MaxGekk commented on code in PR #39872:
URL: https://github.com/apache/spark/pull/39872#discussion_r1096762646
##########
core/src/main/resources/error/error-classes.json:
##########
@@ -511,6 +511,12 @@
],
"sqlState" : "38000"
},
+ "FAILED_PARSE_EMPTY_STRING" : {
Review Comment:
This error class is pretty JSON specific. So, add JSON in the name. For
example:
```suggestion
"EMPTY_JSON_FIELD_VALUE" : {
```
##########
core/src/main/resources/error/error-classes.json:
##########
@@ -511,6 +511,12 @@
],
"sqlState" : "38000"
},
+ "FAILED_PARSE_EMPTY_STRING" : {
+ "message" : [
+ "Failed to parse an empty string for data type <dataType>."
Review Comment:
Please, tell about the SQL config
`spark.sql.legacy.json.allowEmptyString.enabled` to users in the error message.
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala:
##########
@@ -2608,11 +2609,12 @@ abstract class JsonSuite
private def failedOnEmptyString(dataType: DataType): Unit = {
val df = spark.read.schema(s"a ${dataType.catalogString}")
.option("mode", "FAILFAST").json(Seq("""{"a":""}""").toDS)
- val errMessage = intercept[SparkException] {
- df.collect()
- }.getMessage
- assert(errMessage.contains(
- s"Failed to parse an empty string for data type
${dataType.catalogString}"))
+ val e = intercept[SparkException] {df.collect()}
+ checkError(
+ exception =
e.getCause.getCause.getCause.asInstanceOf[SparkRuntimeException],
+ errorClass = "FAILED_PARSE_EMPTY_STRING",
+ parameters = Map("dataType" -> s"${toSQLType(dataType)}")
Review Comment:
nit:
```suggestion
parameters = Map("dataType" -> toSQLType(dataType))
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/errors/QueryExecutionErrors.scala:
##########
@@ -1433,9 +1433,9 @@ private[sql] object QueryExecutionErrors extends
QueryErrorsBase {
def failToParseEmptyStringForDataTypeError(dataType: DataType):
SparkRuntimeException = {
new SparkRuntimeException(
- errorClass = "_LEGACY_ERROR_TEMP_2135",
+ errorClass = "FAILED_PARSE_EMPTY_STRING",
messageParameters = Map(
- "dataType" -> dataType.catalogString))
+ "dataType" -> toSQLType(dataType)))
Review Comment:
```scala
messageParameters = Map("dataType" -> toSQLType(dataType)))
```
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