spark-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Michael Shtelma <mshte...@gmail.com>
Subject Re: Using CBO on Spark 2.3 with analyzed hive tables
Date Fri, 23 Mar 2018 16:23:42 GMT
Hi Maropu,

the problem seems to be in FilterEstimation.scala on lines 50 and 52:
https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/FilterEstimation.scala?utf8=✓#L50-L52

val filterSelectivity =
calculateFilterSelectivity(plan.condition).getOrElse(1.0)
val filteredRowCount: BigInt =
ceil(BigDecimal(childStats.rowCount.get) * filterSelectivity)

The problem is, that filterSelectivity gets NaN value in my case and
NaN cannot be converted to BigDecimal.
I can try adding simple if, checking the NaN value and test if this helps.
I will also try to understand, why in my case, I am getting NaN.

Best,
Michael


On Fri, Mar 23, 2018 at 1:51 PM, Takeshi Yamamuro <linguin.m.s@gmail.com> wrote:
> hi,
>
> What's a query to reproduce this?
> It seems when casting double to BigDecimal, it throws the exception.
>
> // maropu
>
> On Fri, Mar 23, 2018 at 6:20 PM, Michael Shtelma <mshtelma@gmail.com> wrote:
>>
>> Hi all,
>>
>> I am using Spark 2.3 with activated cost-based optimizer and a couple
>> of hive tables, that were analyzed previously.
>>
>> I am getting the following exception for different queries:
>>
>> java.lang.NumberFormatException
>>
>> at java.math.BigDecimal.<init>(BigDecimal.java:494)
>>
>> at java.math.BigDecimal.<init>(BigDecimal.java:824)
>>
>> at scala.math.BigDecimal$.decimal(BigDecimal.scala:52)
>>
>> at scala.math.BigDecimal$.decimal(BigDecimal.scala:55)
>>
>> at scala.math.BigDecimal$.double2bigDecimal(BigDecimal.scala:343)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.FilterEstimation.estimate(FilterEstimation.scala:52)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.BasicStatsPlanVisitor$.visitFilter(BasicStatsPlanVisitor.scala:43)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.BasicStatsPlanVisitor$.visitFilter(BasicStatsPlanVisitor.scala:25)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.LogicalPlanVisitor$class.visit(LogicalPlanVisitor.scala:30)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.BasicStatsPlanVisitor$.visit(BasicStatsPlanVisitor.scala:25)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.LogicalPlanStats$$anonfun$stats$1.apply(LogicalPlanStats.scala:35)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.LogicalPlanStats$$anonfun$stats$1.apply(LogicalPlanStats.scala:33)
>>
>> at scala.Option.getOrElse(Option.scala:121)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.LogicalPlanStats$class.stats(LogicalPlanStats.scala:33)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.stats(LogicalPlan.scala:30)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.EstimationUtils$$anonfun$rowCountsExist$1.apply(EstimationUtils.scala:32)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.EstimationUtils$$anonfun$rowCountsExist$1.apply(EstimationUtils.scala:32)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.prefixLengthImpl(IndexedSeqOptimized.scala:38)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.forall(IndexedSeqOptimized.scala:43)
>>
>> at scala.collection.mutable.WrappedArray.forall(WrappedArray.scala:35)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.EstimationUtils$.rowCountsExist(EstimationUtils.scala:32)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.ProjectEstimation$.estimate(ProjectEstimation.scala:27)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.BasicStatsPlanVisitor$.visitProject(BasicStatsPlanVisitor.scala:63)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.BasicStatsPlanVisitor$.visitProject(BasicStatsPlanVisitor.scala:25)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.LogicalPlanVisitor$class.visit(LogicalPlanVisitor.scala:37)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.BasicStatsPlanVisitor$.visit(BasicStatsPlanVisitor.scala:25)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.LogicalPlanStats$$anonfun$stats$1.apply(LogicalPlanStats.scala:35)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.LogicalPlanStats$$anonfun$stats$1.apply(LogicalPlanStats.scala:33)
>>
>> at scala.Option.getOrElse(Option.scala:121)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.statsEstimation.LogicalPlanStats$class.stats(LogicalPlanStats.scala:33)
