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[GitHub] [spark] viirya opened a new pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
viirya opened a new pull request #33975:
URL: https://github.com/apache/spark/pull/33975
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### What changes were proposed in this pull request?
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This patch proposes to adjust the current overhead of cached relation for DPP.
### Why are the changes needed?
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Currently we calculate if there is benefit of pruning with DPP by simply summing up the size of all scan relations as the overhead. However, for cached relations, the overhead should be different than a non-cached relation. This proposes to use adjusted overhead for cached relation with DPP.
### Does this PR introduce _any_ user-facing change?
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Yes.
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Added unit test.
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URL: https://github.com/apache/spark/pull/33975#issuecomment-918042531
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[GitHub] [spark] viirya commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r707494550
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/PartitionPruning.scala
##########
@@ -177,6 +177,26 @@ object PartitionPruning extends Rule[LogicalPlan] with PredicateHelper with Join
}
}
+ /**
+ * Calculates a heuristic overhead of a logical plan. Normally it returns the total
+ * size in bytes of all scan relations. We don't count in-memory relation which uses
+ * memory.
+ */
+ private def calculatePlanOverhead(plan: LogicalPlan): Float = {
+ val (cached, notCached) = plan.collectLeaves().partition(p => p match {
+ case _: InMemoryRelation => true
+ case _ => false
+ })
+ val scanOverhead = notCached.map(_.stats.sizeInBytes).sum.toFloat
+ val cachedOverhead = cached.map {
+ case m: InMemoryRelation if m.cacheBuilder.storageLevel.useDisk =>
+ m.stats.sizeInBytes.toFloat * 0.2
Review comment:
Oh, I forgot that these two flags are not exclusive.
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[GitHub] [spark] viirya commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r709327455
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/PartitionPruning.scala
##########
@@ -177,6 +177,29 @@ object PartitionPruning extends Rule[LogicalPlan] with PredicateHelper with Join
}
}
+ /**
+ * Calculates a heuristic overhead of a logical plan. Normally it returns the total
+ * size in bytes of all scan relations. We don't count in-memory relation which uses
+ * only memory.
+ */
+ private def calculatePlanOverhead(plan: LogicalPlan): Float = {
+ val (cached, notCached) = plan.collectLeaves().partition(p => p match {
+ case _: InMemoryRelation => true
+ case _ => false
+ })
+ val scanOverhead = notCached.map(_.stats.sizeInBytes).sum.toFloat
+ val cachedOverhead = cached.map {
+ case m: InMemoryRelation if m.cacheBuilder.storageLevel.useDisk &&
+ !m.cacheBuilder.storageLevel.useMemory =>
+ m.stats.sizeInBytes.toFloat * 0.5
Review comment:
Per disk cache, I thought it could be treated as slightly lighter than original table scan. But I'm okay to remove the 0.5 here too.
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[GitHub] [spark] viirya commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r709327455
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/PartitionPruning.scala
##########
@@ -177,6 +177,29 @@ object PartitionPruning extends Rule[LogicalPlan] with PredicateHelper with Join
}
}
+ /**
+ * Calculates a heuristic overhead of a logical plan. Normally it returns the total
+ * size in bytes of all scan relations. We don't count in-memory relation which uses
+ * only memory.
+ */
+ private def calculatePlanOverhead(plan: LogicalPlan): Float = {
+ val (cached, notCached) = plan.collectLeaves().partition(p => p match {
+ case _: InMemoryRelation => true
+ case _ => false
+ })
+ val scanOverhead = notCached.map(_.stats.sizeInBytes).sum.toFloat
+ val cachedOverhead = cached.map {
+ case m: InMemoryRelation if m.cacheBuilder.storageLevel.useDisk &&
+ !m.cacheBuilder.storageLevel.useMemory =>
+ m.stats.sizeInBytes.toFloat * 0.5
Review comment:
Per disk cache, I thought it could be treated as slightly light than original table scan. But I'm okay to remove the 0.5 here too.
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[GitHub] [spark] viirya commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on pull request #33975:
URL: https://github.com/apache/spark/pull/33975#issuecomment-920109713
@cloud-fan Any more comments? Thanks.
