feat: add read_parquet, read_csv, read_json, read_avro SQL table functions

[crm26]

Summary

Adds four inline SQL table functions for ad-hoc file querying:

SELECT * FROM read_parquet('/path/to/*.parquet')
SELECT * FROM read_csv('/data/file.csv')
SELECT * FROM read_json('/data/file.json')
SELECT * FROM read_avro('/data/file.avro')

Closes #3773

Design

Each function is a thin TableFunctionImpl wrapper (~60 lines) over ListingTable:

1. Extract path string from Expr::Literal
2. Construct ListingOptions with the format's FileFormat
3. Infer schema via blocking bridge
4. Return ListingTable as TableProvider

Since the SQL planner wraps UDTF output as LogicalPlan::TableScan, all optimizer rules apply automatically:

• Filter pushdown — verified via EXPLAIN test
• Projection pushdown — verified via EXPLAIN test
• Partition pruning — inherited from ListingTable

Async bridge

call_with_args is a sync fn but infer_schema is async. Uses std::thread::scope + Handle::block_on (not block_in_place) so it works on both multi-thread and current-thread Tokio runtimes. Tested with single-threaded runtime.

Feature gating

• read_parquet — requires parquet feature (default on)
• read_avro — requires avro feature (default off)
• read_csv / read_json — always available (no heavy optional dependencies)

Limitations (v1)

• Positional arguments only — no named args like has_header => true
• No user-supplied schema override
• No explicit Hive partition column specification
• S3 paths require a registered object store

These can be addressed in follow-on PRs.

Tests

16 tests covering: basic read, filtered read, projection, aggregation, glob multi-file, error paths (no args, wrong type), filter/projection pushdown verification, and single-threaded runtime safety.