org.apache.spark.sql.jdbc.OracleDialect.scala Maven / Gradle / Ivy
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* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.spark.sql.jdbc
import java.sql.Types
import org.apache.spark.sql.types._
private case object OracleDialect extends JdbcDialect {
override def canHandle(url: String): Boolean = url.startsWith("jdbc:oracle")
override def getCatalystType(
sqlType: Int, typeName: String, size: Int, md: MetadataBuilder): Option[DataType] = {
if (sqlType == Types.NUMERIC) {
val scale = if (null != md) md.build().getLong("scale") else 0L
size match {
// Handle NUMBER fields that have no precision/scale in special way
// because JDBC ResultSetMetaData converts this to 0 precision and -127 scale
// For more details, please see
// https://github.com/apache/spark/pull/8780#issuecomment-145598968
// and
// https://github.com/apache/spark/pull/8780#issuecomment-144541760
case 0 => Option(DecimalType(DecimalType.MAX_PRECISION, 10))
// Handle FLOAT fields in a special way because JDBC ResultSetMetaData converts
// this to NUMERIC with -127 scale
// Not sure if there is a more robust way to identify the field as a float (or other
// numeric types that do not specify a scale.
case _ if scale == -127L => Option(DecimalType(DecimalType.MAX_PRECISION, 10))
case _ => None
}
} else {
None
}
}
override def getJDBCType(dt: DataType): Option[JdbcType] = dt match {
// For more details, please see
// https://docs.oracle.com/cd/E19501-01/819-3659/gcmaz/
case BooleanType => Some(JdbcType("NUMBER(1)", java.sql.Types.BOOLEAN))
case IntegerType => Some(JdbcType("NUMBER(10)", java.sql.Types.INTEGER))
case LongType => Some(JdbcType("NUMBER(19)", java.sql.Types.BIGINT))
case FloatType => Some(JdbcType("NUMBER(19, 4)", java.sql.Types.FLOAT))
case DoubleType => Some(JdbcType("NUMBER(19, 4)", java.sql.Types.DOUBLE))
case ByteType => Some(JdbcType("NUMBER(3)", java.sql.Types.SMALLINT))
case ShortType => Some(JdbcType("NUMBER(5)", java.sql.Types.SMALLINT))
case StringType => Some(JdbcType("VARCHAR2(255)", java.sql.Types.VARCHAR))
case _ => None
}
override def isCascadingTruncateTable(): Option[Boolean] = Some(false)
}