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ARROW-6669: [Rust] [DataFusion] Implement binary expression for physical plan #5478

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ARROW-6669: [Rust] [DataFusion] Implement binary expression for physical plan #5478

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9b94cc8
Implement binary expression with support for comparison and boolean o…
andygrove Sep 23, 2019
bb82a24
use expect() instead of unwrap() when downcasting arrays
andygrove Sep 23, 2019
9ad3b7f
formatting
andygrove Sep 24, 2019
af8d298
address PR feedback
andygrove Sep 24, 2019
83bfa77
formatting
andygrove Sep 24, 2019
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207 changes: 204 additions & 3 deletions rust/datafusion/src/execution/physical_plan/expressions.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -23,16 +23,18 @@ use std::sync::Arc;

use crate::error::{ExecutionError, Result};
use crate::execution::physical_plan::{Accumulator, AggregateExpr, PhysicalExpr};
use crate::logicalplan::ScalarValue;
use crate::logicalplan::{Operator, ScalarValue};
use arrow::array::{
ArrayRef, Float32Array, Float64Array, Int16Array, Int32Array, Int64Array, Int8Array,
UInt16Array, UInt32Array, UInt64Array, UInt8Array,
ArrayRef, BooleanArray, Float32Array, Float64Array, Int16Array, Int32Array,
Int64Array, Int8Array, UInt16Array, UInt32Array, UInt64Array, UInt8Array,
};
use arrow::array::{
Float32Builder, Float64Builder, Int16Builder, Int32Builder, Int64Builder,
Int8Builder, UInt16Builder, UInt32Builder, UInt64Builder, UInt8Builder,
};
use arrow::compute::kernels::boolean::{and, or};
use arrow::compute::kernels::cast::cast;
use arrow::compute::kernels::comparison::{eq, gt, gt_eq, lt, lt_eq, neq};
use arrow::datatypes::{DataType, Schema};
use arrow::record_batch::RecordBatch;

Expand Down Expand Up @@ -197,6 +199,140 @@ pub fn sum(expr: Arc<dyn PhysicalExpr>) -> Arc<dyn AggregateExpr> {
Arc::new(Sum::new(expr))
}

/// Invoke a compute kernel on a pair of arrays
macro_rules! compute_op {
($LEFT:expr, $RIGHT:expr, $OP:ident, $DT:ident) => {{
let ll = $LEFT
.as_any()
.downcast_ref::<$DT>()
.expect("compute_op failed to downcast array");
let rr = $RIGHT
.as_any()
.downcast_ref::<$DT>()
.expect("compute_op failed to downcast array");
Ok(Arc::new($OP(&ll, &rr)?))
}};
}

/// Invoke a compute kernel on a pair of arrays
macro_rules! comparison_op {
($LEFT:expr, $RIGHT:expr, $OP:ident) => {{
match $LEFT.data_type() {
DataType::Int8 => compute_op!($LEFT, $RIGHT, $OP, Int8Array),
DataType::Int16 => compute_op!($LEFT, $RIGHT, $OP, Int16Array),
DataType::Int32 => compute_op!($LEFT, $RIGHT, $OP, Int32Array),
DataType::Int64 => compute_op!($LEFT, $RIGHT, $OP, Int64Array),
DataType::UInt8 => compute_op!($LEFT, $RIGHT, $OP, UInt8Array),
DataType::UInt16 => compute_op!($LEFT, $RIGHT, $OP, UInt16Array),
DataType::UInt32 => compute_op!($LEFT, $RIGHT, $OP, UInt32Array),
DataType::UInt64 => compute_op!($LEFT, $RIGHT, $OP, UInt64Array),
DataType::Float32 => compute_op!($LEFT, $RIGHT, $OP, Float32Array),
DataType::Float64 => compute_op!($LEFT, $RIGHT, $OP, Float64Array),
other => Err(ExecutionError::General(format!(
"Unsupported data type {:?}",
other
))),
}
}};
}

