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[Kernel] Add type widening to supported table features (#3656)
## Description Allow reading and writing to tables that have the type widening table features enabled (both preview and stable table feature). Reading: - The default kernel parquet reader supports widening conversions since #3541. Engines may also choose to implement type widening natively in their parquet reader if they wish. Writing: - Nothing to do, type widening doesn't impact the write path - writing data always uses the latest data schema. ## How was this patch tested? Added read integration tests. Tests are based on golden tables. Generating the tables requires Spark 4.0, due to spark master cross-compilation being broken, the table generation code is not included here. The following steps where used to generate the tables. 1. Create a table with initial data types and insert initial data 2. Enable type widening and schema evolution 3. Insert data with wider type for each column. Column types are automatically widened during schema evolution. `type-widening` table: | Column | Initial type | Widened Type | | - | - | - | | byte_long | byte | long | | int_long | int | long | | float_double | float | double | | byte_double | byte | double | | short_double | short | double | | int_double | int | double | | decimal_decimal_same_scale | decimal(10, 2) | decimal(20, 2) | | decimal_decimal_greater_scale | decimal(10, 2) | decimal(20, 5) | | byte_decimal | byte | decimal(11, 1) | | short_decimal | short | decimal(11, 1) | | int_decimal | int | decimal(11, 1) | | long_decimal | long | decimal(21, 1) | | date_timestamp_ntz | date | timestamp_ntz | `type-widening-nested` table: | Column | Initial type | Widened Type | | - | - | - | | struct | struct<a: int> | struct<a: long> | | map | map<int, int> | map<long, long> | | array | array<int> | array<long> | ## Does this PR introduce _any_ user-facing changes? Yes, it's now possible to read from and write to delta tables with type widening enabled using kernel.
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