Github user manishgupta88 commented on a diff in the pull request:
https://github.com/apache/carbondata/pull/1023#discussion_r121863383
--- Diff:
integration/spark-common/src/main/scala/org/apache/carbondata/spark/util/CommonUtil.scala
---
@@ -179,6 +193,68 @@ object CommonUtil {
isValid
}
+ def validateTypeConvert(desType: Option[String], value: String): Boolean
= {
+ var flag = true
+ val result = desType match {
+ case Some("IntegerType") =>
+ DataTypeUtil.getDataBasedOnDataType(value.trim, DataType.INT)
+ case Some("StringType") =>
+ DataTypeUtil.getDataBasedOnDataType(value.trim, DataType.STRING)
--- End diff --
Please correct me if I am wrong....While validating the values you are
trimming the values but in the actual range info can still contain the spaces
as the object is not getting refilled with the trimmed values and therefore can
lead to an inconsistent state. For e.g I have Int type column with rangeInfo =
1, 2 , 3,4...while parsing it will pass as trim function is used but original
object still will have the same values...
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