feat(cubesql): Add XIRR aggregate function

rust/cubesql/cubesql/src/compile/engine/udf/extension/mod.rs

@@ -0,0 +1,3 @@
+mod xirr;
+
+pub use xirr::*;

rust/cubesql/cubesql/src/compile/engine/udf/extension/xirr.rs

@@ -0,0 +1,336 @@
+use std::sync::Arc;
+
+use datafusion::{
+    arrow::{
+        array::{ArrayRef, Date32Array, Float64Array, ListArray},
+        compute::cast,
+        datatypes::{DataType, Field, TimeUnit},
+    },
+    error::{DataFusionError, Result},
+    logical_expr::{
+        Accumulator, AccumulatorFunctionImplementation, AggregateUDF, ReturnTypeFunction,
+        Signature, StateTypeFunction, TypeSignature, Volatility,
+    },
+    scalar::ScalarValue,
+};
+
+pub const XIRR_UDAF_NAME: &str = "xirr";
+
+/// Creates a XIRR Aggregate UDF.
+///
+/// Syntax:
+/// ```sql
+/// XIRR(<payment>, <date> [, <initial_guess> [, <on_error>]])
+/// ```
+///
+/// This function calculates internal rate of return for a series of cash flows (payments)
+/// that occur at irregular intervals.
+///
+/// The function takes two arguments:
+/// - `payment` (numeric): The cash flow amount. NULL values are considered 0.
+/// - `date` (datetime): The date of the payment. Time is ignored. Must never be NULL.
+/// - (optional) `initial_guess` (numeric): An initial guess for the rate of return. Must be
+///   greater than -1.0 and consistent across all rows. If NULL or omitted, a default value
+///   of 0.1 is used.
+/// - (optional) `on_error` (numeric): A value to return if the function cannot find a solution.
+///   If omitted, the function will yield an error when it cannot find a solution. Must be
+///   consistent across all rows.
+///
+/// The function always yields an error if:
+/// - There are no rows.
+/// - The `date` argument contains a NULL value.
+/// - The `initial_guess` argument is less than or equal to -1.0, or inconsistent across all rows.
+/// - The `on_error` argument is inconsistent across all rows.
+///
+/// The function returns `on_error` value (or yields an error if omitted) if:
+/// - The function cannot find a solution after a set number of iterations.
+/// - The calculation failed due to internal division by 0.
+pub fn create_xirr_udaf() -> AggregateUDF {
+    let name = XIRR_UDAF_NAME;
+    let type_signatures = {
+        // Only types actually used by cubesql are included
+        const NUMERIC_TYPES: &[DataType] = &[DataType::Float64, DataType::Int64, DataType::Int32];
+        const DATETIME_TYPES: &[DataType] = &[
+            DataType::Date32,
+            DataType::Timestamp(TimeUnit::Nanosecond, None),
+            DataType::Timestamp(TimeUnit::Millisecond, None),
+        ];
+        let mut type_signatures = Vec::with_capacity(45);
+        for payment_type in NUMERIC_TYPES {
+            for date_type in DATETIME_TYPES {
+                // Base signatures without `initial_guess` and `on_error` arguments
+                type_signatures.push(TypeSignature::Exact(vec![
+                    payment_type.clone(),
+                    date_type.clone(),
+                ]));
+                // Signatures with `initial_guess` argument; only [`DataType::Float64`] is accepted
+                const INITIAL_GUESS_TYPE: DataType = DataType::Float64;
+                type_signatures.push(TypeSignature::Exact(vec![
+                    payment_type.clone(),
+                    date_type.clone(),
+                    INITIAL_GUESS_TYPE,
+                ]));
+                // Signatures with `initial_guess` and `on_error` arguments
+                for on_error_type in NUMERIC_TYPES {
+                    type_signatures.push(TypeSignature::Exact(vec![
+                        payment_type.clone(),
+                        date_type.clone(),
+                        INITIAL_GUESS_TYPE,
+                        on_error_type.clone(),
+                    ]));
+                }
+            }
+        }
+        type_signatures
+    };
+    let signature = Signature::one_of(
+        type_signatures,
+        Volatility::Volatile, // due to the usage of [`f64::powf`]
+    );
+    let return_type: ReturnTypeFunction = Arc::new(|_| Ok(Arc::new(DataType::Float64)));
+    let accumulator: AccumulatorFunctionImplementation =
+        Arc::new(|| Ok(Box::new(XirrAccumulator::new())));
+    let state_type: StateTypeFunction = Arc::new(|_| {
+        Ok(Arc::new(vec![
+            DataType::List(Box::new(Field::new("item", DataType::Float64, true))),
+            DataType::List(Box::new(Field::new("item", DataType::Date32, true))),
+            DataType::List(Box::new(Field::new("item", DataType::Float64, true))),
+            DataType::List(Box::new(Field::new("item", DataType::Float64, true))),
+        ]))
+    });
+    AggregateUDF::new(name, &signature, &return_type, &accumulator, &state_type)
+}
+
+#[derive(Debug)]
+struct XirrAccumulator {
+    /// Pairs of (payment, date).
+    pairs: Vec<(f64, i32)>,
+    initial_guess: ValueState<f64>,
+    on_error: ValueState<f64>,
+}
+
+impl XirrAccumulator {
+    fn new() -> Self {
+        XirrAccumulator {
+            pairs: vec![],
+            initial_guess: ValueState::Unset,
+            on_error: ValueState::Unset,
+        }
+    }
+
+    fn add_pair(&mut self, payment: Option<f64>, date: Option<i32>) -> Result<()> {
+        let Some(date) = date else {
+            return Err(DataFusionError::Execution(
+                "One or more values for the `date` argument passed to XIRR is null".to_string(),
+            ));
+        };
+        // NULL payment value is treated as 0
+        let payment = payment.unwrap_or(0.0);
+        self.pairs.push((payment, date));
+        Ok(())
+    }
+
+    fn set_initial_guess(&mut self, initial_guess: Option<f64>) -> Result<()> {
+        let ValueState::Set(current_initial_guess) = self.initial_guess else {
+            self.initial_guess = ValueState::Set(initial_guess);
+            return Ok(());
+        };
+        if current_initial_guess != initial_guess {
+            return Err(DataFusionError::Execution(
+                "The `initial_guess` argument passed to XIRR is inconsistent".to_string(),
+            ));
+        }
+        Ok(())
+    }
+
+    fn set_on_error(&mut self, on_error: Option<f64>) -> Result<()> {
+        let ValueState::Set(current_on_error) = self.on_error else {
+            self.on_error = ValueState::Set(on_error);
+            return Ok(());
+        };
+        if current_on_error != on_error {
+            return Err(DataFusionError::Execution(
+                "The `on_error` argument passed to XIRR is inconsistent".to_string(),
+            ));
+        }
+        Ok(())
