Fixing the streaming join example

crates/core/src/datastream.rs

@@ -113,6 +113,15 @@ impl DataStream {
         })
     }
 
+    pub fn drop_columns(self, columns: &[&str]) -> Result<Self> {
+        Ok(Self {
+            df: Arc::new(self.df.as_ref().clone().drop_columns(columns)?),
+            context: self.context.clone(),
+            shutdown_tx: self.shutdown_tx.clone(),
+            shutdown_rx: self.shutdown_rx.clone(),
+        })
+    }
+
     // Join two streams using the specified expression
     pub fn join_on(
         self,

examples/examples/stream_join.rs

@@ -17,7 +17,10 @@ async fn main() -> Result<()> {
 
     let bootstrap_servers = String::from("localhost:9092");
 
-    let ctx = Context::new()?;
+    let ctx = Context::new()?
+        .with_slatedb_backend(String::from("/tmp/checkpoints/stream-join-checkpoint-1"))
+        .await;
+
     let mut topic_builder = KafkaTopicBuilder::new(bootstrap_servers.clone());
 
     let source_topic_builder = topic_builder
@@ -29,7 +32,7 @@ async fn main() -> Result<()> {
         .clone()
         .with_topic(String::from("temperature"))
         .build_reader(ConnectionOpts::from([
-            ("auto.offset.reset".to_string(), "earliest".to_string()),
+            ("auto.offset.reset".to_string(), "latest".to_string()),
             ("group.id".to_string(), "sample_pipeline".to_string()),
         ]))
         .await?;
@@ -40,30 +43,38 @@ async fn main() -> Result<()> {
                 .clone()
                 .with_topic(String::from("humidity"))
                 .build_reader(ConnectionOpts::from([
-                    ("auto.offset.reset".to_string(), "earliest".to_string()),
+                    ("auto.offset.reset".to_string(), "latest".to_string()),
                     ("group.id".to_string(), "sample_pipeline".to_string()),
                 ]))
                 .await?,
         )
-        .await?;
+        .await?
+        .with_column("humidity_sensor", col("sensor_name"))?
+        .drop_columns(&["sensor_name"])?
+        .window(
+            vec![col("humidity_sensor")],
+            vec![avg(col("reading")).alias("avg_humidity")],
+            Duration::from_millis(1_000),
+            None,
+        )?
+        .with_column("humidity_window_start_time", col("window_start_time"))?
+        .with_column("humidity_window_end_time", col("window_end_time"))?
+        .drop_columns(&["window_start_time", "window_end_time"])?;
 
     let joined_ds = ctx
         .from_topic(temperature_topic)
         .await?
+        .window(
+            vec![col("sensor_name")],
+            vec![avg(col("reading")).alias("avg_temperature")],
+            Duration::from_millis(1_000),
+            None,
+        )?
         .join(
             humidity_ds,
             JoinType::Inner,
-            &["sensor_name"],
-            &["sensor_name"],
-            None,
-        )?
-        .window(
-            vec![],
-            vec![
-                avg(col("temperature.reading")).alias("avg_temperature"),
-                avg(col("humidity.reading")).alias("avg_humidity"),
-            ],
-            Duration::from_millis(1_000),
+            &["sensor_name", "window_start_time"],
+            &["humidity_sensor", "humidity_window_start_time"],
             None,
         )?;
 

py-denormalized/pyproject.toml

@@ -20,7 +20,7 @@ feast = ["feast"]
 [tool.maturin]
 python-source = "python"
 features = ["pyo3/extension-module"]
-module-name = "denormalized._internal"
+module-name = "denormalized._d_internal"
 
 [tool.rye]
 dev-dependencies = ["pip>=24.2", "ipython>=8.26.0", "pytest>=8.3.2"]

py-denormalized/python/denormalized/context.py

@@ -1,4 +1,4 @@
-from denormalized._internal import PyContext
+from denormalized._d_internal import PyContext
 from .data_stream import DataStream
 
 class Context:
@@ -20,4 +20,3 @@ def from_topic(self, topic: str, sample_json: str, bootstrap_servers: str) -> Da
         ds = DataStream(py_ds)
 
         return ds
-

py-denormalized/python/denormalized/data_stream.py

@@ -1,5 +1,5 @@
 import pyarrow as pa
-from denormalized._internal import PyDataStream
+from denormalized._d_internal import PyDataStream
 from denormalized.datafusion import Expr
 from denormalized.utils import to_internal_expr, to_internal_exprs
 

py-denormalized/python/denormalized/datafusion/__init__.py

@@ -36,7 +36,7 @@
 from .catalog import Catalog, Database, Table
 
 # The following imports are okay to remain as opaque to the user.
-from denormalized._internal import Config, LogicalPlan, ExecutionPlan, runtime
+from denormalized._d_internal import Config, LogicalPlan, ExecutionPlan, runtime
 
 from .record_batch import RecordBatchStream, RecordBatch
 

py-denormalized/python/denormalized/datafusion/catalog.py

@@ -19,7 +19,7 @@
 
 from __future__ import annotations
 
-import denormalized._internal as df_internal
+import denormalized._d_internal as df_internal
 
 from typing import TYPE_CHECKING
 

py-denormalized/python/denormalized/datafusion/common.py

@@ -16,7 +16,7 @@
 # under the License.
 """Common data types used throughout the DataFusion project."""
 
