[SPARK-15494][SQL] encoder code cleanup

## What changes were proposed in this pull request?

Our encoder framework has been evolved a lot, this PR tries to clean up the code to make it more readable and emphasise the concept that encoder should be used as a container of serde expressions.

1. move validation logic to analyzer instead of encoder
2. only have a `resolveAndBind` method in encoder instead of `resolve` and `bind`, as we don't have the encoder life cycle concept anymore.
3. `Dataset` don't need to keep a resolved encoder, as there is no such concept anymore. bound encoder is still needed to do serialization outside of query framework.
4. Using `BoundReference` to represent an unresolved field in deserializer expression is kind of weird, this PR adds a `GetColumnByOrdinal` for this purpose. (serializer expression still use `BoundReference`, we can replace it with `GetColumnByOrdinal` in follow-ups)

## How was this patch tested?

existing test

Author: Wenchen Fan <wenchen@databricks.com>
Author: Cheng Lian <lian@databricks.com>

Closes #13269 from cloud-fan/clean-encoder.

1 files changed, 1 insertions, 1 deletions

diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/UDTSerializationBenchmark.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/UDTSerializationBenchmark.scala
index be7110ad6b..8b439e6b7a 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/UDTSerializationBenchmark.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/UDTSerializationBenchmark.scala
@@ -29,7 +29,7 @@ object UDTSerializationBenchmark {
     val iters = 1e2.toInt
     val numRows = 1e3.toInt
 
-    val encoder = ExpressionEncoder[Vector].defaultBinding
+    val encoder = ExpressionEncoder[Vector].resolveAndBind()
 
     val vectors = (1 to numRows).map { i =>
       Vectors.dense(Array.fill(1e5.toInt)(1.0 * i))