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[SPARK-42846][SQL] Remove error condition _LEGACY_ERROR_TEMP_2011 #48086

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[SPARK-42846][SQL] Remove error condition _LEGACY_ERROR_TEMP_2011 #48086

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262d1ad
Remove _LEGACY_ERROR_TEMP_2011
ivanjevtic-db Sep 12, 2024
c3972ff
Remove unused import
ivanjevtic-db Sep 12, 2024
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5 changes: 0 additions & 5 deletions common/utils/src/main/resources/error/error-conditions.json
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Original file line number Diff line number Diff line change
Expand Up @@ -6656,11 +6656,6 @@
"Type <dataType> does not support ordered operations."
]
},
"_LEGACY_ERROR_TEMP_2011" : {
"message" : [
"Unexpected data type <dataType>."
]
},
"_LEGACY_ERROR_TEMP_2013" : {
"message" : [
"Negative values found in <frequencyExpression>"
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4 changes: 2 additions & 2 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala
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Expand Up @@ -21,12 +21,12 @@ import java.util.Locale

import scala.util.control.Exception.allCatch

import org.apache.spark.SparkException
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.catalyst.analysis.TypeCoercion
import org.apache.spark.sql.catalyst.expressions.ExprUtils
import org.apache.spark.sql.catalyst.util.{DateFormatter, TimestampFormatter}
import org.apache.spark.sql.catalyst.util.LegacyDateFormats.FAST_DATE_FORMAT
import org.apache.spark.sql.errors.QueryExecutionErrors
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._

Expand Down Expand Up @@ -138,7 +138,7 @@ class CSVInferSchema(val options: CSVOptions) extends Serializable {
case BooleanType => tryParseBoolean(field)
case StringType => StringType
case other: DataType =>
throw QueryExecutionErrors.dataTypeUnexpectedError(other)
throw SparkException.internalError(s"Unexpected data type $other")
}
compatibleType(typeSoFar, typeElemInfer).getOrElse(StringType)
}
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6 changes: 3 additions & 3 deletions ...ain/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
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Expand Up @@ -21,6 +21,7 @@ import java.nio.ByteBuffer

import com.google.common.primitives.{Doubles, Ints, Longs}

import org.apache.spark.SparkException
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.analysis.{FunctionRegistry, TypeCheckResult}
import org.apache.spark.sql.catalyst.analysis.TypeCheckResult.{DataTypeMismatch, TypeCheckSuccess}
Expand All @@ -32,7 +33,6 @@ import org.apache.spark.sql.catalyst.types.PhysicalNumericType
import org.apache.spark.sql.catalyst.util.{ArrayData, GenericArrayData}
import org.apache.spark.sql.catalyst.util.QuantileSummaries
import org.apache.spark.sql.catalyst.util.QuantileSummaries.{defaultCompressThreshold, Stats}
import org.apache.spark.sql.errors.QueryExecutionErrors
import org.apache.spark.sql.types._
import org.apache.spark.util.ArrayImplicits._

Expand Down Expand Up @@ -189,7 +189,7 @@ case class ApproximatePercentile(
PhysicalNumericType.numeric(n)
.toDouble(value.asInstanceOf[PhysicalNumericType#InternalType])
case other: DataType =>
throw QueryExecutionErrors.dataTypeUnexpectedError(other)
throw SparkException.internalError(s"Unexpected data type $other")
}
buffer.add(doubleValue)
}
Expand All @@ -214,7 +214,7 @@ case class ApproximatePercentile(
case DoubleType => doubleResult
case _: DecimalType => doubleResult.map(Decimal(_))
case other: DataType =>
throw QueryExecutionErrors.dataTypeUnexpectedError(other)
throw SparkException.internalError(s"Unexpected data type $other")
}
if (result.length == 0) {
null
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12 changes: 0 additions & 12 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/errors/QueryExecutionErrors.scala
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Expand Up @@ -384,18 +384,6 @@ private[sql] object QueryExecutionErrors extends QueryErrorsBase with ExecutionE
s"The aggregate window function ${toSQLId(funcName)} does not support merging.")
}

def dataTypeUnexpectedError(dataType: DataType): SparkUnsupportedOperationException = {
new SparkUnsupportedOperationException(
errorClass = "_LEGACY_ERROR_TEMP_2011",
messageParameters = Map("dataType" -> dataType.catalogString))
}

def typeUnsupportedError(dataType: DataType): SparkIllegalArgumentException = {
new SparkIllegalArgumentException(
errorClass = "_LEGACY_ERROR_TEMP_2011",
messageParameters = Map("dataType" -> dataType.toString()))
}

def negativeValueUnexpectedError(
frequencyExpression : Expression): SparkIllegalArgumentException = {
new SparkIllegalArgumentException(
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4 changes: 2 additions & 2 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala
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Expand Up @@ -29,7 +29,7 @@ import scala.util.control.NonFatal

import org.apache.hadoop.fs.Path

import org.apache.spark.SparkRuntimeException
import org.apache.spark.{SparkException, SparkRuntimeException}
import org.apache.spark.sql.catalyst.{InternalRow, SQLConfHelper}
import org.apache.spark.sql.catalyst.analysis.TypeCoercion
import org.apache.spark.sql.catalyst.catalog.CatalogTypes.TablePartitionSpec
Expand Down Expand Up @@ -550,7 +550,7 @@ object PartitioningUtils extends SQLConfHelper {
Cast(Literal(unescapePathName(value)), it).eval()
case BinaryType => value.getBytes()
case BooleanType => value.toBoolean
case dt => throw QueryExecutionErrors.typeUnsupportedError(dt)
case dt => throw SparkException.internalError(s"Unsupported partition type: $dt")
}

def validatePartitionColumn(
Expand Down