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Posted to github@arrow.apache.org by GitBox <gi...@apache.org> on 2022/05/17 20:49:25 UTC
[GitHub] [arrow-datafusion] ovr commented on a diff in pull request #2549: feat: Initial support for AnyExpression
ovr commented on code in PR #2549:
URL: https://github.com/apache/arrow-datafusion/pull/2549#discussion_r875250090
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datafusion/physical-expr/src/expressions/any.rs:
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@@ -0,0 +1,570 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! Any expression
+
+use std::any::Any;
+use std::sync::Arc;
+
+use arrow::array::{
+ BooleanArray, Int16Array, Int32Array, Int64Array, Int8Array, ListArray,
+ PrimitiveArray, UInt16Array, UInt32Array, UInt64Array, UInt8Array,
+};
+use arrow::datatypes::ArrowPrimitiveType;
+use arrow::{
+ datatypes::{DataType, Schema},
+ record_batch::RecordBatch,
+};
+
+use crate::expressions::try_cast;
+use crate::PhysicalExpr;
+use arrow::array::*;
+
+use datafusion_common::{DataFusionError, Result};
+use datafusion_expr::{ColumnarValue, Operator};
+
+macro_rules! compare_op_scalar {
+ ($LEFT: expr, $LIST_VALUES:expr, $OP:expr, $LIST_VALUES_TYPE:ty, $LIST_FROM_SCALAR: expr) => {{
+ let mut builder = BooleanBuilder::new($LEFT.len());
+
+ if $LIST_FROM_SCALAR {
+ for i in 0..$LEFT.len() {
+ if $LEFT.is_null(i) {
+ builder.append_null()?;
+ } else {
+ if $LIST_VALUES.is_null(0) {
+ builder.append_null()?;
+ } else {
+ builder.append_value($OP(
+ $LEFT.value(i),
+ $LIST_VALUES
+ .value(0)
+ .as_any()
+ .downcast_ref::<$LIST_VALUES_TYPE>()
+ .unwrap(),
+ ))?;
+ }
+ }
+ }
+ } else {
+ for i in 0..$LEFT.len() {
+ if $LEFT.is_null(i) {
+ builder.append_null()?;
+ } else {
+ if $LIST_VALUES.is_null(i) {
+ builder.append_null()?;
+ } else {
+ builder.append_value($OP(
+ $LEFT.value(i),
+ $LIST_VALUES
+ .value(i)
+ .as_any()
+ .downcast_ref::<$LIST_VALUES_TYPE>()
+ .unwrap(),
+ ))?;
+ }
+ }
+ }
+ }
+
+ Ok(builder.finish())
+ }};
+}
+
+macro_rules! make_primitive {
+ ($VALUES:expr, $IN_VALUES:expr, $NEGATED:expr, $TYPE:ident, $LIST_FROM_SCALAR: expr) => {{
+ let left = $VALUES.as_any().downcast_ref::<$TYPE>().expect(&format!(
+ "Unable to downcast values to {}",
+ stringify!($TYPE)
+ ));
+
+ if $NEGATED {
+ Ok(ColumnarValue::Array(Arc::new(neq_primitive(
+ left,
+ $IN_VALUES,
+ $LIST_FROM_SCALAR,
+ )?)))
+ } else {
+ Ok(ColumnarValue::Array(Arc::new(eq_primitive(
+ left,
+ $IN_VALUES,
+ $LIST_FROM_SCALAR,
+ )?)))
