feat(ddl): support alter table cast tuple type column

[b41sh]

I hereby agree to the terms of the CLA available at: https://docs.databend.com/dev/policies/cla/

Summary

Add a new function arrays_zip to build Array(Tuple) for multiple Array arguments, for example:

root@0.0.0.0:48000/default> SELECT arrays_zip([1,2,3], ['a','b','c'], 10);

SELECT
  arrays_zip([1,2,3], ['a','b','c'], 10)

┌─────────────────────────────────────────────┐
│ arrays_zip([1, 2, 3], ['a', 'b', 'c'], 10) │
│      Array(Tuple(UInt8, String, UInt8))     │
├─────────────────────────────────────────────┤
│ [(1,'a',10),(2,'b',10),(3,'c',10)]          │
└─────────────────────────────────────────────┘
1 row read in 0.096 sec. Processed 1 row, 1 B (10.42 rows/s, 10 B/s)

Alter table modify column allow convert Tuple and Array(Tuple) with different leaf column numbers. As Tuple type can't auto cast to different Tuple type, we read tuple leaf columns and build a new tuple with tuple and arrays_zip function.

for example:

root@0.0.0.0:48000/default> create table t1(
  a int,
  b Array(Tuple(Float64 NULL, Float64 NULL, String NULL) NULL) NULL
);

root@0.0.0.0:48000/default> insert into t1 values(1, null),(2, [(1,2,'x'),(3,4,'y')]),(3, [(5,null,null),(6,null,'z')]);

root@0.0.0.0:48000/default> select * from t1;
┌────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│        a        │                                             b                                            │
│ Nullable(Int32) │ Nullable(Array(Nullable(Tuple(Nullable(Float64), Nullable(Float64), Nullable(String))))) │
├─────────────────┼──────────────────────────────────────────────────────────────────────────────────────────┤
│               1 │ NULL                                                                                     │
│               2 │ [(1,2,'x'),(3,4,'y')]                                                                    │
│               3 │ [(5,NULL,NULL),(6,NULL,'z')]                                                             │
└────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
3 rows read in 0.040 sec. Processed 3 rows, 162 B (75 rows/s, 3.96 KiB/s)

root@0.0.0.0:48000/default> alter table t1 MODIFY COLUMN b Array(Tuple(Float64 NULL, Float64 NULL, String NULL, String NULL) NULL) NULL;

root@0.0.0.0:48000/default> select * from t1;

┌──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│        a        │                                                      b                                                     │
│ Nullable(Int32) │ Nullable(Array(Nullable(Tuple(Nullable(Float64), Nullable(Float64), Nullable(String), Nullable(String))))) │
├─────────────────┼────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│               1 │ NULL                                                                                                       │
│               2 │ [(1,2,'x',NULL),(3,4,'y',NULL)]                                                                            │
│               3 │ [(5,NULL,NULL,NULL),(6,NULL,'z',NULL)]                                                                     │
└──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
3 rows read in 0.047 sec. Processed 3 rows, 211 B (63.83 rows/s, 4.38 KiB/s)

in this example, we use the following SQL to read values from the orginal table and insert the values into the modified table

SELECT a, if(is_not_null(b), arrays_zip(array_transform(b, x -> x.1), array_transform(b, x -> x.2), array_transform(b, x -> x.3), NULL), NULL) FROM t1;

array_transform function convert the Array Tuple inner column to an Array, and if the original inner column not exist, use the default value instead. arrays_zip function use those arguments to construct a new Array Tuple column

• fixes: #[Link the issue here]

Tests

• Unit Test
• Logic Test
• Benchmark Test
• No Test - Explain why

Type of change

• Bug Fix (non-breaking change which fixes an issue)
• New Feature (non-breaking change which adds functionality)
• Breaking Change (fix or feature that could cause existing functionality not to work as expected)
• Documentation Update
• Refactoring
• Performance Improvement
• Other (please describe):

---

This change is 

[sundy-li]

Better rename it into array_zip https://docs.databricks.com/en/sql/language-manual/functions/arrays_zip.html