amaliujia commented on code in PR #40358:
URL: https://github.com/apache/spark/pull/40358#discussion_r1131967870
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connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala:
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@@ -345,6 +347,37 @@ final class DataFrameWriter[T] private[sql] (ds:
Dataset[T]) {
})
}
+ /**
+ * Saves the content of the `DataFrame` to an external database table via
JDBC. In the case the
+ * table already exists in the external database, behavior of this function
depends on the save
+ * mode, specified by the `mode` function (default to throwing an exception).
+ *
+ * Don't create too many partitions in parallel on a large cluster;
otherwise Spark might crash
+ * your external database systems.
+ *
+ * JDBC-specific option and parameter documentation for storing tables via
JDBC in <a
+ *
href="https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-option";>
+ * Data Source Option</a> in the version you use.
+ *
+ * @param table
+ * Name of the table in the external database.
+ * @param connectionProperties
+ * JDBC database connection arguments, a list of arbitrary string
tag/value. Normally at least
+ * a "user" and "password" property should be included. "batchsize" can be
used to control the
+ * number of rows per insert. "isolationLevel" can be one of "NONE",
"READ_COMMITTED",
+ * "READ_UNCOMMITTED", "REPEATABLE_READ", or "SERIALIZABLE", corresponding
to standard
+ * transaction isolation levels defined by JDBC's Connection object, with
default of
+ * "READ_UNCOMMITTED".
+ * @since 1.4.0
Review Comment:
since 3.4.0
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