+    }
+
+    fn yield_no_solution(&self) -> Result<ScalarValue> {
+        match self.on_error {
+            ValueState::Unset => Err(DataFusionError::Execution(
+                "The XIRR function couldn't find a solution".to_string(),
+            )),
+            ValueState::Set(on_error) => Ok(ScalarValue::Float64(on_error)),
+        }
+    }
+}
+
+impl Accumulator for XirrAccumulator {
+    fn state(&self) -> Result<Vec<ScalarValue>> {
+        let (payments, dates): (Vec<_>, Vec<_>) = self
+            .pairs
+            .iter()
+            .map(|(payment, date)| {
+                let payment = ScalarValue::Float64(Some(*payment));
+                let date = ScalarValue::Date32(Some(*date));
+                (payment, date)
+            })
+            .unzip();
+        let initial_guess = match self.initial_guess {
+            ValueState::Unset => vec![],
+            ValueState::Set(initial_guess) => vec![ScalarValue::Float64(initial_guess)],
+        };
+        let on_error = match self.on_error {
+            ValueState::Unset => vec![],
+            ValueState::Set(on_error) => vec![ScalarValue::Float64(on_error)],
+        };
+        Ok(vec![
+            ScalarValue::List(Some(Box::new(payments)), Box::new(DataType::Float64)),
+            ScalarValue::List(Some(Box::new(dates)), Box::new(DataType::Date32)),
+            ScalarValue::List(Some(Box::new(initial_guess)), Box::new(DataType::Float64)),
+            ScalarValue::List(Some(Box::new(on_error)), Box::new(DataType::Float64)),
+        ])
+    }
+
+    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+        let payments = cast(&values[0], &DataType::Float64)?;
+        let payments = payments.as_any().downcast_ref::<Float64Array>().unwrap();
+        let dates = cast(&values[1], &DataType::Date32)?;
+        let dates = dates.as_any().downcast_ref::<Date32Array>().unwrap();
+        for (payment, date) in payments.into_iter().zip(dates) {
+            self.add_pair(payment, date)?;
+        }
+        let values_len = values.len();
+        if values_len < 3 {
+            return Ok(());
+        }
+        let initial_guesses = values[2].as_any().downcast_ref::<Float64Array>().unwrap();
+        for initial_guess in initial_guesses {
+            self.set_initial_guess(initial_guess)?;
+        }
+        if values_len < 4 {
+            return Ok(());
+        }
+        let on_errors = cast(&values[3], &DataType::Float64)?;
+        let on_errors = on_errors.as_any().downcast_ref::<Float64Array>().unwrap();
+        for on_error in on_errors {
+            self.set_on_error(on_error)?;
+        }
+        Ok(())
+    }
+
+    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+        let payments = states[0]
+            .as_any()
+            .downcast_ref::<ListArray>()
+            .unwrap()
+            .values();
+        let payments = payments.as_any().downcast_ref::<Float64Array>().unwrap();
+        let dates = states[1]
+            .as_any()
+            .downcast_ref::<ListArray>()
+            .unwrap()
+            .values();
+        let dates = dates.as_any().downcast_ref::<Date32Array>().unwrap();
+        for (payment, date) in payments.into_iter().zip(dates) {
+            self.add_pair(payment, date)?;
+        }
+        let states_len = states.len();
+        if states_len < 3 {
+            return Ok(());
+        }
+        let initial_guesses = states[2]
+            .as_any()
+            .downcast_ref::<ListArray>()
+            .unwrap()
+            .values();
+        let initial_guesses = initial_guesses
+            .as_any()
+            .downcast_ref::<Float64Array>()
+            .unwrap();
+        for initial_guess in initial_guesses {
+            self.set_initial_guess(initial_guess)?;
+        }
+        if states_len < 4 {
+            return Ok(());
+        }
+        let on_errors = states[3]
+            .as_any()
+            .downcast_ref::<ListArray>()
+            .unwrap()
+            .values();
+        let on_errors = on_errors.as_any().downcast_ref::<Float64Array>().unwrap();
+        for on_error in on_errors {
+            self.set_on_error(on_error)?;
+        }
+        Ok(())
+    }
+
+    fn evaluate(&self) -> Result<ScalarValue> {
+        const MAX_ITERATIONS: usize = 100;
+        const TOLERANCE: f64 = 1e-6;
+        const DEFAULT_INITIAL_GUESS: f64 = 0.1;
+        let Some(min_date) = self.pairs.iter().map(|(_, date)| *date).min() else {
+            return Err(DataFusionError::Execution(
+                "A result for XIRR couldn't be determined because the arguments are empty"
+                    .to_string(),
+            ));
+        };
+        let pairs = self
+            .pairs
+            .iter()
+            .map(|(payment, date)| {
+                let year_difference = (*date - min_date) as f64 / 365.0;
+                (*payment, year_difference)
+            })
+            .collect::<Vec<_>>();
+        let mut rate_of_return = self
+            .initial_guess
+            .to_value()
+            .unwrap_or(DEFAULT_INITIAL_GUESS);
+        if rate_of_return <= -1.0 {
+            return Err(DataFusionError::Execution(
+                "The `initial_guess` argument passed to the XIRR function must be greater than -1"
+                    .to_string(),
+            ));
+        }
+        for _ in 0..MAX_ITERATIONS {
+            let mut net_present_value = 0.0;
+            let mut derivative_value = 0.0;
+            for (payment, year_difference) in &pairs {
+                if *payment == 0.0 {
+                    continue;
+                }
+                let rate_positive = 1.0 + rate_of_return;
+                let denominator = rate_positive.powf(*year_difference);
+                net_present_value += *payment / denominator;
+                derivative_value -= *year_difference * *payment / denominator / rate_positive;
+            }
+            if net_present_value.abs() < TOLERANCE {
+                return Ok(ScalarValue::Float64(Some(rate_of_return)));
+            }
+            let rate_reduction = net_present_value / derivative_value;
+            if rate_reduction.is_nan() {
+                return self.yield_no_solution();
+            }
+            rate_of_return -= rate_reduction;
+        }
+        self.yield_no_solution()
+    }
+}
+
+#[derive(Debug)]
+enum ValueState<T: Copy> {
+    Unset,
+    Set(Option<T>),
+}
+
+impl<T: Copy> ValueState<T> {
+    fn to_value(&self) -> Option<T> {
+        match self {
+            ValueState::Unset => None,
+            ValueState::Set(value) => *value,
+        }
+    }
+}

