delta lake and iceberg table support (#43)

* delta support

* imports

raysql/context.py

@@ -8,7 +8,7 @@
 
 import raysql
 from raysql import Context, ExecutionGraph, QueryStage
-
+from typing import List
 
 def schedule_execution(
     graph: ExecutionGraph,
@@ -203,6 +203,9 @@ def register_csv(self, table_name: str, path: str, has_header: bool):
     def register_parquet(self, table_name: str, path: str):
         self.ctx.register_parquet(table_name, path)
 
+    def register_data_lake(self, table_name: str, paths: List[str]):
+        self.ctx.register_datalake_table(table_name, paths)
+
     def sql(self, sql: str) -> pa.RecordBatch:
         # TODO we should parse sql and inspect the plan rather than
         # perform a string comparison here

src/context.rs

@@ -73,6 +73,16 @@ impl PyContext {
         Ok(())
     }
 
+    pub fn register_datalake_table(&self, name: &str, path: Vec<&str>, py: Python) -> PyResult<()> {
+        let options = ParquetReadOptions::default();
+        let listing_options = options.to_listing_options(&self.ctx.state().config());
+        wait_for_future(py, self.ctx.register_listing_table(name, path, listing_options, None, None))?;
+        Ok(())
+    }
+
+
+
+
     /// Execute SQL directly against the DataFusion context. Useful for statements
     /// such as "create view" or "drop view"
     pub fn sql(&self, sql: &str, py: Python) -> PyResult<()> {