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The following commit(s) were added to refs/heads/main by this push:
new e07f24c8 feat: Support Ansi mode in abs function (#500)
e07f24c8 is described below
commit e07f24c88293b4882bb8fd688acee9809478e07c
Author: Pablo Langa <[email protected]>
AuthorDate: Tue Jun 11 09:28:02 2024 -0400
feat: Support Ansi mode in abs function (#500)
* change proto msg
* QueryPlanSerde with eval mode
* Move eval mode
* Add abs in planner
* CometAbsFunc wrapper
* Add error management
* Add tests
* Add license
* spotless apply
* format
* Fix clippy
* error msg for all spark versions
* Fix benches
* Use enum to ansi mode
* Fix format
* Add more tests
* Format
* Refactor
* refactor
* fix merge
* fix merge
---
core/benches/cast_from_string.rs | 2 +-
core/benches/cast_numeric.rs | 2 +-
core/src/execution/datafusion/expressions/abs.rs | 87 ++++++++++++++++++++++
core/src/execution/datafusion/expressions/cast.rs | 9 +--
core/src/execution/datafusion/expressions/mod.rs | 29 ++++++++
.../execution/datafusion/expressions/negative.rs | 8 +-
core/src/execution/datafusion/planner.rs | 19 +++--
core/src/execution/proto/expr.proto | 1 +
.../org/apache/comet/serde/QueryPlanSerde.scala | 14 ++--
.../org/apache/comet/CometExpressionSuite.scala | 54 ++++++++++++++
10 files changed, 195 insertions(+), 30 deletions(-)
diff --git a/core/benches/cast_from_string.rs b/core/benches/cast_from_string.rs
index 5bfaebf3..9a9ab18c 100644
--- a/core/benches/cast_from_string.rs
+++ b/core/benches/cast_from_string.rs
@@ -17,7 +17,7 @@
use arrow_array::{builder::StringBuilder, RecordBatch};
use arrow_schema::{DataType, Field, Schema};
-use comet::execution::datafusion::expressions::cast::{Cast, EvalMode};
+use comet::execution::datafusion::expressions::{cast::Cast, EvalMode};
use criterion::{criterion_group, criterion_main, Criterion};
use datafusion_physical_expr::{expressions::Column, PhysicalExpr};
use std::sync::Arc;
diff --git a/core/benches/cast_numeric.rs b/core/benches/cast_numeric.rs
index 398be694..35f24ce5 100644
--- a/core/benches/cast_numeric.rs
+++ b/core/benches/cast_numeric.rs
@@ -17,7 +17,7 @@
use arrow_array::{builder::Int32Builder, RecordBatch};
use arrow_schema::{DataType, Field, Schema};
-use comet::execution::datafusion::expressions::cast::{Cast, EvalMode};
+use comet::execution::datafusion::expressions::{cast::Cast, EvalMode};
use criterion::{criterion_group, criterion_main, Criterion};
use datafusion_physical_expr::{expressions::Column, PhysicalExpr};
use std::sync::Arc;
diff --git a/core/src/execution/datafusion/expressions/abs.rs
b/core/src/execution/datafusion/expressions/abs.rs
new file mode 100644
index 00000000..4eb8c7c1
--- /dev/null
+++ b/core/src/execution/datafusion/expressions/abs.rs
@@ -0,0 +1,87 @@
+// 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.