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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r709790654
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
##########
@@ -468,30 +468,68 @@ abstract class DynamicPartitionPruningSuiteBase
Given("no stats and selective predicate with the size of dim too large")
withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true",
SQLConf.DYNAMIC_PARTITION_PRUNING_USE_STATS.key -> "true") {
- sql(
- """
- |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
- |FROM fact_sk f WHERE store_id < 5
+ withTable("fact_aux") {
+ sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_sk f WHERE store_id < 5
+ """.stripMargin)
+ .write
+ .partitionBy("store_id")
+ .saveAsTable("fact_aux")
+
+ val df = sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_aux f JOIN dim_store s
+ |ON f.store_id = s.store_id WHERE s.country = 'US'
""".stripMargin)
- .write
- .partitionBy("store_id")
- .saveAsTable("fact_aux")
- val df = sql(
- """
- |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
- |FROM fact_aux f JOIN dim_store s
- |ON f.store_id = s.store_id WHERE s.country = 'US'
+ checkPartitionPruningPredicate(df, false, false)
+
+ checkAnswer(df,
+ Row(1070, 2, 10, 4) ::
+ Row(1080, 3, 20, 4) ::
+ Row(1090, 3, 10, 4) ::
+ Row(1100, 3, 10, 4) :: Nil
+ )
+ }
+ }
+
+ Given("no stats and selective predicate with the size of dim too large but cached")
+ withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true",
+ SQLConf.DYNAMIC_PARTITION_PRUNING_USE_STATS.key -> "true") {
+ withTable("fact_aux") {
+ withTempView("cached_dim_store") {
+ sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_sk f WHERE store_id < 5
""".stripMargin)
Review comment:
ditto
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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r709790825
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
##########
@@ -468,30 +468,68 @@ abstract class DynamicPartitionPruningSuiteBase
Given("no stats and selective predicate with the size of dim too large")
withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true",
SQLConf.DYNAMIC_PARTITION_PRUNING_USE_STATS.key -> "true") {
- sql(
- """
- |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
- |FROM fact_sk f WHERE store_id < 5
+ withTable("fact_aux") {
+ sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_sk f WHERE store_id < 5
+ """.stripMargin)
+ .write
+ .partitionBy("store_id")
+ .saveAsTable("fact_aux")
+
+ val df = sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_aux f JOIN dim_store s
+ |ON f.store_id = s.store_id WHERE s.country = 'US'
""".stripMargin)
- .write
- .partitionBy("store_id")
- .saveAsTable("fact_aux")
- val df = sql(
- """
- |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
- |FROM fact_aux f JOIN dim_store s
- |ON f.store_id = s.store_id WHERE s.country = 'US'
+ checkPartitionPruningPredicate(df, false, false)
+
+ checkAnswer(df,
+ Row(1070, 2, 10, 4) ::
+ Row(1080, 3, 20, 4) ::
+ Row(1090, 3, 10, 4) ::
+ Row(1100, 3, 10, 4) :: Nil
+ )
+ }
+ }
+
+ Given("no stats and selective predicate with the size of dim too large but cached")
+ withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true",
+ SQLConf.DYNAMIC_PARTITION_PRUNING_USE_STATS.key -> "true") {
+ withTable("fact_aux") {
+ withTempView("cached_dim_store") {
+ sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_sk f WHERE store_id < 5
""".stripMargin)
+ .write
+ .partitionBy("store_id")
+ .saveAsTable("fact_aux")
- checkPartitionPruningPredicate(df, false, false)
+ spark.table("dim_store").cache()
+ .createOrReplaceTempView("cached_dim_store")
- checkAnswer(df,
- Row(1070, 2, 10, 4) ::
- Row(1080, 3, 20, 4) ::
- Row(1090, 3, 10, 4) ::
- Row(1100, 3, 10, 4) :: Nil
- )
+ val df = sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_aux f JOIN cached_dim_store s
+ |ON f.store_id = s.store_id WHERE s.country = 'US'
+ """.stripMargin)
Review comment:
ditto.
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Posted by GitBox <gi...@apache.org>.
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[GitHub] [spark] SparkQA commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/33975#issuecomment-917860201
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[GitHub] [spark] SparkQA commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
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[GitHub] [spark] dongjoon-hyun edited a comment on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun edited a comment on pull request #33975:
URL: https://github.com/apache/spark/pull/33975#issuecomment-920591367
+1, late LGTM. Only four indentation nit issues.
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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r709789991
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
##########
@@ -468,30 +468,68 @@ abstract class DynamicPartitionPruningSuiteBase
Given("no stats and selective predicate with the size of dim too large")
withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true",
SQLConf.DYNAMIC_PARTITION_PRUNING_USE_STATS.key -> "true") {
- sql(
- """
- |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
- |FROM fact_sk f WHERE store_id < 5
+ withTable("fact_aux") {
+ sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_sk f WHERE store_id < 5
+ """.stripMargin)
Review comment:
indentation?
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[GitHub] [spark] viirya commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on pull request #33975:
URL: https://github.com/apache/spark/pull/33975#issuecomment-920371852
Thanks! Merging to master.
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[GitHub] [spark] viirya commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on pull request #33975:
URL: https://github.com/apache/spark/pull/33975#issuecomment-917926607
cc @cloud-fan
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[GitHub] [spark] SparkQA commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
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URL: https://github.com/apache/spark/pull/33975#issuecomment-918377571
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[GitHub] [spark] viirya commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on pull request #33975:
URL: https://github.com/apache/spark/pull/33975#issuecomment-918382760
retest this please
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[GitHub] [spark] viirya closed pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya closed pull request #33975:
URL: https://github.com/apache/spark/pull/33975
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[GitHub] [spark] cloud-fan commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r707095930
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/PartitionPruning.scala
##########
@@ -177,6 +177,26 @@ object PartitionPruning extends Rule[LogicalPlan] with PredicateHelper with Join
}
}
+ /**
+ * Calculates a heuristic overhead of a logical plan. Normally it returns the total
+ * size in bytes of all scan relations. We don't count in-memory relation which uses
+ * memory.
