Peng-Lei commented on a change in pull request #34093:
URL: https://github.com/apache/spark/pull/34093#discussion_r730690648
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/errors/QueryExecutionErrors.scala
##########
@@ -435,131 +435,129 @@ object QueryExecutionErrors {
}
def createStreamingSourceNotSpecifySchemaError(): Throwable = {
- new IllegalArgumentException(
- s"""
- |Schema must be specified when creating a streaming source DataFrame.
If some
- |files already exist in the directory, then depending on the file
format you
- |may be able to create a static DataFrame on that directory with
- |'spark.read.load(directory)' and infer schema from it.
- """.stripMargin)
+ new SparkIllegalArgumentException(
+ errorClass = "MISSING_STREAMING_SOURCE_SCHEMA",
+ messageParameters = Array.empty)
}
def streamedOperatorUnsupportedByDataSourceError(
className: String, operator: String): Throwable = {
- new UnsupportedOperationException(
- s"Data source $className does not support streamed $operator")
+ new SparkUnsupportedOperationException(
+ errorClass = "UNSUPPORTED_STREAMED_OPERATOR_BY_DATA_SOURCE",
+ messageParameters = Array(className, operator))
}
def multiplePathsSpecifiedError(allPaths: Seq[String]): Throwable = {
- new IllegalArgumentException("Expected exactly one path to be specified,
but " +
- s"got: ${allPaths.mkString(", ")}")
+ new SparkIllegalArgumentException(
+ errorClass = "SPECIFIED_MULTIPLE_PATHS",
+ messageParameters = Array(allPaths.mkString(", ")))
}
def failedToFindDataSourceError(provider: String, error: Throwable):
Throwable = {
- new ClassNotFoundException(
- s"""
- |Failed to find data source: $provider. Please find packages at
- |http://spark.apache.org/third-party-projects.html
- """.stripMargin, error)
+ new SparkClassNotFoundException(
+ errorClass = "FAILED_FIND_DATA_SOURCE",
+ messageParameters = Array(provider), error)
}
def removedClassInSpark2Error(className: String, e: Throwable): Throwable = {
- new ClassNotFoundException(s"$className was removed in Spark 2.0. " +
- "Please check if your library is compatible with Spark 2.0", e)
+ new SparkClassNotFoundException(
+ errorClass = "CANNOT_FIND_CLASS_IN_SPARK2",
+ messageParameters = Array(className), e)
}
def incompatibleDataSourceRegisterError(e: Throwable): Throwable = {
- new SparkClassNotFoundException("INCOMPATIBLE_DATASOURCE_REGISTER",
Array(e.getMessage), e)
+ new SparkClassNotFoundException(
+ errorClass = "INCOMPATIBLE_DATASOURCE_REGISTER",
+ messageParameters = Array(e.getMessage), e)
}
def unrecognizedFileFormatError(format: String): Throwable = {
- new IllegalStateException(s"unrecognized format $format")
+ new SparkIllegalStateException(
+ errorClass = "UNRECOGNIZED_FORMAT",
+ messageParameters = Array(format))
}
def sparkUpgradeInReadingDatesError(
format: String, config: String, option: String): SparkUpgradeException =
{
- new SparkUpgradeException("3.0",
- s"""
- |reading dates before 1582-10-15 or timestamps before
1900-01-01T00:00:00Z from $format
- |files can be ambiguous, as the files may be written by Spark 2.x or
legacy versions of
- |Hive, which uses a legacy hybrid calendar that is different from
Spark 3.0+'s Proleptic
- |Gregorian calendar. See more details in SPARK-31404. You can set the
SQL config
- |'$config' or the datasource option '$option' to 'LEGACY' to rebase
the datetime values
- |w.r.t. the calendar difference during reading. To read the datetime
values as it is,
- |set the SQL config '$config' or the datasource option '$option' to
'CORRECTED'.
- """.stripMargin, null)
+ new SparkUpgradeException(
+ version = "3.0",
+ errorClass = "READING_AMBIGUOUS_DATES_AFTER_UPGRADE",
+ messageParameters = Array(format, config, option, config, option), null)
}
def sparkUpgradeInWritingDatesError(format: String, config: String):
SparkUpgradeException = {
- new SparkUpgradeException("3.0",
- s"""
- |writing dates before 1582-10-15 or timestamps before
1900-01-01T00:00:00Z into $format
- |files can be dangerous, as the files may be read by Spark 2.x or
legacy versions of Hive
- |later, which uses a legacy hybrid calendar that is different from
Spark 3.0+'s Proleptic
- |Gregorian calendar. See more details in SPARK-31404. You can set
$config to 'LEGACY' to
- |rebase the datetime values w.r.t. the calendar difference during
writing, to get maximum
- |interoperability. Or set $config to 'CORRECTED' to write the
datetime values as it is,
- |if you are 100% sure that the written files will only be read by
Spark 3.0+ or other
- |systems that use Proleptic Gregorian calendar.
- """.stripMargin, null)
+ new SparkUpgradeException(
+ version = "3.0",
+ errorClass = "WRITING_AMBIGUOUS_DATES_AFTER_UPGRADE",
+ messageParameters = Array(format, config, config), null)
}
def buildReaderUnsupportedForFileFormatError(format: String): Throwable = {
- new UnsupportedOperationException(s"buildReader is not supported for
$format")
+ new SparkUnsupportedOperationException(
+ errorClass = "UNSUPPORTED_BUILD_READER_FOR_FILE_FORMAT",
+ messageParameters = Array(format))
}
def jobAbortedError(cause: Throwable): Throwable = {
- new SparkException("Job aborted.", cause)
+ new SparkException(
+ errorClass = "JOB_ABORTED",
+ messageParameters = Array.empty, cause)
}
def taskFailedWhileWritingRowsError(cause: Throwable): Throwable = {
- new SparkException("Task failed while writing rows.", cause)
+ new SparkException(
+ errorClass = "FAILED_TASK_WHILE_WRITING_ROWS",
+ messageParameters = Array.empty, cause)
}
def readCurrentFileNotFoundError(e: FileNotFoundException): Throwable = {
- new FileNotFoundException(
- s"""
- |${e.getMessage}\n
- |It is possible the underlying files have been updated. You can
explicitly invalidate
- |the cache in Spark by running 'REFRESH TABLE tableName' command in
SQL or by
- |recreating the Dataset/DataFrame involved.
- """.stripMargin)
+ new SparkFileNotFoundException(
+ errorClass = "CANNOT_READ_CURRENT_FILE",
+ messageParameters = Array(e.getMessage))
}
def unsupportedSaveModeError(saveMode: String, pathExists: Boolean):
Throwable = {
- new IllegalStateException(s"unsupported save mode $saveMode ($pathExists)")
+ new SparkIllegalStateException(
+ errorClass = "UNSUPPORTED_SAVE_MODE",
+ messageParameters = Array(saveMode + " (" + pathExists.toString + ")"))
Review comment:
I agree
[#comments](https://github.com/apache/spark/pull/34093#discussion_r729995285).
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