Add Interruptible Query Execution in Jupyter via KeyboardInterrupt Support

python/tests/test_dataframe.py

@@ -14,9 +14,12 @@
 # KIND, either express or implied.  See the License for the
 # specific language governing permissions and limitations
 # under the License.
+import ctypes
 import datetime
 import os
 import re
+import threading
+import time
 from typing import Any
 
 import pyarrow as pa
@@ -2060,3 +2063,121 @@ def test_fill_null_all_null_column(ctx):
     # Check that all nulls were filled
     result = filled_df.collect()[0]
     assert result.column(1).to_pylist() == ["filled", "filled", "filled"]
+
+
+def test_collect_interrupted():
+    """Test that a long-running query can be interrupted with Ctrl-C.
+
+    This test simulates a Ctrl-C keyboard interrupt by raising a KeyboardInterrupt
+    exception in the main thread during a long-running query execution.
+    """
+    # Create a context and a DataFrame with a query that will run for a while
+    ctx = SessionContext()
+
+    # Create a recursive computation that will run for some time
+    batches = []
+    for i in range(10):
+        batch = pa.RecordBatch.from_arrays(
+            [
+                pa.array(list(range(i * 1000, (i + 1) * 1000))),
+                pa.array([f"value_{j}" for j in range(i * 1000, (i + 1) * 1000)]),
+            ],
+            names=["a", "b"],
+        )
+        batches.append(batch)
+
+    # Register tables
+    ctx.register_record_batches("t1", [batches])
+    ctx.register_record_batches("t2", [batches])
+
+    # Create a large join operation that will take time to process
+    df = ctx.sql("""
+        WITH t1_expanded AS (
+            SELECT
+                a,
+                b,
+                CAST(a AS DOUBLE) / 1.5 AS c,
+                CAST(a AS DOUBLE) * CAST(a AS DOUBLE) AS d
+            FROM t1
+            CROSS JOIN (SELECT 1 AS dummy FROM t1 LIMIT 5)
+        ),
+        t2_expanded AS (
+            SELECT
+                a,
+                b,
+                CAST(a AS DOUBLE) * 2.5 AS e,
+                CAST(a AS DOUBLE) * CAST(a AS DOUBLE) * CAST(a AS DOUBLE) AS f
+            FROM t2
+            CROSS JOIN (SELECT 1 AS dummy FROM t2 LIMIT 5)
+        )
+        SELECT
+            t1.a, t1.b, t1.c, t1.d,
+            t2.a AS a2, t2.b AS b2, t2.e, t2.f
+        FROM t1_expanded t1
+        JOIN t2_expanded t2 ON t1.a % 100 = t2.a % 100
+        WHERE t1.a > 100 AND t2.a > 100
+    """)
+
+    # Flag to track if the query was interrupted
+    interrupted = False
+    interrupt_error = None
+    main_thread = threading.main_thread()
+
+    # Shared flag to indicate query execution has started
+    query_started = threading.Event()
+    max_wait_time = 5.0  # Maximum wait time in seconds
+
+    # This function will be run in a separate thread and will raise
+    # KeyboardInterrupt in the main thread
+    def trigger_interrupt():
+        """Poll for query start, then raise KeyboardInterrupt in the main thread"""
+        # Poll for query to start with small sleep intervals
+        start_time = time.time()
+        while not query_started.is_set():
+            time.sleep(0.1)  # Small sleep between checks
+            if time.time() - start_time > max_wait_time:
+                msg = f"Query did not start within {max_wait_time} seconds"
+                raise RuntimeError(msg)
+
+        # Check if thread ID is available
+        thread_id = main_thread.ident
+        if thread_id is None:
+            msg = "Cannot get main thread ID"
+            raise RuntimeError(msg)
+
+        # Use ctypes to raise exception in main thread
+        exception = ctypes.py_object(KeyboardInterrupt)
+        res = ctypes.pythonapi.PyThreadState_SetAsyncExc(
+            ctypes.c_long(thread_id), exception
+        )
+        if res != 1:
+            # If res is 0, the thread ID was invalid
+            # If res > 1, we modified multiple threads
+            ctypes.pythonapi.PyThreadState_SetAsyncExc(
+                ctypes.c_long(thread_id), ctypes.py_object(0)
+            )
+            msg = "Failed to raise KeyboardInterrupt in main thread"
+            raise RuntimeError(msg)
+
+    # Start a thread to trigger the interrupt
+    interrupt_thread = threading.Thread(target=trigger_interrupt)
+    # we mark as daemon so the test process can exit even if this thread doesn't finish
+    interrupt_thread.daemon = True
+    interrupt_thread.start()
+
+    # Execute the query and expect it to be interrupted
+    try:
+        # Signal that we're about to start the query
+        query_started.set()
+        df.collect()
+    except KeyboardInterrupt:
+        interrupted = True
+    except Exception as e:
+        interrupt_error = e
+
+    # Assert that the query was interrupted properly
+    if not interrupted:
+        pytest.fail(f"Query was not interrupted; got error: {interrupt_error}")
+
+    # Make sure the interrupt thread has finished
+    interrupt_thread.join(timeout=1.0)

