## What changes were proposed in this pull request?
Here is a table about the behaviours of `array`/`map` and `greatest`/`least` in Hive, MySQL and Postgres:
| |Hive|MySQL|Postgres|
|---|---|---|---|---|
|`array`/`map`|can find a wider type with decimal type arguments, and will truncate the wider decimal type if necessary|can find a wider type with decimal type arguments, no truncation problem|can find a wider type with decimal type arguments, no truncation problem|
|`greatest`/`least`|can find a wider type with decimal type arguments, and truncate if necessary, but can't do string promotion|can find a wider type with decimal type arguments, no truncation problem, but can't do string promotion|can find a wider type with decimal type arguments, no truncation problem, but can't do string promotion|
I think these behaviours makes sense and Spark SQL should follow them.
This PR fixes `array` and `map` by using `findWiderCommonType` to get the wider type.
This PR fixes `greatest` and `least` by add a `findWiderTypeWithoutStringPromotion`, which provides similar semantic of `findWiderCommonType`, but without string promotion.
## How was this patch tested?
new tests in `TypeCoersionSuite`
Author: Wenchen Fan <wenchen@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Closes#14439 from cloud-fan/bug.
b55f34370f