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perf: Improve query planning to more reliably fall back to columnar shuffle when native shuffle is not supported #1209

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perf: Improve query planning to more reliably fall back to columnar shuffle when native shuffle is not supported #1209

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a1d5dc9
rebase on main
andygrove Jan 1, 2025
fadd394
update stability plans for Spark 3.4
andygrove Jan 1, 2025
540171d
update stability plans for Spark 3.4
andygrove Jan 1, 2025
f62cc68
update stability plans for Spark 3.5
andygrove Jan 1, 2025
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122 changes: 68 additions & 54 deletions spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -788,68 +788,82 @@ class CometSparkSessionExtensions
}

// Native shuffle for Comet operators
case s: ShuffleExchangeExec
if isCometShuffleEnabled(conf) &&
case s: ShuffleExchangeExec =>
val nativeShuffle: Option[SparkPlan] =
if (isCometShuffleEnabled(conf) &&
isCometNativeShuffleMode(conf) &&
QueryPlanSerde.supportPartitioning(s.child.output, s.outputPartitioning)._1 =>
logInfo("Comet extension enabled for Native Shuffle")

val newOp = transform1(s)
newOp match {
case Some(nativeOp) =>
// Switch to use Decimal128 regardless of precision, since Arrow native execution
// doesn't support Decimal32 and Decimal64 yet.
conf.setConfString(CometConf.COMET_USE_DECIMAL_128.key, "true")
val cometOp = CometShuffleExchangeExec(s, shuffleType = CometNativeShuffle)
CometSinkPlaceHolder(nativeOp, s, cometOp)
case None =>
s
}
QueryPlanSerde.supportPartitioning(s.child.output, s.outputPartitioning)._1) {
val newOp = transform1(s)
newOp match {
case Some(nativeOp) =>
// Switch to use Decimal128 regardless of precision, since Arrow native execution
// doesn't support Decimal32 and Decimal64 yet.
conf.setConfString(CometConf.COMET_USE_DECIMAL_128.key, "true")
val cometOp = CometShuffleExchangeExec(s, shuffleType = CometNativeShuffle)
Some(CometSinkPlaceHolder(nativeOp, s, cometOp))
case None =>
None
}
} else {
None
}

// Columnar shuffle for regular Spark operators (not Comet) and Comet operators
// (if configured).
// If the child of ShuffleExchangeExec is also a ShuffleExchangeExec, we should not
// convert it to CometColumnarShuffle,
case s: ShuffleExchangeExec
if isCometShuffleEnabled(conf) && isCometJVMShuffleMode(conf) &&
Comment on lines -813 to -814
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Hmm, if it is auto mode, why this is not triggered?

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This part is triggered, but in the following code, transform1(s) returns None so we return the original shuffle.

          val newOp = transform1(s)
          newOp match {
            case Some(nativeOp) =>
              // Switch to use Decimal128 regardless of precision, since Arrow native execution
              // doesn't support Decimal32 and Decimal64 yet.
              conf.setConfString(CometConf.COMET_USE_DECIMAL_128.key, "true")
              val cometOp = CometShuffleExchangeExec(s, shuffleType = CometNativeShuffle)
              CometSinkPlaceHolder(nativeOp, s, cometOp)
            case None =>
              s
          }

val nativeOrColumnarShuffle = if (nativeShuffle.isDefined) {
nativeShuffle
} else {
// Columnar shuffle for regular Spark operators (not Comet) and Comet operators
// (if configured).
// If the child of ShuffleExchangeExec is also a ShuffleExchangeExec, we should not
// convert it to CometColumnarShuffle,
if (isCometShuffleEnabled(conf) && isCometJVMShuffleMode(conf) &&
QueryPlanSerde.supportPartitioningTypes(s.child.output, s.outputPartitioning)._1 &&
!isShuffleOperator(s.child) =>
logInfo("Comet extension enabled for JVM Columnar Shuffle")
!isShuffleOperator(s.child)) {

