Spark: Avoid attempt to parsing partition path into different types i…

…f type inference is disabled

spark/src/main/scala/org/apache/spark/sql/delta/util/PartitionUtils.scala

@@ -528,46 +528,46 @@ private[delta] object PartitionUtils {
  timeZone: TimeZone,
  dateFormatter: DateFormatter,
  timestampFormatter: TimestampFormatter): Literal = {
- val decimalTry = Try {
- // `BigDecimal` conversion can fail when the `field` is not a form of number.
- val bigDecimal = new JBigDecimal(raw)
- // It reduces the cases for decimals by disallowing values having scale (eg. `1.1`).
- require(bigDecimal.scale <= 0)
- // `DecimalType` conversion can fail when
- // 1. The precision is bigger than 38.
- // 2. scale is bigger than precision.
- Literal(bigDecimal)
- }
+ if (typeInference) {
+ val decimalTry = Try {
+ // `BigDecimal` conversion can fail when the `field` is not a form of number.
+ val bigDecimal = new JBigDecimal(raw)
+ // It reduces the cases for decimals by disallowing values having scale (eg. `1.1`).
+ require(bigDecimal.scale <= 0)
+ // `DecimalType` conversion can fail when
+ // 1. The precision is bigger than 38.
+ // 2. scale is bigger than precision.
+ Literal(bigDecimal)
+ }
 
- val dateTry = Try {
- // try and parse the date, if no exception occurs this is a candidate to be resolved as
- // DateType
- dateFormatter.parse(raw)
- // SPARK-23436: Casting the string to date may still return null if a bad Date is provided.
- // This can happen since DateFormat.parse may not use the entire text of the given string:
- // so if there are extra-characters after the date, it returns correctly.
- // We need to check that we can cast the raw string since we later can use Cast to get
- // the partition values with the right DataType (see
- // org.apache.spark.sql.execution.datasources.PartitioningAwareFileIndex.inferPartitioning)
- val dateValue = Cast(Literal(raw), DateType).eval()
- // Disallow DateType if the cast returned null
- require(dateValue != null)
- Literal.create(dateValue, DateType)
- }
+  val dateTry = Try {
+  // try and parse the date, if no exception occurs this is a candidate to be resolved as
+  // DateType
+  dateFormatter.parse(raw)
+  // SPARK-23436: Casting the string to date may still return null if a bad Date is provided.
+  // This can happen since DateFormat.parse may not use the entire text of the given string:
+  // so if there are extra-characters after the date, it returns correctly.
+  // We need to check that we can cast the raw string since we later can use Cast to get
+  // the partition values with the right DataType (see
+  // org.apache.spark.sql.execution.datasources.PartitioningAwareFileIndex.inferPartitioning)
+  val dateValue = Cast(Literal(raw), DateType).eval()
+  // Disallow DateType if the cast returned null
+  require(dateValue != null)
+  Literal.create(dateValue, DateType)
+  }
 
- val timestampTry = Try {
- val unescapedRaw = unescapePathName(raw)
- // try and parse the date, if no exception occurs this is a candidate to be resolved as
- // TimestampType
- timestampFormatter.parse(unescapedRaw)
- // SPARK-23436: see comment for date
- val timestampValue = Cast(Literal(unescapedRaw), TimestampType, Some(timeZone.getID)).eval()
- // Disallow TimestampType if the cast returned null
- require(timestampValue != null)
- Literal.create(timestampValue, TimestampType)
- }
+  val timestampTry = Try {
+  val unescapedRaw = unescapePathName(raw)
+  // try and parse the date, if no exception occurs this is a candidate to be resolved as
+  // TimestampType
+  timestampFormatter.parse(unescapedRaw)
+  // SPARK-23436: see comment for date
+  val timestampValue = Cast(Literal(unescapedRaw), TimestampType, Some(timeZone.getID)).eval()
+  // Disallow TimestampType if the cast returned null
+  require(timestampValue != null)
+  Literal.create(timestampValue, TimestampType)
+  }
 
- if (typeInference) {
  // First tries integral types
  Try(Literal.create(Integer.parseInt(raw), IntegerType))
  .orElse(Try(Literal.create(JLong.parseLong(raw), LongType)))