+ }
+ }};
+}
+
+fn eq_primitive<T: ArrowPrimitiveType>(
+ array: &PrimitiveArray<T>,
+ list: &ListArray,
+ list_from_scalar: bool,
+) -> Result<BooleanArray> {
+ compare_op_scalar!(
+ array,
+ list,
+ |x, v: &PrimitiveArray<T>| v.values().contains(&x),
+ PrimitiveArray<T>,
+ list_from_scalar
+ )
+}
+
+fn neq_primitive<T: ArrowPrimitiveType>(
+ array: &PrimitiveArray<T>,
+ list: &ListArray,
+ list_from_scalar: bool,
+) -> Result<BooleanArray> {
+ compare_op_scalar!(
+ array,
+ list,
+ |x, v: &PrimitiveArray<T>| !v.values().contains(&x),
+ PrimitiveArray<T>,
+ list_from_scalar
+ )
+}
+
+fn eq_bool(
+ array: &BooleanArray,
+ list: &ListArray,
+ list_from_scalar: bool,
+) -> Result<BooleanArray> {
+ compare_op_scalar!(
+ array,
+ list,
+ |x, v: &BooleanArray| unsafe {
+ for i in 0..v.len() {
+ if v.value_unchecked(i) == x {
+ return true;
+ }
+ }
+
+ false
+ },
+ BooleanArray,
+ list_from_scalar
+ )
+}
+
+fn neq_bool(
+ array: &BooleanArray,
+ list: &ListArray,
+ list_from_scalar: bool,
+) -> Result<BooleanArray> {
+ compare_op_scalar!(
+ array,
+ list,
+ |x, v: &BooleanArray| unsafe {
+ for i in 0..v.len() {
+ if v.value_unchecked(i) == x {
+ return false;
+ }
+ }
+
+ true
+ },
+ BooleanArray,
+ list_from_scalar
+ )
+}
+
+fn eq_utf8<OffsetSize: StringOffsetSizeTrait>(
+ array: &GenericStringArray<OffsetSize>,
+ list: &ListArray,
+ list_from_scalar: bool,
+) -> Result<BooleanArray> {
+ compare_op_scalar!(
+ array,
+ list,
+ |x, v: &GenericStringArray<OffsetSize>| unsafe {
+ for i in 0..v.len() {
+ if v.value_unchecked(i) == x {
+ return true;
+ }
+ }
+
+ false
+ },
+ GenericStringArray<OffsetSize>,
+ list_from_scalar
+ )
+}
+
+fn neq_utf8<OffsetSize: StringOffsetSizeTrait>(
+ array: &GenericStringArray<OffsetSize>,
+ list: &ListArray,
+ list_from_scalar: bool,
+) -> Result<BooleanArray> {
+ compare_op_scalar!(
+ array,
+ list,
+ |x, v: &GenericStringArray<OffsetSize>| unsafe {
+ for i in 0..v.len() {
+ if v.value_unchecked(i) == x {
+ return false;
+ }
+ }
+
+ true
+ },
+ GenericStringArray<OffsetSize>,
+ list_from_scalar
+ )
+}
+
+/// AnyExpr
+#[derive(Debug)]
+pub struct AnyExpr {
+ value: Arc<dyn PhysicalExpr>,
+ op: Operator,
+ list: Arc<dyn PhysicalExpr>,
+}
+
+impl AnyExpr {
+ /// Create a new InList expression
+ pub fn new(
+ value: Arc<dyn PhysicalExpr>,
+ op: Operator,
+ list: Arc<dyn PhysicalExpr>,
+ ) -> Self {
+ Self { value, op, list }
+ }
+
+ /// Compare for specific utf8 types
+ fn compare_utf8<T: StringOffsetSizeTrait>(
+ &self,
+ array: ArrayRef,
+ list: &ListArray,
+ negated: bool,
+ list_from_scalar: bool,
+ ) -> Result<ColumnarValue> {
+ let array = array
+ .as_any()
+ .downcast_ref::<GenericStringArray<T>>()
+ .unwrap();
+
+ if negated {
+ Ok(ColumnarValue::Array(Arc::new(neq_utf8(
+ array,
+ list,
+ list_from_scalar,
+ )?)))
+ } else {
+ Ok(ColumnarValue::Array(Arc::new(eq_utf8(
+ array,
+ list,
+ list_from_scalar,
+ )?)))
+ }
+ }
+
+ /// Get the left side of the binary expression
+ pub fn left(&self) -> &Arc<dyn PhysicalExpr> {
+ &self.value
+ }
+
+ /// Get the right side of the binary expression
+ pub fn right(&self) -> &Arc<dyn PhysicalExpr> {
+ &self.list
+ }
+
+ /// Get the operator for this binary expression
+ pub fn op(&self) -> &Operator {
+ &self.op
+ }
+
+ /// Compare for specific utf8 types
+ fn compare_bool(
+ &self,
+ array: ArrayRef,
+ list: &ListArray,
+ negated: bool,
+ list_from_scalar: bool,
+ ) -> Result<ColumnarValue> {
+ let array = array.as_any().downcast_ref::<BooleanArray>().unwrap();
+
+ if negated {
+ Ok(ColumnarValue::Array(Arc::new(neq_bool(
+ array,
+ list,
+ list_from_scalar,
+ )?)))