val newOp = QueryPlanSerde.operator2Proto(s)
newOp match {
case Some(nativeOp) =>
s.child match {
case n if n.isInstanceOf[CometNativeExec] || !n.supportsColumnar =>
val cometOp = CometShuffleExchangeExec(s, shuffleType = CometColumnarShuffle)
CometSinkPlaceHolder(nativeOp, s, cometOp)
case _ =>
s
val newOp = QueryPlanSerde.operator2Proto(s)
newOp match {
case Some(nativeOp) =>
s.child match {
case n if n.isInstanceOf[CometNativeExec] || !n.supportsColumnar =>
val cometOp =
CometShuffleExchangeExec(s, shuffleType = CometColumnarShuffle)
Some(CometSinkPlaceHolder(nativeOp, s, cometOp))
case _ =>
None
}
case None =>
None
}
case None =>
s
} else {
None
}
}

case s: ShuffleExchangeExec =>
val isShuffleEnabled = isCometShuffleEnabled(conf)
val outputPartitioning = s.outputPartitioning
val reason = getCometShuffleNotEnabledReason(conf).getOrElse("no reason available")
val msg1 = createMessage(!isShuffleEnabled, s"Comet shuffle is not enabled: $reason")
val columnarShuffleEnabled = isCometJVMShuffleMode(conf)
val msg2 = createMessage(
isShuffleEnabled && !columnarShuffleEnabled && !QueryPlanSerde
.supportPartitioning(s.child.output, outputPartitioning)
._1,
"Native shuffle: " +
s"${QueryPlanSerde.supportPartitioning(s.child.output, outputPartitioning)._2}")
val msg3 = createMessage(
isShuffleEnabled && columnarShuffleEnabled && !QueryPlanSerde
if (nativeOrColumnarShuffle.isDefined) {
nativeOrColumnarShuffle.get
} else {
val isShuffleEnabled = isCometShuffleEnabled(conf)
val outputPartitioning = s.outputPartitioning
val reason = getCometShuffleNotEnabledReason(conf).getOrElse("no reason available")
val msg1 = createMessage(!isShuffleEnabled, s"Comet shuffle is not enabled: $reason")
val columnarShuffleEnabled = isCometJVMShuffleMode(conf)
val msg2 = createMessage(
isShuffleEnabled && !columnarShuffleEnabled && !QueryPlanSerde
.supportPartitioning(s.child.output, outputPartitioning)
._1,
"Native shuffle: " +
s"${QueryPlanSerde.supportPartitioning(s.child.output, outputPartitioning)._2}")
val typeInfo = QueryPlanSerde
.supportPartitioningTypes(s.child.output, outputPartitioning)
._1,
"JVM shuffle: " +
s"${QueryPlanSerde.supportPartitioningTypes(s.child.output, outputPartitioning)._2}")
withInfo(s, Seq(msg1, msg2, msg3).flatten.mkString(","))
s
._2
val msg3 = createMessage(
isShuffleEnabled && columnarShuffleEnabled && !QueryPlanSerde
.supportPartitioningTypes(s.child.output, outputPartitioning)
._1,
"JVM shuffle: " +
s"$typeInfo")
withInfo(s, Seq(msg1, msg2, msg3).flatten.mkString(","))
s
}