/// Invoke a boolean kernel on a pair of arrays
macro_rules! boolean_op {
($LEFT:expr, $RIGHT:expr, $OP:ident) => {{
let ll = $LEFT
.as_any()
.downcast_ref::<BooleanArray>()
.expect("boolean_op failed to downcast array");
let rr = $RIGHT
.as_any()
.downcast_ref::<BooleanArray>()
.expect("boolean_op failed to downcast array");
Ok(Arc::new($OP(&ll, &rr)?))
}};
}
/// Binary expression
pub struct BinaryExpr {
left: Arc<dyn PhysicalExpr>,
op: Operator,
right: Arc<dyn PhysicalExpr>,
}

impl BinaryExpr {
/// Create new binary expression
pub fn new(
left: Arc<dyn PhysicalExpr>,
op: Operator,
right: Arc<dyn PhysicalExpr>,
) -> Self {
Self { left, op, right }
}
}

impl PhysicalExpr for BinaryExpr {
fn name(&self) -> String {
format!("{:?}", self.op)
}

fn data_type(&self, input_schema: &Schema) -> Result<DataType> {
self.left.data_type(input_schema)
}

fn evaluate(&self, batch: &RecordBatch) -> Result<ArrayRef> {
let left = self.left.evaluate(batch)?;
let right = self.right.evaluate(batch)?;
if left.data_type() != right.data_type() {
return Err(ExecutionError::General(format!(
"Cannot evaluate binary expression {:?} with types {:?} and {:?}",
self.op,
left.data_type(),
right.data_type()
)));
}
match &self.op {
Operator::Lt => comparison_op!(left, right, lt),
Operator::LtEq => comparison_op!(left, right, lt_eq),
Operator::Gt => comparison_op!(left, right, gt),
Operator::GtEq => comparison_op!(left, right, gt_eq),
Operator::Eq => comparison_op!(left, right, eq),
Operator::NotEq => comparison_op!(left, right, neq),
Operator::And => {
if left.data_type() == &DataType::Boolean {
boolean_op!(left, right, and)
} else {
return Err(ExecutionError::General(format!(
"Cannot evaluate binary expression {:?} with types {:?} and {:?}",
self.op,
left.data_type(),
right.data_type()
)));
}
}
Operator::Or => {
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It's a shame this has to be repeated instead of using Operator::And | Operator::Or

if left.data_type() == &DataType::Boolean {
boolean_op!(left, right, or)
} else {
return Err(ExecutionError::General(format!(
"Cannot evaluate binary expression {:?} with types {:?} and {:?}",
self.op,
left.data_type(),
right.data_type()
)));
}
}
_ => Err(ExecutionError::General("Unsupported operator".to_string())),
}
}
}

/// Create a binary expression
pub fn binary(
l: Arc<dyn PhysicalExpr>,
op: Operator,
r: Arc<dyn PhysicalExpr>,
) -> Arc<dyn PhysicalExpr> {
Arc::new(BinaryExpr::new(l, op, r))
}

/// CAST expression casts an expression to a specific data type
pub struct CastExpr {
/// The expression to cast
Expand Down Expand Up @@ -335,6 +471,71 @@ mod tests {
use arrow::array::BinaryArray;
use arrow::datatypes::*;

#[test]
fn binary_comparison() -> Result<()> {
let schema = Schema::new(vec![
Field::new("a", DataType::Int32, false),
Field::new("b", DataType::Int32, false),
]);
let a = Int32Array::from(vec![1, 2, 3, 4, 5]);
let b = Int32Array::from(vec![1, 2, 4, 8, 16]);
let batch = RecordBatch::try_new(
Arc::new(schema.clone()),
vec![Arc::new(a), Arc::new(b)],
)?;

// expression: "a < b"
let lt = binary(col(0), Operator::Lt, col(1));
let result = lt.evaluate(&batch)?;
assert_eq!(result.len(), 5);

let expected = vec![false, false, true, true, true];
let result = result
.as_any()
.downcast_ref::<BooleanArray>()
.expect("failed to downcast to BooleanArray");
for i in 0..5 {
assert_eq!(result.value(i), expected[i]);
}

Ok(())
}

#[test]
fn binary_nested() -> Result<()> {
let schema = Schema::new(vec![
Field::new("a", DataType::Int32, false),
Field::new("b", DataType::Int32, false),
]);
let a = Int32Array::from(vec![2, 4, 6, 8, 10]);
let b = Int32Array::from(vec![2, 5, 4, 8, 8]);
let batch = RecordBatch::try_new(
Arc::new(schema.clone()),
vec![Arc::new(a), Arc::new(b)],
)?;

// expression: "a < b OR a == b"
let expr = binary(
binary(col(0), Operator::Lt, col(1)),
Operator::Or,
binary(col(0), Operator::Eq, col(1)),
);
let result = expr.evaluate(&batch)?;
assert_eq!(result.len(), 5);

let expected = vec![true, true, false, true, false];
let result = result
.as_any()
.downcast_ref::<BooleanArray>()
.expect("failed to downcast to BooleanArray");
for i in 0..5 {
print!("{}", i);
assert_eq!(result.value(i), expected[i]);
}

Ok(())
}

#[test]
fn literal_i32() -> Result<()> {
// create an arbitrary record bacth
Expand Down