>>
>> at
>> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.stats(LogicalPlan.scala:30)
>>
>> at
>> org.apache.spark.sql.catalyst.optimizer.CostBasedJoinReorder$$anonfun$2.apply(CostBasedJoinReorder.scala:64)
>>
>> at
>> org.apache.spark.sql.catalyst.optimizer.CostBasedJoinReorder$$anonfun$2.apply(CostBasedJoinReorder.scala:64)
>>
>> at
>> scala.collection.LinearSeqOptimized$class.forall(LinearSeqOptimized.scala:83)
>>
>> at scala.collection.immutable.List.forall(List.scala:84)
>>
>> at
>> org.apache.spark.sql.catalyst.optimizer.CostBasedJoinReorder$.org$apache$spark$sql$catalyst$optimizer$CostBasedJoinReorder$$reorder(CostBasedJoinReorder.scala:64)
>>
>> at
>> org.apache.spark.sql.catalyst.optimizer.CostBasedJoinReorder$$anonfun$1.applyOrElse(CostBasedJoinReorder.scala:46)
>>
>> at
>> org.apache.spark.sql.catalyst.optimizer.CostBasedJoinReorder$$anonfun$1.applyOrElse(CostBasedJoinReorder.scala:43)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4$$anonfun$apply$11.apply(TreeNode.scala:335)
>>
>> at
>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>>
>> at
>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>>
>> at scala.collection.immutable.List.foreach(List.scala:392)
>>
>> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
>>
>> at scala.collection.immutable.List.map(List.scala:296)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:333)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4$$anonfun$apply$11.apply(TreeNode.scala:335)
>>
>> at
>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>>
>> at
>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>>
>> at scala.collection.immutable.List.foreach(List.scala:392)
>>
>> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
>>
>> at scala.collection.immutable.List.map(List.scala:296)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:333)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304)
>>
>> at
>> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:272)
>>
>> at
>> org.apache.spark.sql.catalyst.optimizer.CostBasedJoinReorder$.apply(CostBasedJoinReorder.scala:43)
>>
>> at
>> org.apache.spark.sql.catalyst.optimizer.CostBasedJoinReorder$.apply(CostBasedJoinReorder.scala:35)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:87)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:84)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)
>>
>> at scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:35)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:84)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:76)
>>
>> at scala.collection.immutable.List.foreach(List.scala:392)
>>
>> at
>> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:76)
>>
>> at
>> org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:66)
>>
>> at
>> org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:66)
>>
>> at
>> org.apache.spark.sql.execution.QueryExecution$$anonfun$toString$2.apply(QueryExecution.scala:204)
>>
>> at
>> org.apache.spark.sql.execution.QueryExecution$$anonfun$toString$2.apply(QueryExecution.scala:204)
>>
>> at
>> org.apache.spark.sql.execution.QueryExecution.stringOrError(QueryExecution.scala:100)
>>
>> at
>> org.apache.spark.sql.execution.QueryExecution.toString(QueryExecution.scala:204)
>>
>> at
>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:74)
>>
>> at
>> org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:654)
>>
>> at
>> org.apache.spark.sql.DataFrameWriter.createTable(DataFrameWriter.scala:458)
>>
>> at
>> org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:437)
>>
>> at
>> org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:393)
>>
>>
>>
>> This exception only comes, if the statistics exist for the hive tables
>> being used.
>>
>> Has anybody already seen something like this ?
>> Any assistance would be greatly appreciated!
>>
>> Best,
>> Michael
>>
>> ---------------------------------------------------------------------
>> To unsubscribe e-mail: user-unsubscribe@spark.apache.org
>>
>
>
>
> --
> ---
> Takeshi Yamamuro

---------------------------------------------------------------------
To unsubscribe e-mail: user-unsubscribe@spark.apache.org


Mime
View raw message