src/catalog.rs

@@ -97,7 +97,7 @@ impl PyDatabase {
     }
 
     fn table(&self, name: &str, py: Python) -> PyDataFusionResult<PyTable> {
-        if let Some(table) = wait_for_future(py, self.database.table(name))? {
+        if let Some(table) = wait_for_future(py, self.database.table(name))?? {
             Ok(PyTable::new(table))
         } else {
             Err(PyDataFusionError::Common(format!(

src/context.rs

@@ -34,7 +34,7 @@ use pyo3::prelude::*;
 use crate::catalog::{PyCatalog, PyTable};
 use crate::dataframe::PyDataFrame;
 use crate::dataset::Dataset;
-use crate::errors::{py_datafusion_err, PyDataFusionResult};
+use crate::errors::{py_datafusion_err, to_datafusion_err, PyDataFusionResult};
 use crate::expr::sort_expr::PySortExpr;
 use crate::physical_plan::PyExecutionPlan;
 use crate::record_batch::PyRecordBatchStream;
@@ -375,7 +375,7 @@ impl PySessionContext {
             None => {
                 let state = self.ctx.state();
                 let schema = options.infer_schema(&state, &table_path);
-                wait_for_future(py, schema)?
+                wait_for_future(py, schema)??
             }
         };
         let config = ListingTableConfig::new(table_path)
@@ -400,7 +400,7 @@ impl PySessionContext {
     /// Returns a PyDataFrame whose plan corresponds to the SQL statement.
     pub fn sql(&mut self, query: &str, py: Python) -> PyDataFusionResult<PyDataFrame> {
         let result = self.ctx.sql(query);
-        let df = wait_for_future(py, result)?;
+        let df = wait_for_future(py, result)??;
         Ok(PyDataFrame::new(df))
     }
 
@@ -417,7 +417,7 @@ impl PySessionContext {
             SQLOptions::new()
         };
         let result = self.ctx.sql_with_options(query, options);
-        let df = wait_for_future(py, result)?;
+        let df = wait_for_future(py, result)??;
         Ok(PyDataFrame::new(df))
     }
 
@@ -451,7 +451,7 @@ impl PySessionContext {
 
         self.ctx.register_table(&*table_name, Arc::new(table))?;
 
-        let table = wait_for_future(py, self._table(&table_name))?;
+        let table = wait_for_future(py, self._table(&table_name))??;
 
         let df = PyDataFrame::new(table);
         Ok(df)
@@ -650,7 +650,7 @@ impl PySessionContext {
             .collect();
 
         let result = self.ctx.register_parquet(name, path, options);
-        wait_for_future(py, result)?;
+        wait_for_future(py, result)??;
         Ok(())
     }
 
@@ -693,11 +693,11 @@ impl PySessionContext {
         if path.is_instance_of::<PyList>() {
             let paths = path.extract::<Vec<String>>()?;
             let result = self.register_csv_from_multiple_paths(name, paths, options);
-            wait_for_future(py, result)?;
+            wait_for_future(py, result)??;
         } else {
             let path = path.extract::<String>()?;
             let result = self.ctx.register_csv(name, &path, options);
-            wait_for_future(py, result)?;
+            wait_for_future(py, result)??;
         }
 