rust/cubesql/cubesql/src/compile/engine/udf/mod.rs

@@ -1,8 +1,10 @@
 mod common;
+mod extension;
 mod pg_catalog;
 mod redshift;
 mod utils;
 
 pub use common::*;
+pub use extension::*;
 pub use pg_catalog::*;
 pub use redshift::*;

rust/cubesql/cubesql/src/compile/query_engine.rs

@@ -516,6 +516,7 @@ impl QueryEngine for SqlQueryEngine {
         // udaf
         ctx.register_udaf(create_measure_udaf());
         ctx.register_udaf(create_patch_measure_udaf());
+        ctx.register_udaf(create_xirr_udaf());
 
         // udtf
         ctx.register_udtf(create_generate_series_udtf());

rust/cubesql/cubesql/src/compile/test/snapshots/cubesql__compile__test__test_udfs__extension_udf_xirr.snap

@@ -0,0 +1,9 @@
+---
+source: cubesql/src/compile/test/test_udfs.rs
+expression: "execute_query(r#\"\n            SELECT LEFT(XIRR(payment, date)::text, 10) AS xirr\n            FROM (\n                SELECT '2014-01-01'::date AS date, -10000.0 AS payment\n                UNION ALL\n                SELECT '2014-03-01'::date AS date, 2750.0 AS payment\n                UNION ALL\n                SELECT '2014-10-30'::date AS date, 4250.0 AS payment\n                UNION ALL\n                SELECT '2015-02-15'::date AS date, 3250.0 AS payment\n                UNION ALL\n                SELECT '2015-04-01'::date AS date, 2750.0 AS payment\n            ) AS \"t\"\n            \"#.to_string(),\nDatabaseProtocol::PostgreSQL).await?"
+---
++------------+
+| xirr       |
++------------+
+| 0.37485859 |
++------------+