case op =>
op match {
Expand Down
122 changes: 63 additions & 59 deletions spark/src/test/resources/tpcds-plan-stability/approved-plans-v1_4-spark3_5/q10/explain.txt
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Original file line number Diff line number Diff line change
@@ -1,49 +1,50 @@
== Physical Plan ==
TakeOrderedAndProject (45)
+- * HashAggregate (44)
+- Exchange (43)
+- * HashAggregate (42)
+- * Project (41)
+- * BroadcastHashJoin Inner BuildRight (40)
:- * Project (35)
: +- * BroadcastHashJoin Inner BuildRight (34)
: :- * Project (28)
: : +- * Filter (27)
: : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (26)
: : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (19)
: : : :- * ColumnarToRow (12)
: : : : +- CometBroadcastHashJoin (11)
: : : : :- CometFilter (2)
: : : : : +- CometScan parquet spark_catalog.default.customer (1)
: : : : +- CometBroadcastExchange (10)
: : : : +- CometProject (9)
: : : : +- CometBroadcastHashJoin (8)
: : : : :- CometScan parquet spark_catalog.default.store_sales (3)
: : : : +- CometBroadcastExchange (7)
: : : : +- CometProject (6)
: : : : +- CometFilter (5)
: : : : +- CometScan parquet spark_catalog.default.date_dim (4)
: : : +- BroadcastExchange (18)
: : : +- * ColumnarToRow (17)
: : : +- CometProject (16)
: : : +- CometBroadcastHashJoin (15)
: : : :- CometScan parquet spark_catalog.default.web_sales (13)
: : : +- ReusedExchange (14)
: : +- BroadcastExchange (25)
: : +- * ColumnarToRow (24)
: : +- CometProject (23)
: : +- CometBroadcastHashJoin (22)
: : :- CometScan parquet spark_catalog.default.catalog_sales (20)
: : +- ReusedExchange (21)
: +- BroadcastExchange (33)
: +- * ColumnarToRow (32)
: +- CometProject (31)
: +- CometFilter (30)
: +- CometScan parquet spark_catalog.default.customer_address (29)
+- BroadcastExchange (39)
+- * ColumnarToRow (38)
+- CometFilter (37)
+- CometScan parquet spark_catalog.default.customer_demographics (36)
TakeOrderedAndProject (46)
+- * HashAggregate (45)
+- * ColumnarToRow (44)
+- CometColumnarExchange (43)
+- * HashAggregate (42)
+- * Project (41)
+- * BroadcastHashJoin Inner BuildRight (40)
:- * Project (35)
: +- * BroadcastHashJoin Inner BuildRight (34)
: :- * Project (28)
: : +- * Filter (27)
: : +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (26)
: : :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (19)
: : : :- * ColumnarToRow (12)
: : : : +- CometBroadcastHashJoin (11)
: : : : :- CometFilter (2)
: : : : : +- CometScan parquet spark_catalog.default.customer (1)
: : : : +- CometBroadcastExchange (10)
: : : : +- CometProject (9)
: : : : +- CometBroadcastHashJoin (8)
: : : : :- CometScan parquet spark_catalog.default.store_sales (3)
: : : : +- CometBroadcastExchange (7)
: : : : +- CometProject (6)
: : : : +- CometFilter (5)
: : : : +- CometScan parquet spark_catalog.default.date_dim (4)
: : : +- BroadcastExchange (18)
: : : +- * ColumnarToRow (17)
: : : +- CometProject (16)
: : : +- CometBroadcastHashJoin (15)
: : : :- CometScan parquet spark_catalog.default.web_sales (13)
: : : +- ReusedExchange (14)
: : +- BroadcastExchange (25)
: : +- * ColumnarToRow (24)
: : +- CometProject (23)
: : +- CometBroadcastHashJoin (22)
: : :- CometScan parquet spark_catalog.default.catalog_sales (20)
: : +- ReusedExchange (21)
: +- BroadcastExchange (33)
: +- * ColumnarToRow (32)
: +- CometProject (31)
: +- CometFilter (30)
: +- CometScan parquet spark_catalog.default.customer_address (29)
+- BroadcastExchange (39)
+- * ColumnarToRow (38)
+- CometFilter (37)
+- CometScan parquet spark_catalog.default.customer_demographics (36)


(1) CometScan parquet spark_catalog.default.customer
Expand Down Expand Up @@ -243,50 +244,53 @@ Functions [1]: [partial_count(1)]
Aggregate Attributes [1]: [count#31]
Results [9]: [cd_gender#23, cd_marital_status#24, cd_education_status#25, cd_purchase_estimate#26, cd_credit_rating#27, cd_dep_count#28, cd_dep_employed_count#29, cd_dep_college_count#30, count#32]

(43) Exchange
(43) CometColumnarExchange
Input [9]: [cd_gender#23, cd_marital_status#24, cd_education_status#25, cd_purchase_estimate#26, cd_credit_rating#27, cd_dep_count#28, cd_dep_employed_count#29, cd_dep_college_count#30, count#32]
Arguments: hashpartitioning(cd_gender#23, cd_marital_status#24, cd_education_status#25, cd_purchase_estimate#26, cd_credit_rating#27, cd_dep_count#28, cd_dep_employed_count#29, cd_dep_college_count#30, 5), ENSURE_REQUIREMENTS, [plan_id=5]
Arguments: hashpartitioning(cd_gender#23, cd_marital_status#24, cd_education_status#25, cd_purchase_estimate#26, cd_credit_rating#27, cd_dep_count#28, cd_dep_employed_count#29, cd_dep_college_count#30, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(44) HashAggregate [codegen id : 6]
(44) ColumnarToRow [codegen id : 6]
Input [9]: [cd_gender#23, cd_marital_status#24, cd_education_status#25, cd_purchase_estimate#26, cd_credit_rating#27, cd_dep_count#28, cd_dep_employed_count#29, cd_dep_college_count#30, count#32]