         Ok(())
@@ -734,7 +734,7 @@ impl PySessionContext {
         options.schema = schema.as_ref().map(|x| &x.0);
 
         let result = self.ctx.register_json(name, path, options);
-        wait_for_future(py, result)?;
+        wait_for_future(py, result)??;
 
         Ok(())
     }
@@ -764,7 +764,7 @@ impl PySessionContext {
         options.schema = schema.as_ref().map(|x| &x.0);
 
         let result = self.ctx.register_avro(name, path, options);
-        wait_for_future(py, result)?;
+        wait_for_future(py, result)??;
 
         Ok(())
     }
@@ -825,9 +825,19 @@ impl PySessionContext {
     }
 
     pub fn table(&self, name: &str, py: Python) -> PyResult<PyDataFrame> {
-        let x = wait_for_future(py, self.ctx.table(name))
+        let res = wait_for_future(py, self.ctx.table(name))
             .map_err(|e| PyKeyError::new_err(e.to_string()))?;
-        Ok(PyDataFrame::new(x))
+        match res {
+            Ok(df) => Ok(PyDataFrame::new(df)),
+            Err(e) => {
+                if let datafusion::error::DataFusionError::Plan(msg) = &e {
+                    if msg.contains("No table named") {
+                        return Err(PyKeyError::new_err(msg.to_string()));
+                    }
+                }
+                Err(py_datafusion_err(e))
+            }
+        }
     }
 
     pub fn table_exist(&self, name: &str) -> PyDataFusionResult<bool> {
@@ -865,10 +875,10 @@ impl PySessionContext {
         let df = if let Some(schema) = schema {
             options.schema = Some(&schema.0);
             let result = self.ctx.read_json(path, options);
-            wait_for_future(py, result)?
+            wait_for_future(py, result)??
         } else {
             let result = self.ctx.read_json(path, options);
-            wait_for_future(py, result)?
+            wait_for_future(py, result)??
         };
         Ok(PyDataFrame::new(df))
     }
@@ -915,12 +925,12 @@ impl PySessionContext {
             let paths = path.extract::<Vec<String>>()?;
             let paths = paths.iter().map(|p| p as &str).collect::<Vec<&str>>();
             let result = self.ctx.read_csv(paths, options);
-            let df = PyDataFrame::new(wait_for_future(py, result)?);
+            let df = PyDataFrame::new(wait_for_future(py, result)??);
             Ok(df)
         } else {
             let path = path.extract::<String>()?;
             let result = self.ctx.read_csv(path, options);
-            let df = PyDataFrame::new(wait_for_future(py, result)?);
+            let df = PyDataFrame::new(wait_for_future(py, result)??);
             Ok(df)
         }
     }
@@ -958,7 +968,7 @@ impl PySessionContext {
             .collect();
 
         let result = self.ctx.read_parquet(path, options);
-        let df = PyDataFrame::new(wait_for_future(py, result)?);
+        let df = PyDataFrame::new(wait_for_future(py, result)??);
         Ok(df)
     }
 
@@ -978,10 +988,10 @@ impl PySessionContext {
         let df = if let Some(schema) = schema {
             options.schema = Some(&schema.0);
             let read_future = self.ctx.read_avro(path, options);
-            wait_for_future(py, read_future)?
+            wait_for_future(py, read_future)??
         } else {
             let read_future = self.ctx.read_avro(path, options);
-            wait_for_future(py, read_future)?
+            wait_for_future(py, read_future)??
         };
         Ok(PyDataFrame::new(df))
     }
@@ -1021,8 +1031,8 @@ impl PySessionContext {
         let plan = plan.plan.clone();
         let fut: JoinHandle<datafusion::common::Result<SendableRecordBatchStream>> =
             rt.spawn(async move { plan.execute(part, Arc::new(ctx)) });
-        let stream = wait_for_future(py, fut).map_err(py_datafusion_err)?;
-        Ok(PyRecordBatchStream::new(stream?))
+        let stream = wait_for_future(py, async { fut.await.map_err(to_datafusion_err) })???;
+        Ok(PyRecordBatchStream::new(stream))
     }
 }