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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* 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,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.sql.execution.datasources.jdbc
import org.apache.spark.sql.{AnalysisException, DataFrame, SaveMode, SQLContext}
import org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils._
import org.apache.spark.sql.sources.{BaseRelation, CreatableRelationProvider, DataSourceRegister, RelationProvider}
class JdbcRelationProvider extends CreatableRelationProvider
with RelationProvider with DataSourceRegister {
override def shortName(): String = "jdbc"
override def createRelation(
sqlContext: SQLContext,
parameters: Map[String, String]): BaseRelation = {
import JDBCOptions._
val jdbcOptions = new JDBCOptions(parameters)
val partitionColumn = jdbcOptions.partitionColumn
val lowerBound = jdbcOptions.lowerBound
val upperBound = jdbcOptions.upperBound
val numPartitions = jdbcOptions.numPartitions
val partitionInfo = if (partitionColumn.isEmpty) {
assert(lowerBound.isEmpty && upperBound.isEmpty, "When 'partitionColumn' is not specified, " +
s"'$JDBC_LOWER_BOUND' and '$JDBC_UPPER_BOUND' are expected to be empty")
null
} else {
assert(lowerBound.nonEmpty && upperBound.nonEmpty && numPartitions.nonEmpty,
s"When 'partitionColumn' is specified, '$JDBC_LOWER_BOUND', '$JDBC_UPPER_BOUND', and " +
s"'$JDBC_NUM_PARTITIONS' are also required")
JDBCPartitioningInfo(
partitionColumn.get, lowerBound.get, upperBound.get, numPartitions.get)
}
val parts = JDBCRelation.columnPartition(partitionInfo)
JDBCRelation(parts, jdbcOptions)(sqlContext.sparkSession)
}
override def createRelation(
sqlContext: SQLContext,
mode: SaveMode,
parameters: Map[String, String],
df: DataFrame): BaseRelation = {
val options = new JDBCOptions(parameters)
val isCaseSensitive = sqlContext.conf.caseSensitiveAnalysis
val conn = JdbcUtils.createConnectionFactory(options)()
try {
val tableExists = JdbcUtils.tableExists(conn, options)
if (tableExists) {
mode match {
case SaveMode.Overwrite =>
if (options.isTruncate && isCascadingTruncateTable(options.url) == Some(false)) {
// In this case, we should truncate table and then load.
truncateTable(conn, options)
val tableSchema = JdbcUtils.getSchemaOption(conn, options)
saveTable(df, tableSchema, isCaseSensitive, options)
} else {
// Otherwise, do not truncate the table, instead drop and recreate it
dropTable(conn, options.table)
createTable(conn, df, options)
saveTable(df, Some(df.schema), isCaseSensitive, options)
}
case SaveMode.Append =>
val tableSchema = JdbcUtils.getSchemaOption(conn, options)
saveTable(df, tableSchema, isCaseSensitive, options)
case SaveMode.ErrorIfExists =>
throw new AnalysisException(
s"Table or view '${options.table}' already exists. SaveMode: ErrorIfExists.")
case SaveMode.Ignore =>
// With `SaveMode.Ignore` mode, if table already exists, the save operation is expected
// to not save the contents of the DataFrame and to not change the existing data.
// Therefore, it is okay to do nothing here and then just return the relation below.
}
} else {
createTable(conn, df, options)
saveTable(df, Some(df.schema), isCaseSensitive, options)
}
} finally {
conn.close()
}
createRelation(sqlContext, parameters)
}
}