+
+use arrow::datatypes::DataType;
+use arrow_schema::ArrowError;
+use datafusion::logical_expr::{ColumnarValue, ScalarUDFImpl, Signature};
+use datafusion_common::DataFusionError;
+use datafusion_functions::math;
+use std::{any::Any, sync::Arc};
+
+use crate::execution::operators::ExecutionError;
+
+use super::{arithmetic_overflow_error, EvalMode};
+
+#[derive(Debug)]
+pub struct CometAbsFunc {
+ inner_abs_func: Arc<dyn ScalarUDFImpl>,
+ eval_mode: EvalMode,
+ data_type_name: String,
+}
+
+impl CometAbsFunc {
+ pub fn new(eval_mode: EvalMode, data_type_name: String) -> Result<Self,
ExecutionError> {
+ if let EvalMode::Legacy | EvalMode::Ansi = eval_mode {
+ Ok(Self {
+ inner_abs_func: math::abs().inner(),
+ eval_mode,
+ data_type_name,
+ })
+ } else {
+ Err(ExecutionError::GeneralError(format!(
+ "Invalid EvalMode: \"{:?}\"",
+ eval_mode
+ )))
+ }
+ }
+}
+
+impl ScalarUDFImpl for CometAbsFunc {
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+ fn name(&self) -> &str {
+ "abs"
+ }
+
+ fn signature(&self) -> &Signature {
+ self.inner_abs_func.signature()
+ }
+
+ fn return_type(&self, arg_types: &[DataType]) -> Result<DataType,
DataFusionError> {
+ self.inner_abs_func.return_type(arg_types)
+ }
+
+ fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue,
DataFusionError> {
+ match self.inner_abs_func.invoke(args) {
+ Err(DataFusionError::ArrowError(ArrowError::ComputeError(msg),
trace))
+ if msg.contains("overflow") =>
+ {
+ if self.eval_mode == EvalMode::Legacy {
+ Ok(args[0].clone())
+ } else {
+ let msg =
arithmetic_overflow_error(&self.data_type_name).to_string();
+ Err(DataFusionError::ArrowError(
+ ArrowError::ComputeError(msg),
+ trace,
+ ))
+ }
+ }
+ other => other,
+ }
+ }
+}
diff --git a/core/src/execution/datafusion/expressions/cast.rs
b/core/src/execution/datafusion/expressions/cast.rs
index 04562646..4dae62dc 100644
--- a/core/src/execution/datafusion/expressions/cast.rs
+++ b/core/src/execution/datafusion/expressions/cast.rs
@@ -52,6 +52,8 @@ use crate::{
},
};
+use super::EvalMode;
+
static TIMESTAMP_FORMAT: Option<&str> = Some("%Y-%m-%d %H:%M:%S%.f");
static CAST_OPTIONS: CastOptions = CastOptions {
@@ -61,13 +63,6 @@ static CAST_OPTIONS: CastOptions = CastOptions {
.with_timestamp_format(TIMESTAMP_FORMAT),
};
-#[derive(Debug, Hash, PartialEq, Clone, Copy)]
-pub enum EvalMode {
- Legacy,
- Ansi,
- Try,
-}
-
#[derive(Debug, Hash)]
pub struct Cast {
pub child: Arc<dyn PhysicalExpr>,
diff --git a/core/src/execution/datafusion/expressions/mod.rs
b/core/src/execution/datafusion/expressions/mod.rs
index 05230b4c..5d5f58e0 100644
--- a/core/src/execution/datafusion/expressions/mod.rs
+++ b/core/src/execution/datafusion/expressions/mod.rs
@@ -24,6 +24,10 @@ pub mod if_expr;
mod normalize_nan;
pub mod scalar_funcs;
pub use normalize_nan::NormalizeNaNAndZero;
+use prost::DecodeError;
+
+use crate::{errors::CometError, execution::spark_expression};
+pub mod abs;
pub mod avg;
pub mod avg_decimal;
pub mod bloom_filter_might_contain;
@@ -39,3 +43,28 @@ pub mod temporal;
pub mod unbound;
mod utils;
pub mod variance;
+
+#[derive(Debug, Hash, PartialEq, Clone, Copy)]
+pub enum EvalMode {
+ Legacy,
+ Ansi,
+ Try,
+}
+
+impl TryFrom<i32> for EvalMode {
+ type Error = DecodeError;
+
+ fn try_from(value: i32) -> Result<Self, Self::Error> {
+ match spark_expression::EvalMode::try_from(value)? {
+ spark_expression::EvalMode::Legacy => Ok(EvalMode::Legacy),
+ spark_expression::EvalMode::Try => Ok(EvalMode::Try),
+ spark_expression::EvalMode::Ansi => Ok(EvalMode::Ansi),
+ }
+ }
+}
+
+fn arithmetic_overflow_error(from_type: &str) -> CometError {
+ CometError::ArithmeticOverflow {
