refactor: Organize window_bounds the same as selector functions (#594)

* refactor: Organize window_bounds the same as selector functions

* fix: add missing file

query/src/exec.rs

@@ -8,9 +8,6 @@ mod schema_pivot;
 pub mod seriesset;
 pub mod stringset;
 
-// Export function to make window bounds without exposing its implementation
-pub use planning::make_window_bound_expr;
-
 use std::sync::Arc;
 
 use arrow_deps::{

query/src/exec/planning.rs

@@ -4,17 +4,12 @@
 use std::sync::Arc;
 
 use arrow_deps::{
-    arrow::{
-        array::{ArrayRef, Int64Array, Int64Builder},
-        datatypes::DataType,
-        record_batch::RecordBatch,
-    },
+    arrow::record_batch::RecordBatch,
     datafusion::{
         execution::context::{ExecutionContextState, QueryPlanner},
-        logical_plan::{Expr, LogicalPlan, UserDefinedLogicalNode},
+        logical_plan::{LogicalPlan, UserDefinedLogicalNode},
         physical_plan::{
             collect,
-            functions::ScalarFunctionImplementation,
             merge::MergeExec,
             planner::{DefaultPhysicalPlanner, ExtensionPlanner},
             ExecutionPlan, PhysicalPlanner, SendableRecordBatchStream,
@@ -24,8 +19,6 @@ use arrow_deps::{
 };
 
 use crate::exec::schema_pivot::{SchemaPivotExec, SchemaPivotNode};
-use crate::group_by::WindowDuration;
-use crate::window;
 
 use tracing::debug;
 
@@ -147,114 +140,3 @@ impl IOxExecutionContext {
         }
     }
 }
-
-/// This is the implementation of the `window_bounds` user defined
-/// function used in IOx to compute window boundaries when doing
-/// grouping by windows.
-fn window_bounds(
-    args: &[ArrayRef],
-    every: &WindowDuration,
-    offset: &WindowDuration,
-) -> Result<ArrayRef> {
-    // Note:  At the time of writing, DataFusion creates arrays of constants for
-    // constant arguments (which 4 of 5 arguments to window bounds are). We
-    // should eventually contribute some way back upstream to make DataFusion
-    // pass 4 constants rather than 4 arrays of constants.
-
-    // There are any number of ways this function could also be further
-    // optimized, which we leave as an exercise to our future selves
-
-    // `args` and output are dynamically-typed Arrow arrays, which means that we
-    // need to:
-    //
-    // 1. cast the values to the type we want
-    // 2. perform the window_bounds calculation for every element in the
-    //     timestamp array
-    // 3. construct the resulting array
-
-    // this is guaranteed by DataFusion based on the function's signature.
-    assert_eq!(args.len(), 1);
-
-    let time = &args[0]
-        .as_any()
-        .downcast_ref::<Int64Array>()
-        .expect("cast of time failed");
-
-    // Note: the Go code uses the `Stop` field of the `GetEarliestBounds` call as
-    // the window boundary https://github.com/influxdata/influxdb/blob/master/storage/reads/array_cursor.gen.go#L546
-
-    // Note window doesn't use the period argument
-    let period = window::Duration::from_nsecs(0);
-    let window = window::Window::new(every.into(), period, offset.into());
-
-    // calculate the output times, one at a time, one element at a time
-    let mut builder = Int64Builder::new(time.len());
-    time.iter().try_for_each(|ts| match ts {
-        Some(ts) => {
-            let bounds = window.get_earliest_bounds(ts);
-            builder.append_value(bounds.stop)
-        }
-        None => builder.append_null(),
-    })?;
-
-    Ok(Arc::new(builder.finish()))
-}
-
-/// Create a DataFusion `Expr` that invokes `window_bounds` with the
-/// appropriate every and offset arguments at runtime
-pub fn make_window_bound_expr(
-    time_arg: Expr,
-    every: &WindowDuration,
-    offset: &WindowDuration,
-) -> Expr {
-    // Bind a copy of the arguments in a closure
-    let every = every.clone();
-    let offset = offset.clone();
-    let func_ptr: ScalarFunctionImplementation =
-        Arc::new(move |args| window_bounds(args, &every, &offset));
-
-    let udf = create_udf(
-        "window_bounds",
-        vec![DataType::Int64],     // argument types
-        Arc::new(DataType::Int64), // return type
-        func_ptr,
-    );
-
-    udf.call(vec![time_arg])
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-
-    #[test]
-    fn test_window_bounds() {
-        let input: ArrayRef = Arc::new(Int64Array::from(vec![
-            Some(100),
-            None,
-            Some(200),
-            Some(300),
-            Some(400),
-        ]));
-
-        let every = WindowDuration::from_nanoseconds(200);
-        let offset = WindowDuration::from_nanoseconds(50);
-
-        let bounds_array =
-            window_bounds(&[input], &every, &offset).expect("window_bounds executed correctly");
-
-        let expected_array: ArrayRef = Arc::new(Int64Array::from(vec![
-            Some(250),
-            None,
-            Some(250),
-            Some(450),
-            Some(450),
-        ]));
-
-        assert_eq!(
-            &expected_array, &bounds_array,
-            "Expected:\n{:?}\nActual:\n{:?}",
-            expected_array, bounds_array,
-        );
-    }
-}

query/src/func.rs

@@ -1,2 +1,3 @@
 //! Special IOx functions used in DataFusion plans
 pub mod selectors;
+pub mod window;

