want opi2 to be included along with opi1 in pi, So expected schema should look like this
root
|-- id: string (nullable = true)
|-- pi: struct (nullable = false)
| |-- opi1: array (nullable = false)
| | |-- element: struct (containsNull = false)
| | | |-- data_description: string (nullable = false)
| | | |-- data_details: string (nullable = true)
|----|-- opi2: array (nullable = false)
| | |-- element: struct (containsNull = false)
| | |-- |--data_description: string (nullable = false)
| | |---- |--data_details: string (nullable = true)
And Expected Output will be two arrays opi1 and opi2 inside pi like below
--- ----------------------------------------------------- ---------------------------------------------------
|id |pi |
--- ----------------------------------------------------- ---------------------------------------------------
|1 |{[{fname, Adam}, {mname, Angra}, {lname, Anastasia}],[{fname, Adam}, {mname, Angra}, {lname, Anastasia}]}|
--- ----------------------------------------------------- ---------------------------------------------------
So basically adding existing column to struct (I am using Spark 2.3 by the way so any functions from Spark 2.4 cannot be used)
CodePudding user response:
Just create a new struct from pi.opi1
and opi2
val df2 = spark.sql("select id, named_struct('opi1',pi.opi1, 'opi2', opi2) as pi from df1")
df2.show(false)
df2.printSchema
--- ----------------------------------------------------------------------------------------------------------
|id |pi |
--- ----------------------------------------------------------------------------------------------------------
|1 |{[{fname, Adam}, {mname, Angra}, {lname, Anastasia}], [{fname, Adam}, {mname, Angra}, {lname, Anastasia}]}|
--- ----------------------------------------------------------------------------------------------------------
root
|-- id: string (nullable = true)
|-- pi: struct (nullable = false)
| |-- opi1: array (nullable = false)
| | |-- element: struct (containsNull = false)
| | | |-- data_description: string (nullable = false)
| | | |-- data_details: string (nullable = true)
| |-- opi2: array (nullable = false)
| | |-- element: struct (containsNull = false)
| | | |-- data_description: string (nullable = false)
| | | |-- data_details: string (nullable = true)