Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/11724#discussion_r56444849
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala
---
@@ -108,14 +109,38 @@ private[csv] object CSVInferSchema {
}
private def tryParseDouble(field: String): DataType = {
- if ((allCatch opt field.toDouble).isDefined) {
+ val doubleTry = allCatch opt field.toDouble
--- End diff --
Ah.. numeric types with fractions can be also `Decimal`. It has precision
and scale.
```scala
import java.math.BigDecimal
scala> BigDecimal.valueOf(1.1111)
res4: java.math.BigDecimal = 1.1111
scala> BigDecimal.valueOf(1.1111).precision
res6: Int = 5
scala> BigDecimal.valueOf(1.1111).scale
res7: Int = 4
```
```scala
import java.math.BigDecimal
scala> BigDecimal.valueOf(1)
res5: java.math.BigDecimal = 1
scala> BigDecimal.valueOf(1).precision
res8: Int = 1
scala> BigDecimal.valueOf(1).scale
res9: Int = 0
```
`DoubleType` with fractions can lose precision if it has too many.
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