+ from_type: from_type.to_string(),
+ }
+}
diff --git a/core/src/execution/datafusion/expressions/negative.rs
b/core/src/execution/datafusion/expressions/negative.rs
index a85cde89..cd0e9bcc 100644
--- a/core/src/execution/datafusion/expressions/negative.rs
+++ b/core/src/execution/datafusion/expressions/negative.rs
@@ -33,6 +33,8 @@ use std::{
sync::Arc,
};
+use super::arithmetic_overflow_error;
+
pub fn create_negate_expr(
expr: Arc<dyn PhysicalExpr>,
fail_on_error: bool,
@@ -48,12 +50,6 @@ pub struct NegativeExpr {
fail_on_error: bool,
}
-fn arithmetic_overflow_error(from_type: &str) -> CometError {
- CometError::ArithmeticOverflow {
- from_type: from_type.to_string(),
- }
-}
-
macro_rules! check_overflow {
($array:expr, $array_type:ty, $min_val:expr, $type_name:expr) => {{
let typed_array = $array
diff --git a/core/src/execution/datafusion/planner.rs
b/core/src/execution/datafusion/planner.rs
index e5193215..d92bf578 100644
--- a/core/src/execution/datafusion/planner.rs
+++ b/core/src/execution/datafusion/planner.rs
@@ -24,7 +24,6 @@ use datafusion::{
arrow::{compute::SortOptions, datatypes::SchemaRef},
common::DataFusionError,
execution::FunctionRegistry,
- functions::math,
logical_expr::Operator as DataFusionOperator,
physical_expr::{
execution_props::ExecutionProps,
@@ -51,6 +50,7 @@ use datafusion_common::{
tree_node::{Transformed, TransformedResult, TreeNode, TreeNodeRecursion,
TreeNodeRewriter},
JoinType as DFJoinType, ScalarValue,
};
+use datafusion_expr::ScalarUDF;
use datafusion_physical_expr_common::aggregate::create_aggregate_expr;
use itertools::Itertools;
use jni::objects::GlobalRef;
@@ -65,7 +65,7 @@ use crate::{
avg_decimal::AvgDecimal,
bitwise_not::BitwiseNotExpr,
bloom_filter_might_contain::BloomFilterMightContain,
- cast::{Cast, EvalMode},
+ cast::Cast,
checkoverflow::CheckOverflow,
correlation::Correlation,
covariance::Covariance,
@@ -97,6 +97,8 @@ use crate::{
},
};
+use super::expressions::{abs::CometAbsFunc, EvalMode};
+
// For clippy error on type_complexity.
type ExecResult<T> = Result<T, ExecutionError>;
type PhyAggResult = Result<Vec<Arc<dyn AggregateExpr>>, ExecutionError>;
@@ -356,11 +358,7 @@ impl PhysicalPlanner {
let child = self.create_expr(expr.child.as_ref().unwrap(),
input_schema)?;
let datatype =
to_arrow_datatype(expr.datatype.as_ref().unwrap());
let timezone = expr.timezone.clone();
- let eval_mode = match
spark_expression::EvalMode::try_from(expr.eval_mode)? {
- spark_expression::EvalMode::Legacy => EvalMode::Legacy,
- spark_expression::EvalMode::Try => EvalMode::Try,
- spark_expression::EvalMode::Ansi => EvalMode::Ansi,
- };
+ let eval_mode = expr.eval_mode.try_into()?;
Ok(Arc::new(Cast::new(child, datatype, eval_mode, timezone)))
}
@@ -499,7 +497,12 @@ impl PhysicalPlanner {
let child = self.create_expr(expr.child.as_ref().unwrap(),
input_schema.clone())?;
let return_type = child.data_type(&input_schema)?;
let args = vec![child];
- let expr = ScalarFunctionExpr::new("abs", math::abs(), args,
return_type);
+ let eval_mode = expr.eval_mode.try_into()?;
+ let comet_abs =
Arc::new(ScalarUDF::new_from_impl(CometAbsFunc::new(
+ eval_mode,
+ return_type.to_string(),
+ )?));
+ let expr = ScalarFunctionExpr::new("abs", comet_abs, args,
return_type);
Ok(Arc::new(expr))
}
ExprStruct::CaseWhen(case_when) => {
diff --git a/core/src/execution/proto/expr.proto
b/core/src/execution/proto/expr.proto
index 5192bbd4..093b07b3 100644
--- a/core/src/execution/proto/expr.proto
+++ b/core/src/execution/proto/expr.proto
@@ -480,6 +480,7 @@ message BitwiseNot {
message Abs {
Expr child = 1;
+ EvalMode eval_mode = 2;
}
message Subquery {
diff --git a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala
