org.apache.spark.sql.jdbc.TeradataDialect.scala Maven / Gradle / Ivy
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* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
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* See the License for the specific language governing permissions and
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package org.apache.spark.sql.jdbc
import java.sql.Types
import java.util.Locale
import org.apache.spark.sql.connector.catalog.Identifier
import org.apache.spark.sql.types._
private case object TeradataDialect extends JdbcDialect {
override def canHandle(url: String): Boolean =
url.toLowerCase(Locale.ROOT).startsWith("jdbc:teradata")
// scalastyle:off line.size.limit
// See https://docs.teradata.com/r/Teradata-VantageTM-SQL-Functions-Expressions-and-Predicates/March-2019/Aggregate-Functions
// scalastyle:on line.size.limit
private val supportedAggregateFunctions = Set("MAX", "MIN", "SUM", "COUNT", "AVG",
"VAR_POP", "VAR_SAMP", "STDDEV_POP", "STDDEV_SAMP", "COVAR_POP", "COVAR_SAMP", "CORR")
private val supportedFunctions = supportedAggregateFunctions
override def isSupportedFunction(funcName: String): Boolean =
supportedFunctions.contains(funcName)
override def getJDBCType(dt: DataType): Option[JdbcType] = dt match {
case StringType => Some(JdbcType("VARCHAR(255)", java.sql.Types.VARCHAR))
case BooleanType => Option(JdbcType("CHAR(1)", java.sql.Types.CHAR))
case _ => None
}
// Teradata does not support cascading a truncation
override def isCascadingTruncateTable(): Option[Boolean] = Some(false)
/**
* The SQL query used to truncate a table. Teradata does not support the 'TRUNCATE' syntax that
* other dialects use. Instead, we need to use a 'DELETE FROM' statement.
* @param table The table to truncate.
* @param cascade Whether or not to cascade the truncation. Default value is the
* value of isCascadingTruncateTable(). Teradata does not support cascading a
* 'DELETE FROM' statement (and as mentioned, does not support 'TRUNCATE' syntax)
* @return The SQL query to use for truncating a table
*/
override def getTruncateQuery(
table: String,
cascade: Option[Boolean] = isCascadingTruncateTable): String = {
s"DELETE FROM $table ALL"
}
// See https://docs.teradata.com/reader/scPHvjfglIlB8F70YliLAw/wysTNUMsP~0aGzksLCl1kg
override def renameTable(oldTable: Identifier, newTable: Identifier): String = {
s"RENAME TABLE ${getFullyQualifiedQuotedTableName(oldTable)} TO " +
s"${getFullyQualifiedQuotedTableName(newTable)}"
}
override def getLimitClause(limit: Integer): String = {
""
}
override def getCatalystType(
sqlType: Int, typeName: String, size: Int, md: MetadataBuilder): Option[DataType] = {
sqlType match {
case Types.NUMERIC =>
if (md == null) {
Some(DecimalType.SYSTEM_DEFAULT)
} else {
val scale = md.build().getLong("scale")
// In Teradata, define Number without parameter means precision and scale is flexible.
// However, in this case, the scale returned from JDBC is 0, which will lead to
// fractional part loss. And the precision returned from JDBC is 40, which conflicts to
// DecimalType.MAX_PRECISION.
// Handle this special case by adding explicit conversion to system default decimal type.
if (size == 40) {
if (scale == 0) Some(DecimalType.SYSTEM_DEFAULT)
// In Teradata, Number(*, scale) is valid but in this case, the precision
// returned from JDBC is also 40, which conflicts to DecimalType.MAX_PRECISION.
else Some(DecimalType(DecimalType.MAX_PRECISION, scale.toInt))
} else {
// Normal case, Number(precision, scale) is explicitly set in Teradata
Some(DecimalType(size, scale.toInt))
}
}
case _ => None
}
}
}