-from denormalized._internal import common as common_internal
+from denormalized._d_internal import common as common_internal
 from enum import Enum
 
 # TODO these should all have proper wrapper classes

py-denormalized/python/denormalized/datafusion/context.py

@@ -19,13 +19,13 @@
 
 from __future__ import annotations
 
-from denormalized._internal import SessionConfig as SessionConfigInternal
-from denormalized._internal import RuntimeConfig as RuntimeConfigInternal
-from denormalized._internal import SQLOptions as SQLOptionsInternal
-from denormalized._internal import SessionContext as SessionContextInternal
-from denormalized._internal import LogicalPlan, ExecutionPlan
+from denormalized._d_internal import SessionConfig as SessionConfigInternal
+from denormalized._d_internal import RuntimeConfig as RuntimeConfigInternal
+from denormalized._d_internal import SQLOptions as SQLOptionsInternal
+from denormalized._d_internal import SessionContext as SessionContextInternal
+from denormalized._d_internal import LogicalPlan, ExecutionPlan
 
-from denormalized._internal import AggregateUDF
+from denormalized._d_internal import AggregateUDF
 from denormalized.datafusion.catalog import Catalog, Table
 from denormalized.datafusion.dataframe import DataFrame
 from denormalized.datafusion.expr import Expr, SortExpr, sort_list_to_raw_sort_list

py-denormalized/python/denormalized/datafusion/dataframe.py

@@ -32,9 +32,9 @@
     import pathlib
     from typing import Callable
 
-from denormalized._internal import DataFrame as DataFrameInternal
+from denormalized._d_internal import DataFrame as DataFrameInternal
 from denormalized.datafusion.expr import Expr, SortExpr, sort_or_default
-from denormalized._internal import (
+from denormalized._d_internal import (
     LogicalPlan,
     ExecutionPlan,
 )

py-denormalized/python/denormalized/datafusion/expr.py

@@ -28,9 +28,9 @@
 from denormalized.datafusion.common import DataTypeMap, NullTreatment, RexType
 from typing_extensions import deprecated
 
-from denormalized._internal import LogicalPlan
-from denormalized._internal import expr as expr_internal
-from denormalized._internal import functions as functions_internal
+from denormalized._d_internal import LogicalPlan
+from denormalized._d_internal import expr as expr_internal
+from denormalized._d_internal import functions as functions_internal
 
 # The following are imported from the internal representation. We may choose to
 # give these all proper wrappers, or to simply leave as is. These were added

py-denormalized/python/denormalized/datafusion/functions.py

@@ -18,7 +18,7 @@
 
 from __future__ import annotations
 
-from denormalized._internal import functions as f
+from denormalized._d_internal import functions as f
 from denormalized.datafusion.expr import (
     CaseBuilder,
     Expr,

py-denormalized/python/denormalized/datafusion/object_store.py

@@ -16,7 +16,7 @@
 # under the License.
 """Object store functionality."""
 
-from denormalized._internal import object_store
+from denormalized._d_internal import object_store
 
 AmazonS3 = object_store.AmazonS3
 GoogleCloud = object_store.GoogleCloud

py-denormalized/python/denormalized/datafusion/record_batch.py

@@ -27,7 +27,7 @@
 
 if TYPE_CHECKING:
     import pyarrow
-    import denormalized._internal as df_internal
+    import denormalized._d_internal as df_internal
     import typing_extensions
 
 

py-denormalized/python/denormalized/datafusion/udf.py

@@ -19,7 +19,7 @@
 
 from __future__ import annotations
 
-import denormalized._internal as df_internal
+import denormalized._d_internal as df_internal
 from datafusion.expr import Expr
 from typing import Callable, TYPE_CHECKING, TypeVar
 from abc import ABCMeta, abstractmethod

py-denormalized/python/denormalized/feast_data_stream.py

@@ -2,7 +2,7 @@
 from typing import Any, TypeVar, Union, cast, get_type_hints
 
 import pyarrow as pa
-from denormalized._internal import PyDataStream
+from denormalized._d_internal import PyDataStream
 from denormalized.datafusion import Expr
 from feast import FeatureStore, Field
 from feast.data_source import PushMode

py-denormalized/python/denormalized/utils.py

@@ -1,4 +1,4 @@
-from denormalized._internal import expr as internal_exprs
+from denormalized._d_internal import expr as internal_exprs
 from denormalized.datafusion import Expr
 
 

py-denormalized/src/lib.rs

@@ -11,7 +11,7 @@ pub mod utils;
 pub(crate) struct TokioRuntime(tokio::runtime::Runtime);
 
 /// A Python module implemented in Rust.
-#[pymodule(name="_internal")]
+#[pymodule(name = "_d_internal")]
 fn _py_denormalized_internal(py: Python, m: Bound<'_, PyModule>) -> PyResult<()> {
     m.add_class::<datastream::PyDataStream>()?;
     m.add_class::<context::PyContext>()?;