b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala
index 5a0ad38d..c1c8b5c5 100644
--- a/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala
+++ b/spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala
@@ -1476,15 +1476,15 @@ object QueryPlanSerde extends Logging with
ShimQueryPlanSerde with CometExprShim
None
}
- case Abs(child, _) =>
+ case Abs(child, failOnErr) =>
val childExpr = exprToProtoInternal(child, inputs)
if (childExpr.isDefined) {
- val abs =
- ExprOuterClass.Abs
- .newBuilder()
- .setChild(childExpr.get)
- .build()
- Some(Expr.newBuilder().setAbs(abs).build())
+ val evalModeStr =
+ if (failOnErr) ExprOuterClass.EvalMode.ANSI else
ExprOuterClass.EvalMode.LEGACY
+ val absBuilder = ExprOuterClass.Abs.newBuilder()
+ absBuilder.setChild(childExpr.get)
+ absBuilder.setEvalMode(evalModeStr)
+ Some(Expr.newBuilder().setAbs(absBuilder).build())
} else {
withInfo(expr, child)
None
diff --git a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala
b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala
index 10fbc468..a2b6edd0 100644
--- a/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala
+++ b/spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala
@@ -19,6 +19,9 @@
package org.apache.comet
+import scala.reflect.ClassTag
+import scala.reflect.runtime.universe.TypeTag
+
import org.apache.hadoop.fs.Path
import org.apache.spark.sql.{CometTestBase, DataFrame, Row}
import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
@@ -850,6 +853,57 @@ class CometExpressionSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
}
}
+ test("abs Overflow ansi mode") {
+
+ def testAbsAnsiOverflow[T <: Product: ClassTag: TypeTag](data: Seq[T]):
Unit = {
+ withParquetTable(data, "tbl") {
+ checkSparkMaybeThrows(sql("select abs(_1), abs(_2) from tbl")) match {
+ case (Some(sparkExc), Some(cometExc)) =>
+ val cometErrorPattern =
+ """.+[ARITHMETIC_OVERFLOW].+overflow. If necessary set
"spark.sql.ansi.enabled" to "false" to bypass this error.""".r
+
assert(cometErrorPattern.findFirstIn(cometExc.getMessage).isDefined)
+ assert(sparkExc.getMessage.contains("overflow"))
+ case _ => fail("Exception should be thrown")
+ }
+ }
+ }
+
+ def testAbsAnsi[T <: Product: ClassTag: TypeTag](data: Seq[T]): Unit = {
+ withParquetTable(data, "tbl") {
+ checkSparkAnswerAndOperator("select abs(_1), abs(_2) from tbl")
+ }
+ }
+
+ withSQLConf(
+ SQLConf.ANSI_ENABLED.key -> "true",
+ CometConf.COMET_ANSI_MODE_ENABLED.key -> "true") {
+ testAbsAnsiOverflow(Seq((Byte.MaxValue, Byte.MinValue)))
+ testAbsAnsiOverflow(Seq((Short.MaxValue, Short.MinValue)))
+ testAbsAnsiOverflow(Seq((Int.MaxValue, Int.MinValue)))
+ testAbsAnsiOverflow(Seq((Long.MaxValue, Long.MinValue)))
+ testAbsAnsi(Seq((Float.MaxValue, Float.MinValue)))
+ testAbsAnsi(Seq((Double.MaxValue, Double.MinValue)))
+ }
+ }
+
+ test("abs Overflow legacy mode") {
+
+ def testAbsLegacyOverflow[T <: Product: ClassTag: TypeTag](data: Seq[T]):
Unit = {
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> "false") {
+ withParquetTable(data, "tbl") {
+ checkSparkAnswerAndOperator("select abs(_1), abs(_2) from tbl")
+ }
+ }
+ }
+
+ testAbsLegacyOverflow(Seq((Byte.MaxValue, Byte.MinValue)))
+ testAbsLegacyOverflow(Seq((Short.MaxValue, Short.MinValue)))
+ testAbsLegacyOverflow(Seq((Int.MaxValue, Int.MinValue)))
+ testAbsLegacyOverflow(Seq((Long.MaxValue, Long.MinValue)))
+ testAbsLegacyOverflow(Seq((Float.MaxValue, Float.MinValue)))
+ testAbsLegacyOverflow(Seq((Double.MaxValue, Double.MinValue)))
+ }
+
test("ceil and floor") {
Seq("true", "false").foreach { dictionary =>
withSQLConf(
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