[SPARK-41874][CONNECT][PYTHON] Implement DataFrame.sameSemantics

[techaddict]

What changes were proposed in this pull request?

Implement DataFrame.sameSemantics

Why are the changes needed?

api coverage

Does this PR introduce any user-facing change?

yes

How was this patch tested?

new Unit tests

[techaddict]

cc: @HyukjinKwon @zhengruifeng

[zhengruifeng]

@techaddict thank you for working on it.

we had some discussion on sameSemantics and semanticHash in #38742 (comment)

I think this one and #39427 are controversial, and the two are developer APIs (

spark/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala

Lines 3941 to 3967 in 470beda

	/**
	* Returns `true` when the logical query plans inside both [[Dataset]]s are equal and
	* therefore return same results.
	*
	* @note The equality comparison here is simplified by tolerating the cosmetic differences
	* such as attribute names.
	* @note This API can compare both [[Dataset]]s very fast but can still return `false` on
	* the [[Dataset]] that return the same results, for instance, from different plans. Such
	* false negative semantic can be useful when caching as an example.
	* @since 3.1.0
	*/
	@DeveloperApi
	def sameSemantics(other: Dataset[T]): Boolean = {
	queryExecution.analyzed.sameResult(other.queryExecution.analyzed)
	}
	/**
	* Returns a `hashCode` of the logical query plan against this [[Dataset]].
	*
	* @note Unlike the standard `hashCode`, the hash is calculated against the query plan
	* simplified by tolerating the cosmetic differences such as attribute names.
	* @since 3.1.0
	*/
	@DeveloperApi
	def semanticHash(): Int = {
	queryExecution.analyzed.semanticHash()
	}

).

I think we may not add them.