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[SPARK-46443][SQL] Decimal precision and scale should decided by H2 dialect. #44398

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[SPARK-46443][SQL] Decimal precision and scale should decided by H2 dialect. #44398

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16 changes: 15 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/jdbc/H2Dialect.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ import org.apache.spark.sql.connector.catalog.functions.UnboundFunction
import org.apache.spark.sql.connector.catalog.index.TableIndex
import org.apache.spark.sql.connector.expressions.{Expression, FieldReference, NamedReference}
import org.apache.spark.sql.execution.datasources.jdbc.{JDBCOptions, JdbcUtils}
import org.apache.spark.sql.types.{BooleanType, ByteType, DataType, DecimalType, ShortType, StringType}
import org.apache.spark.sql.types.{BooleanType, ByteType, DataType, DecimalType, MetadataBuilder, ShortType, StringType}

private[sql] object H2Dialect extends JdbcDialect {
override def canHandle(url: String): Boolean =
Expand All @@ -57,6 +57,20 @@ private[sql] object H2Dialect extends JdbcDialect {
override def isSupportedFunction(funcName: String): Boolean =
supportedFunctions.contains(funcName)

override def getCatalystType(
sqlType: Int, typeName: String, size: Int, md: MetadataBuilder): Option[DataType] = {
sqlType match {
case Types.NUMERIC if size > 38 =>
// H2 supports very large decimal precision like 100000. The max precision in Spark is only
// 38. Here we shrink both the precision and scale of H2 decimal to fit Spark, and still
// keep the ratio between them.
val scale = if (null != md) md.build().getLong("scale") else 0L
val selectedScale = (DecimalType.MAX_PRECISION * (scale.toDouble / size.toDouble)).toInt
Option(DecimalType(DecimalType.MAX_PRECISION, selectedScale))
case _ => None
}
}

override def getJDBCType(dt: DataType): Option[JdbcType] = dt match {
case StringType => Option(JdbcType("CLOB", Types.CLOB))
case BooleanType => Some(JdbcType("BOOLEAN", Types.BOOLEAN))
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