使用spark xml读取值xml标记值，想要获取值但是给我列表

<c2>KH0013001</c2>
<c3>-2271164.00</c3>
<c4>9</c4>
<c7>65395</c7>
<c9>1</c9>
<c12>KHR</c12>
<c16>TR</c16>
<c17>6-71-10-1-001-030</c17>
<c20>1</c20>
<c22>1</c22>
<c23>DC183050001030071</c23>
<c24>DC</c24>
<c25>20181101</c25>
<c26>185685445477437.02</c26>
<c26 m='3'>1</c26>
<c29>1</c29>
<c30>5011_DMUSER__OFS_DM.OFS.SRC.VAL</c30>
<c31>1811012130</c31>
<c32>6010_DMUSER</c32>
<c56>PL.65395.......1.....KH0013001</c56>
<c98></c98>

SPARK与SPARK XML

import org.apache.spark.sql.{SQLContext, SparkSession}

object sparkXml {
def main(args: Array[String]): Unit = {

val spark = SparkSession.
  builder.master("local[*]")
  //.config("spark.debug.maxToStringFields", "100")
  .appName("Insight Application Big Data")
  .getOrCreate()

val df = spark.read
  .format("com.databricks.spark.xml")
  .option("rowTag", "row")
  .load("src/main/resources/in/FBNK_CATEG_ENTRY.xml")
df.createOrReplaceTempView("categ_entry")

df.printSchema()
spark.sql("Select c26['_VALUE'] as value, c26['_m'] as option from categ_entry").show()

}
}
printSchema

root
|-- _id: double (nullable = true)
|-- _space: string (nullable = true)
|-- c12: string (nullable = true)
|-- c16: string (nullable = true)
|-- c17: string (nullable = true)
|-- c2: string (nullable = true)
|-- c20: long (nullable = true)
|-- c22: long (nullable = true)
|-- c23: string (nullable = true)
|-- c24: string (nullable = true)
|-- c25: long (nullable = true)
|-- c26: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- _VALUE: double (nullable = true)
| | |-- _m: long (nullable = true)
|-- c29: long (nullable = true)
|-- c3: double (nullable = true)
|-- c30: string (nullable = true)
|-- c31: long (nullable = true)
|-- c32: string (nullable = true)
|-- c4: long (nullable = true)
|-- c56: string (nullable = true)
|-- c7: long (nullable = true)
|-- c9: long (nullable = true)
|-- c98: string (nullable = true)
运行后的结果

我期望结果是这样的。