gengliangwang opened a new pull request #31349:
URL: https://github.com/apache/spark/pull/31349
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### What changes were proposed in this pull request?
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In Spark ANSI mode, the type coercion rules are based on the type precedence
lists of the input data types.
As per the section "Type precedence list determination" of "ISO/IEC
9075-2:2011
Information technology — Database languages - SQL — Part 2: Foundation
(SQL/Foundation)", the type precedence lists of primitive data types are as
following:
- Byte: Byte, Short, Int, Long, Decimal, Float, Double
- Short: Short, Int, Long, Decimal, Float, Double
- Int: Int, Long, Decimal, Float, Double
- Long: Long, Decimal, Float, Double
- Decimal: Any wider Numeric type
- Float: Float, Double
- Double: Double
- String: String
- Date: Date, Timestamp
- Timestamp: Timestamp
- Binary: Binary
- Boolean: Boolean
- Interval: Interval
As for complex data types, Spark will determine the precedent list
recursively based on their sub-types.
- With the definition of type precedent list, the general type coercion
rules are as following:
- Data type S is allowed to be implicitly cast as type T iff T is in the
precedence list of S
- Comparison is allowed iff the data type precedence list of both sides has
at least one common element. When evaluating the comparison, Spark casts both
sides as the tightest common data type of their precedent lists.
- There should be at least one common data type among all the children's
precedence lists for the following operators. The data type of the operator is
the tightest common precedent data type.
```
In, Except(odd), Intersect, Greatest, Least, Union, If, CaseWhen,
CreateArray, Array Concat,Sequence, MapConcat, CreateMap
```
- For complex types (struct, array, map), Spark recursively looks into the
element type and applies the rules above. If the element nullability is
converted from true to false, add runtime null check to the elements.
### Why are the changes needed?
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The current type coercion rules are complex. Also, they are very hard to
describe and understand. For details please refer the attached documentation
"Default Type coercion rules of Spark"
[Default Type coercion rules of
Spark.pdf](https://github.com/apache/spark/files/5874362/Default.Type.coercion.rules.of.Spark.pdf)
This PR is to create a new and strict type coercion system under ANSI mode.
The rules are simple and clean, so that users can follow them easily
### Does this PR introduce _any_ user-facing change?
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Yes, new implicit cast syntax rules in ANSI mode
### How was this patch tested?
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Unit tests
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