Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/14054#discussion_r71093448
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
---
@@ -284,9 +286,17 @@ object JdbcUtils extends Logging {
val rddSchema = df.schema
val getConnection: () => Connection = createConnectionFactory(url,
properties)
val batchSize = properties.getProperty(JDBC_BATCH_INSERT_SIZE,
"1000").toInt
- df.foreachPartition { iterator =>
- savePartition(getConnection, table, iterator, rddSchema, nullTypes,
batchSize, dialect)
- }
+ val isolationLevel =
+ properties.getProperty(JDBC_TXN_ISOLATION_LEVEL, "READ_UNCOMMITTED")
match {
--- End diff --
If not specified, should we use the default transaction isolation level set
by the data sources?
My major concern is that the default level `READ_UNCOMMITTED` might not be
supported by the underlying JDBC sources. In this case, we might get a
`SQLException`?
Thus, maybe we should check whether the isolation we specified is supported
or not by using `supportsTransactionIsolationLevel`
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