coderfender commented on code in PR #2600:
URL: https://github.com/apache/datafusion-comet/pull/2600#discussion_r2640708288
##########
spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala:
##########
@@ -1490,11 +1501,23 @@ class CometAggregateSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
}
}
+ test("ANSI support for try_sum - null test") {
+ Seq(true, false).foreach { ansiEnabled =>
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> ansiEnabled.toString) {
+ withParquetTable(
+ Seq((null.asInstanceOf[java.lang.Long], "a"),
(null.asInstanceOf[java.lang.Long], "b")),
+ "null_tbl") {
+ val res = sql("SELECT try_sum(_1) FROM null_tbl")
+ checkSparkAnswerAndOperator(res)
+ assert(res.collect() === Array(Row(null)))
Review Comment:
@comphead , Yeah , I found some inconsistencies while writing these tests
as (partially) discussed here :
https://github.com/apache/datafusion-comet/issues/2692 . Also ,I wanted to be
completely sure in terms of output given the core functionality of this PR
##########
spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala:
##########
@@ -1508,11 +1531,28 @@ class CometAggregateSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
}
}
+ test("ANSI support for sum - null test (group by)") {
+ Seq(true, false).foreach { ansiEnabled =>
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> ansiEnabled.toString) {
+ withParquetTable(
+ Seq(
+ (null.asInstanceOf[java.lang.Long], "a"),
+ (null.asInstanceOf[java.lang.Long], "a"),
+ (null.asInstanceOf[java.lang.Long], "b"),
+ (null.asInstanceOf[java.lang.Long], "b"),
+ (null.asInstanceOf[java.lang.Long], "b")),
+ "tbl") {
+ val res = sql("SELECT _2, sum(_1) FROM tbl group by 1")
+ checkSparkAnswerAndOperator(res)
+ assert(res.orderBy(col("_2")).collect() === Array(Row("a", null),
Row("b", null)))
Review Comment:
replied above
##########
spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala:
##########
@@ -1602,35 +1768,68 @@ class CometAggregateSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
}
}
+ test("try_sum overflow - with GROUP BY") {
+ // Test Long overflow with GROUP BY - some groups overflow while some don't
+ withParquetTable(Seq((Long.MaxValue, 1), (100L, 1), (200L, 2), (300L, 2)),
"tbl") {
+ val res = sql("SELECT _2, try_sum(_1) FROM tbl GROUP BY
_2").repartition(2, col("_2"))
Review Comment:
Sure let me add a comment here
##########
spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala:
##########
@@ -1555,11 +1612,63 @@ class CometAggregateSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
(1 to 50).flatMap(_ => Seq((maxDec38_0, 1)))
}
+ test("ANSI support - SUM function") {
+ Seq(true, false).foreach { ansiEnabled =>
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> ansiEnabled.toString) {
+ // Test long overflow
+ withParquetTable(Seq((Long.MaxValue, 1L), (100L, 1L)), "tbl") {
+ val res = sql("SELECT SUM(_1) FROM tbl")
+ if (ansiEnabled) {
+ checkSparkAnswerMaybeThrows(res) match {
+ case (Some(sparkExc), Some(cometExc)) =>
+ assert(sparkExc.getMessage.contains("ARITHMETIC_OVERFLOW"))
Review Comment:
Sure . I thought that the `ansiEnabled` should give away why the overflow
message is expected but let me add a comment to make things explicit
##########
spark/src/main/scala/org/apache/comet/serde/aggregates.scala:
##########
@@ -213,17 +213,6 @@ object CometAverage extends
CometAggregateExpressionSerde[Average] {
object CometSum extends CometAggregateExpressionSerde[Sum] {
- override def getSupportLevel(sum: Sum): SupportLevel = {
- sum.evalMode match {
- case EvalMode.ANSI if !sum.dataType.isInstanceOf[DecimalType] =>
- Incompatible(Some("ANSI mode for non decimal inputs is not supported"))
Review Comment:
@comphead thank you . I generally follow up the main PR with a separate doc
PR and I hope that is okay to do the same thing with this PR too ?
##########
spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala:
##########
@@ -1529,11 +1569,28 @@ class CometAggregateSuite extends CometTestBase with
AdaptiveSparkPlanHelper {
}
}
+ test("ANSI support for try_sum - null test (group by)") {
+ Seq(true, false).foreach { ansiEnabled =>
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> ansiEnabled.toString) {
+ withParquetTable(
+ Seq(
+ (null.asInstanceOf[java.lang.Long], "a"),
+ (null.asInstanceOf[java.lang.Long], "a"),
+ (null.asInstanceOf[java.lang.Long], "b"),
+ (null.asInstanceOf[java.lang.Long], "b"),
+ (null.asInstanceOf[java.lang.Long], "b")),
+ "tbl") {
+ val res = sql("SELECT _2, try_sum(_1) FROM tbl group by 1")
+ checkSparkAnswerAndOperator(res)
+ assert(res.orderBy(col("_2")).collect() === Array(Row("a", null),
Row("b", null)))
Review Comment:
replied above
##########
native/spark-expr/src/agg_funcs/sum_int.rs:
##########
@@ -0,0 +1,589 @@
+// 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 crate::{arithmetic_overflow_error, EvalMode};
+use arrow::array::{
+ as_primitive_array, cast::AsArray, Array, ArrayRef, ArrowNativeTypeOp,
ArrowPrimitiveType,
+ BooleanArray, Int64Array, PrimitiveArray,
+};
+use arrow::datatypes::{
+ ArrowNativeType, DataType, Field, FieldRef, Int16Type, Int32Type,
Int64Type, Int8Type,
+};
+use datafusion::common::{DataFusionError, Result as DFResult, ScalarValue};
+use datafusion::logical_expr::function::{AccumulatorArgs, StateFieldsArgs};
+use datafusion::logical_expr::Volatility::Immutable;
+use datafusion::logical_expr::{
+ Accumulator, AggregateUDFImpl, EmitTo, GroupsAccumulator, ReversedUDAF,
Signature,
+};
+use std::{any::Any, sync::Arc};
+
+#[derive(Debug, PartialEq, Eq, Hash)]
+pub struct SumInteger {
+ signature: Signature,
+ eval_mode: EvalMode,
+}
+
+impl SumInteger {
+ pub fn try_new(data_type: DataType, eval_mode: EvalMode) -> DFResult<Self>
{
+ match data_type {
+ DataType::Int8 | DataType::Int16 | DataType::Int32 |
DataType::Int64 => Ok(Self {
+ signature: Signature::user_defined(Immutable),
+ eval_mode,
+ }),
+ _ => Err(DataFusionError::Internal(
+ "Invalid data type for SumInteger".into(),
+ )),
+ }
+ }
+}
+
+impl AggregateUDFImpl for SumInteger {
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn name(&self) -> &str {
Review Comment:
It would be the same :) . We even have the same name for the decimal sum
(which is a custom implementation) as well .
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