(45) HashAggregate [codegen id : 6]
Input [9]: [cd_gender#23, cd_marital_status#24, cd_education_status#25, cd_purchase_estimate#26, cd_credit_rating#27, cd_dep_count#28, cd_dep_employed_count#29, cd_dep_college_count#30, count#32]
Keys [8]: [cd_gender#23, cd_marital_status#24, cd_education_status#25, cd_purchase_estimate#26, cd_credit_rating#27, cd_dep_count#28, cd_dep_employed_count#29, cd_dep_college_count#30]
Functions [1]: [count(1)]
Aggregate Attributes [1]: [count(1)#33]
Results [14]: [cd_gender#23, cd_marital_status#24, cd_education_status#25, count(1)#33 AS cnt1#34, cd_purchase_estimate#26, count(1)#33 AS cnt2#35, cd_credit_rating#27, count(1)#33 AS cnt3#36, cd_dep_count#28, count(1)#33 AS cnt4#37, cd_dep_employed_count#29, count(1)#33 AS cnt5#38, cd_dep_college_count#30, count(1)#33 AS cnt6#39]

(45) TakeOrderedAndProject
(46) TakeOrderedAndProject
Input [14]: [cd_gender#23, cd_marital_status#24, cd_education_status#25, cnt1#34, cd_purchase_estimate#26, cnt2#35, cd_credit_rating#27, cnt3#36, cd_dep_count#28, cnt4#37, cd_dep_employed_count#29, cnt5#38, cd_dep_college_count#30, cnt6#39]
Arguments: 100, [cd_gender#23 ASC NULLS FIRST, cd_marital_status#24 ASC NULLS FIRST, cd_education_status#25 ASC NULLS FIRST, cd_purchase_estimate#26 ASC NULLS FIRST, cd_credit_rating#27 ASC NULLS FIRST, cd_dep_count#28 ASC NULLS FIRST, cd_dep_employed_count#29 ASC NULLS FIRST, cd_dep_college_count#30 ASC NULLS FIRST], [cd_gender#23, cd_marital_status#24, cd_education_status#25, cnt1#34, cd_purchase_estimate#26, cnt2#35, cd_credit_rating#27, cnt3#36, cd_dep_count#28, cnt4#37, cd_dep_employed_count#29, cnt5#38, cd_dep_college_count#30, cnt6#39]

===== Subqueries =====

Subquery:1 Hosting operator id = 3 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8
BroadcastExchange (50)
+- * ColumnarToRow (49)
+- CometProject (48)
+- CometFilter (47)
+- CometScan parquet spark_catalog.default.date_dim (46)
BroadcastExchange (51)
+- * ColumnarToRow (50)
+- CometProject (49)
+- CometFilter (48)
+- CometScan parquet spark_catalog.default.date_dim (47)


(46) CometScan parquet spark_catalog.default.date_dim
(47) CometScan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#9, d_year#10, d_moy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2002), GreaterThanOrEqual(d_moy,1), LessThanOrEqual(d_moy,4), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(47) CometFilter
(48) CometFilter
Input [3]: [d_date_sk#9, d_year#10, d_moy#11]
Condition : (((((isnotnull(d_year#10) AND isnotnull(d_moy#11)) AND (d_year#10 = 2002)) AND (d_moy#11 >= 1)) AND (d_moy#11 <= 4)) AND isnotnull(d_date_sk#9))

(48) CometProject
(49) CometProject
Input [3]: [d_date_sk#9, d_year#10, d_moy#11]
Arguments: [d_date_sk#9], [d_date_sk#9]

(49) ColumnarToRow [codegen id : 1]
(50) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#9]

(50) BroadcastExchange
(51) BroadcastExchange
Input [1]: [d_date_sk#9]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]

Expand Down
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