Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/12708#discussion_r61822276
--- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala ---
@@ -335,6 +358,19 @@ trait Row extends Serializable {
def getAs[T](fieldName: String): T = getAs[T](fieldIndex(fieldName))
/**
+ * Returns the value of a given fieldName as a scala.util.Try object.
+ */
+ def attempt[T](fieldName: String): Try[T] =
Try(getAs[T](fieldIndex(fieldName)))
--- End diff --
There are two types of row (external) `org.apache.spark.sql.Row` and
`org.apache.spark.sql.catalyst.InternalRow`. In general, I don't think that
users consume Row objects that they constructed. Instead I think they
construct rows to pass in to Spark or they consume rows produced by Spark.
Given that, I think this is a more realistic use case:
```scala
import org.apache.spark.sql.types._
val rows = sc.parallelize(Row.fromSeq("string" :: Nil) :: Nil)
val schema = StructType(StructField("id", IntegerType) :: Nil)
val df = sqlContext.createDataFrame(rows, schema)
df.collect()
```
This is going to fail before Spark returns the invalid row to you:
```
java.lang.ClassCastException: java.lang.String cannot be cast to
java.lang.Integer
at scala.runtime.BoxesRunTime.unboxToInt(BoxesRunTime.java:106)
at
org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow$class.getInt(rows.scala:41)
at
org.apache.spark.sql.catalyst.expressions.GenericInternalRow.getInt(rows.scala:221)
at
org.apache.spark.sql.catalyst.CatalystTypeConverters$IntConverter$.toScalaImpl(CatalystTypeConverters.scala:363)
at
org.apache.spark.sql.catalyst.CatalystTypeConverters$IntConverter$.toScalaImpl(CatalystTypeConverters.scala:362)
at
org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toScala(CatalystTypeConverters.scala:110)
```
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