+ */
+ private def calculatePlanOverhead(plan: LogicalPlan): Float = {
+ val (cached, notCached) = plan.collectLeaves().partition(p => p match {
+ case _: InMemoryRelation => true
+ case _ => false
+ })
+ val scanOverhead = notCached.map(_.stats.sizeInBytes).sum.toFloat
+ val cachedOverhead = cached.map {
+ case m: InMemoryRelation if m.cacheBuilder.storageLevel.useDisk =>
+ m.stats.sizeInBytes.toFloat * 0.2
Review comment:
shall we consider the percentage of data that are on disk?
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[GitHub] [spark] viirya commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r707016645
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/PartitionPruning.scala
##########
@@ -177,6 +177,26 @@ object PartitionPruning extends Rule[LogicalPlan] with PredicateHelper with Join
}
}
+ /**
+ * Calculates a heuristic overhead of a logical plan. Normally it returns the total
+ * size in bytes of all scan relations. We don't count in-memory relation which uses
+ * memory.
+ */
+ private def calculatePlanOverhead(plan: LogicalPlan): Float = {
+ val (cached, notCached) = plan.collectLeaves().partition(p => p match {
+ case _: InMemoryRelation => true
+ case _ => false
+ })
+ val scanOverhead = notCached.map(_.stats.sizeInBytes).sum.toFloat
+ val cachedOverhead = cached.map {
+ case m: InMemoryRelation if m.cacheBuilder.storageLevel.useDisk =>
+ m.stats.sizeInBytes.toFloat * 0.2
+ case m: InMemoryRelation if m.cacheBuilder.storageLevel.useMemory =>
+ 0.0
Review comment:
This is just heuristic values. Open to change it. Maybe it can be configurable?
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[GitHub] [spark] cloud-fan commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r709316271
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/dynamicpruning/PartitionPruning.scala
##########
@@ -177,6 +177,29 @@ object PartitionPruning extends Rule[LogicalPlan] with PredicateHelper with Join
}
}
+ /**
+ * Calculates a heuristic overhead of a logical plan. Normally it returns the total
+ * size in bytes of all scan relations. We don't count in-memory relation which uses
+ * only memory.
+ */
+ private def calculatePlanOverhead(plan: LogicalPlan): Float = {
+ val (cached, notCached) = plan.collectLeaves().partition(p => p match {
+ case _: InMemoryRelation => true
+ case _ => false
+ })
+ val scanOverhead = notCached.map(_.stats.sizeInBytes).sum.toFloat
+ val cachedOverhead = cached.map {
+ case m: InMemoryRelation if m.cacheBuilder.storageLevel.useDisk &&
+ !m.cacheBuilder.storageLevel.useMemory =>
+ m.stats.sizeInBytes.toFloat * 0.5
Review comment:
for disk-only cache, I think we should treat it as a parquet table scan? then we shouldn't add the `* 0.5`
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[GitHub] [spark] SparkQA removed a comment on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
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[GitHub] [spark] dongjoon-hyun commented on a change in pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on a change in pull request #33975:
URL: https://github.com/apache/spark/pull/33975#discussion_r709790100
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
##########
@@ -468,30 +468,68 @@ abstract class DynamicPartitionPruningSuiteBase
Given("no stats and selective predicate with the size of dim too large")
withSQLConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED.key -> "true",
SQLConf.DYNAMIC_PARTITION_PRUNING_USE_STATS.key -> "true") {
- sql(
- """
- |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
- |FROM fact_sk f WHERE store_id < 5
+ withTable("fact_aux") {
+ sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_sk f WHERE store_id < 5
+ """.stripMargin)
+ .write
+ .partitionBy("store_id")
+ .saveAsTable("fact_aux")
+
+ val df = sql(
+ """
+ |SELECT f.date_id, f.product_id, f.units_sold, f.store_id
+ |FROM fact_aux f JOIN dim_store s
+ |ON f.store_id = s.store_id WHERE s.country = 'US'
""".stripMargin)
Review comment:
ditto. indentation?
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[GitHub] [spark] dongjoon-hyun commented on pull request #33975: [SPARK-36735][SQL] Adjust overhead of cached relation for DPP
Posted by GitBox <gi...@apache.org>.
dongjoon-hyun commented on pull request #33975:
URL: https://github.com/apache/spark/pull/33975#issuecomment-920591367
+1, late LGTM. Only four indentation nit issue.
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