I have XML file like below format.
<nt:vars>
<nt:var id="1.3.0" type="TimeStamp"> 89:19:00.01</nt:var>
<nt:var id="1.3.1" type="OBJECT ">1.9.5.67.2</nt:var>
<nt:var id="1.3.9" type="STRING">AB-CD-EF</nt:var>
</nt:vars>
I built a dataframe on it using below code. Though the code is displaying 3 rows and retrieving id and type fields it'snot displaying actual value which is 89:19:00.01, 1.9.5.67.2, AB-CD-EF
spark.read.format("xml").option("rootTag","nt:vars").option("rowTag","nt:var").load("/FileStore/tables/POC_DB.xml").show()
Could you please help me if I have to add any other options to above line to bring the values as well please.
You can instead specify rowTag as nt:vars:
df = spark.read.format("xml").option("rowTag","nt:vars").load("file.xml")
df.printSchema()
root
|-- nt:var: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- _VALUE: string (nullable = true)
| | |-- _id: string (nullable = true)
| | |-- _type: string (nullable = true)
df.show(truncate=False)
+-------------------------------------------------------------------------------------------+
|nt:var |
+-------------------------------------------------------------------------------------------+
|[[ 89:19:00.01, 1.3.0, TimeStamp], [1.9.5.67.2, 1.3.1, OBJECT ], [AB-CD-EF, 1.3.9, STRING]]|
+-------------------------------------------------------------------------------------------+
And to get the values as separate rows, you can explode the array of structs:
df.select(F.explode('nt:var')).show(truncate=False)
+--------------------------------+
|col |
+--------------------------------+
|[ 89:19:00.01, 1.3.0, TimeStamp]|
|[1.9.5.67.2, 1.3.1, OBJECT ] |
|[AB-CD-EF, 1.3.9, STRING] |
+--------------------------------+
Or if you just want the values:
df.select(F.explode('nt:var._VALUE')).show()
+------------+
| col|
+------------+
| 89:19:00.01|
| 1.9.5.67.2|
| AB-CD-EF|
+------------+