Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/12030#discussion_r58302585
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/InferSchema.scala
---
@@ -135,11 +135,25 @@ private[sql] object InferSchema {
// when we see a Java BigInteger, we use DecimalType.
case BIG_INTEGER | BIG_DECIMAL =>
val v = parser.getDecimalValue
- DecimalType(v.precision(), v.scale())
+ try {
+ // Creating `DecimalType` here can fail when precision is
bigger than 38.
+ DecimalType(v.precision(), v.scale())
--- End diff --
It's reasonable to have a decimal "0.01", so we should use max of precision
and scale as precision here. Also it's better to not reply on exception for
branch.
if (Math.max(v.precision(), v.scale()) <= DecimalType.MAX_MAX_PRECISION) {
DecimalType(Math.max(v.precision(), v.scale()), v.scale())
} else {
DoubleType
}
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