query/src/func/window.rs

@@ -0,0 +1,131 @@
+mod internal;
+
+pub use internal::{Duration, Window};
+
+use std::sync::Arc;
+
+use arrow_deps::{
+    arrow::{
+        array::{ArrayRef, Int64Array, Int64Builder},
+        datatypes::DataType,
+    },
+    datafusion::{
+        logical_plan::Expr, physical_plan::functions::ScalarFunctionImplementation, prelude::*,
+    },
+};
+
+use crate::group_by::WindowDuration;
+
+// Reuse DataFusion error and Result types for this module
+pub use arrow_deps::datafusion::error::{DataFusionError as Error, Result};
+
+/// This is the implementation of the `window_bounds` user defined
+/// function used in IOx to compute window boundaries when doing
+/// grouping by windows.
+fn window_bounds(
+    args: &[ArrayRef],
+    every: &WindowDuration,
+    offset: &WindowDuration,
+) -> Result<ArrayRef> {
+    // Note:  At the time of writing, DataFusion creates arrays of constants for
+    // constant arguments (which 4 of 5 arguments to window bounds are). We
+    // should eventually contribute some way back upstream to make DataFusion
+    // pass 4 constants rather than 4 arrays of constants.
+
+    // There are any number of ways this function could also be further
+    // optimized, which we leave as an exercise to our future selves
+
+    // `args` and output are dynamically-typed Arrow arrays, which means that we
+    // need to:
+    //
+    // 1. cast the values to the type we want
+    // 2. perform the window_bounds calculation for every element in the
+    //     timestamp array
+    // 3. construct the resulting array
+
+    // this is guaranteed by DataFusion based on the function's signature.
+    assert_eq!(args.len(), 1);
+
+    let time = &args[0]
+        .as_any()
+        .downcast_ref::<Int64Array>()
+        .expect("cast of time failed");
+
+    // Note: the Go code uses the `Stop` field of the `GetEarliestBounds` call as
+    // the window boundary https://github.com/influxdata/influxdb/blob/master/storage/reads/array_cursor.gen.go#L546
+
+    // Note window doesn't use the period argument
+    let period = internal::Duration::from_nsecs(0);
+    let window = internal::Window::new(every.into(), period, offset.into());
+
+    // calculate the output times, one at a time, one element at a time
+    let mut builder = Int64Builder::new(time.len());
+    time.iter().try_for_each(|ts| match ts {
+        Some(ts) => {
+            let bounds = window.get_earliest_bounds(ts);
+            builder.append_value(bounds.stop)
+        }
+        None => builder.append_null(),
+    })?;
+
+    Ok(Arc::new(builder.finish()))
+}
+
+/// Create a DataFusion `Expr` that invokes `window_bounds` with the
+/// appropriate every and offset arguments at runtime
+pub fn make_window_bound_expr(
+    time_arg: Expr,
+    every: &WindowDuration,
+    offset: &WindowDuration,
+) -> Expr {
+    // Bind a copy of the arguments in a closure
+    let every = every.clone();
+    let offset = offset.clone();
+    let func_ptr: ScalarFunctionImplementation =
+        Arc::new(move |args| window_bounds(args, &every, &offset));
+
+    let udf = create_udf(
+        "window_bounds",
+        vec![DataType::Int64],     // argument types
+        Arc::new(DataType::Int64), // return type
+        func_ptr,
+    );
+
+    udf.call(vec![time_arg])
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_window_bounds() {
+        let input: ArrayRef = Arc::new(Int64Array::from(vec![
+            Some(100),
+            None,
+            Some(200),
+            Some(300),
+            Some(400),
+        ]));
+
+        let every = WindowDuration::from_nanoseconds(200);
+        let offset = WindowDuration::from_nanoseconds(50);
+
+        let bounds_array =
+            window_bounds(&[input], &every, &offset).expect("window_bounds executed correctly");
+
+        let expected_array: ArrayRef = Arc::new(Int64Array::from(vec![
+            Some(250),
+            None,
+            Some(250),
+            Some(450),
+            Some(450),
+        ]));
+
+        assert_eq!(
+            &expected_array, &bounds_array,
+            "Expected:\n{:?}\nActual:\n{:?}",
+            expected_array, bounds_array,
+        );
+    }
+}

query/src/group_by.rs

@@ -2,10 +2,11 @@
 //! and Aggregate functions in IOx, designed to be compatible with
 //! InfluxDB classic
 
-use crate::window;
 use arrow_deps::datafusion::logical_plan::Expr;
 use snafu::Snafu;
 
+use crate::func::window;
+
 #[derive(Debug, Snafu)]
 pub enum Error {
     #[snafu(display(

query/src/lib.rs

@@ -19,7 +19,6 @@ pub mod group_by;
 pub mod id;
 pub mod predicate;
 pub mod util;
-pub mod window;
 
 use self::group_by::GroupByAndAggregate;
 use self::predicate::{Predicate, TimestampRange};

write_buffer/src/table.rs

@@ -1,7 +1,9 @@
 use generated_types::wal as wb;
-use query::exec::make_window_bound_expr;
-use query::exec::{make_schema_pivot, SeriesSetPlan};
-use query::group_by::{Aggregate, WindowDuration};
+use query::{
+    exec::{make_schema_pivot, SeriesSetPlan},
+    func::window::make_window_bound_expr,
+    group_by::{Aggregate, WindowDuration},
+};
 use tracing::debug;
 
 use std::{collections::BTreeSet, collections::HashMap, sync::Arc};