cloud-fan commented on code in PR #47233:
URL: https://github.com/apache/spark/pull/47233#discussion_r1717319483
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sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala:
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@@ -4136,6 +4136,29 @@ class Dataset[T] private[sql](
new MergeIntoWriter[T](table, this, condition)
}
+ /**
+ * Update rows in a table that match a condition.
+ *
+ * Scala Example:
+ * {{{
+ * spark.table("source").update(Map("salary" -> lit(200)))
+ * .where($"salary" === 100)
+ * .execute()
+ *
+ * }}}
+ * @param assignments A Map of column names to Column expressions
representing the updates
+ * to be applied.
+ * @since 4.0.0
+ */
+ def update(assignments: Map[String, Column]): UpdateWriter[T] = {
Review Comment:
well, we can add more overloads to include the `options`. My worry is many
people are used to the common DataFrame pattern:
`sourceDF.transformAPIs.write.writeConfigurationAPIs.insertInto/save/saveAsTable`.
I think it's better to use a different API style for UPDATE and DELETE, as
they don't have a source query.
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