+ } else {
+ Ok(ColumnarValue::Array(Arc::new(eq_bool(
+ array,
+ list,
+ list_from_scalar,
+ )?)))
+ }
+ }
+}
+
+impl std::fmt::Display for AnyExpr {
+ fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
+ write!(f, "{} {} ANY({})", self.value, self.op, self.list)
+ }
+}
+
+impl PhysicalExpr for AnyExpr {
+ /// Return a reference to Any that can be used for downcasting
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn data_type(&self, _input_schema: &Schema) -> Result<DataType> {
+ Ok(DataType::Boolean)
+ }
+
+ fn nullable(&self, input_schema: &Schema) -> Result<bool> {
+ self.value.nullable(input_schema)
+ }
+
+ fn evaluate(&self, batch: &RecordBatch) -> Result<ColumnarValue> {
+ let value = match self.value.evaluate(batch)? {
+ ColumnarValue::Array(array) => array,
+ ColumnarValue::Scalar(scalar) => scalar.to_array(),
+ };
+
+ let (list, list_from_scalar) = match self.list.evaluate(batch)? {
+ ColumnarValue::Array(array) => (array, false),
+ ColumnarValue::Scalar(scalar) => (scalar.to_array(), true),
+ };
+ let as_list = list
+ .as_any()
+ .downcast_ref::<ListArray>()
+ .expect("Unable to downcast list to ListArray");
+
+ let negated = match self.op {
+ Operator::Eq => false,
+ Operator::NotEq => true,
+ op => {
+ return Err(DataFusionError::NotImplemented(format!(
+ "Operator for ANY expression, actual: {:?}",
+ op
+ )));
+ }
+ };
+
+ match value.data_type() {
+ DataType::Float16 => {
+ make_primitive!(value, as_list, negated, Float16Array, list_from_scalar)
+ }
+ DataType::Float32 => {
+ make_primitive!(value, as_list, negated, Float32Array, list_from_scalar)
+ }
+ DataType::Float64 => {
+ make_primitive!(value, as_list, negated, Float64Array, list_from_scalar)
+ }
+ DataType::Int8 => {
+ make_primitive!(value, as_list, negated, Int8Array, list_from_scalar)
+ }
+ DataType::Int16 => {
+ make_primitive!(value, as_list, negated, Int16Array, list_from_scalar)
+ }
+ DataType::Int32 => {
+ make_primitive!(value, as_list, negated, Int32Array, list_from_scalar)
+ }
+ DataType::Int64 => {
+ make_primitive!(value, as_list, negated, Int64Array, list_from_scalar)
+ }
+ DataType::UInt8 => {
+ make_primitive!(value, as_list, negated, UInt8Array, list_from_scalar)
+ }
+ DataType::UInt16 => {
+ make_primitive!(value, as_list, negated, UInt16Array, list_from_scalar)
+ }
+ DataType::UInt32 => {
+ make_primitive!(value, as_list, negated, UInt32Array, list_from_scalar)
+ }
+ DataType::UInt64 => {
+ make_primitive!(value, as_list, negated, UInt64Array, list_from_scalar)
+ }
+ DataType::Boolean => {
+ self.compare_bool(value, as_list, negated, list_from_scalar)
+ }
+ DataType::Utf8 => {
+ self.compare_utf8::<i32>(value, as_list, negated, list_from_scalar)
+ }
+ DataType::LargeUtf8 => {
+ self.compare_utf8::<i64>(value, as_list, negated, list_from_scalar)
+ }
+ datatype => Result::Err(DataFusionError::NotImplemented(format!(
+ "AnyExpr does not support datatype {:?}.",
+ datatype
+ ))),
+ }
+ }
+}
+
+/// return two physical expressions that are optionally coerced to a
+/// common type that the binary operator supports.
+fn any_cast(
+ value: Arc<dyn PhysicalExpr>,
+ _op: &Operator,
+ list: Arc<dyn PhysicalExpr>,
+ input_schema: &Schema,
+) -> Result<(Arc<dyn PhysicalExpr>, Arc<dyn PhysicalExpr>)> {
+ let tmp = list.data_type(input_schema)?;
+ let list_type = match &tmp {
+ DataType::List(f) => f.data_type(),
+ _ => panic!("wtf"),
Review Comment:
Oops! My bad :D Fixed.
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