Databricks: Add support for OPTIMIZE, PARTITIONED BY, and STRUCT syntax

[funcpp]

Summary

This PR adds several Databricks Delta Lake SQL syntax features:

1. OPTIMIZE statement support

Adds support for the Databricks OPTIMIZE statement syntax:

OPTIMIZE table_name [WHERE predicate] [ZORDER BY (col1, col2, ...)]

Reference: https://docs.databricks.com/en/sql/language-manual/delta-optimize.html

Key difference from ClickHouse: Databricks omits the TABLE keyword after OPTIMIZE.

2. PARTITIONED BY with optional column types

Databricks allows partition columns to reference existing table columns without specifying types:

CREATE TABLE t (col1 STRING, col2 INT) PARTITIONED BY (col1)
CREATE TABLE t (name STRING) PARTITIONED BY (year INT, month INT)

Reference: https://docs.databricks.com/en/sql/language-manual/sql-ref-partition.html

3. STRUCT type with colon syntax

Databricks uses Hive-style colon separator for struct field definitions:

STRUCT<field_name: field_type, ...>
ARRAY<STRUCT<finish_flag: STRING, survive_flag: STRING, score: INT>>

Reference: https://docs.databricks.com/en/sql/language-manual/data-types/struct-type.html

The colon is optional per the spec, so both field: type and field type syntaxes are now accepted.

Changes

• Extended OptimizeTable AST to support Databricks-specific fields (predicate, zorder, has_table_keyword)
• Added parse_column_def_for_partition() to handle optional column types in PARTITIONED BY
• Added DatabricksDialect to STRUCT type parsing
• Modified parse_struct_field_def() to accept optional colon separator

Test plan

• Added tests for OPTIMIZE statement variations
• Added tests for PARTITIONED BY with/without column types
• Added tests for STRUCT type with colon syntax
• Verified existing ClickHouse and BigQuery tests still pass
• All tests pass (cargo test)