HyukjinKwon commented on a change in pull request #32723:
URL: https://github.com/apache/spark/pull/32723#discussion_r642803647
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File path: sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
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@@ -301,23 +306,22 @@ class DataFrameReader private[sql](sparkSession:
SparkSession) extends Logging {
* Don't create too many partitions in parallel on a large cluster;
otherwise Spark might crash
* your external database systems.
*
- * @param url JDBC database url of the form `jdbc:subprotocol:subname`.
+ * You can find the JDBC-specific options for reading table 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 columnName the name of a column of numeric, date, or timestamp type
- * that will be used for partitioning.
- * @param lowerBound the minimum value of `columnName` used to decide
partition stride.
- * @param upperBound the maximum value of `columnName` used to decide
partition stride.
- * @param numPartitions the number of partitions. This, along with
`lowerBound` (inclusive),
- * `upperBound` (exclusive), form partition strides for
generated WHERE
- * clause expressions used to split the column
`columnName` evenly. When
- * the input is less than 1, the number is set to 1.
+ * @param columnName alias of `partitionColumn` option. Refer to
`partitionColumn` in
Review comment:
```suggestion
* @param columnName Alias of `partitionColumn` option. Refer to
`partitionColumn` in
```
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