Github user HarshSharma8 commented on a diff in the pull request:
https://github.com/apache/spark/pull/16997#discussion_r102011677
--- Diff: docs/sql-programming-guide.md ---
@@ -297,6 +297,9 @@ reflection and become the names of the columns. Case
classes can also be nested
types such as `Seq`s or `Array`s. This RDD can be implicitly converted to
a DataFrame and then be
registered as a table. Tables can be used in subsequent SQL statements.
+Spark Encoders are used to convert a JVM object to Spark SQL
representation. When we want to make a datase, Spark requires an encoder which
takes the form Encoder[T] where T is the type we want to be encoded. When we
try to create dataset with a custom type of object, then may result into
<b>java.lang.UnsupportedOperationException: No Encoder found for
Object-Name</b>.
--- End diff --
Hello srowen,
I have updated the content to match the void of the content, you can have
another look at it.
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