I don't think we implement INTERSECT ALL or EXCEPT ALL; only UNION ALL. I modified JdbcFrontLinqBackTest.testIntersect() and got a similar problem.
See https://issues.apache.org/jira/browse/CALCITE-1446. On Fri, Feb 9, 2018 at 2:17 PM, Alessandro Solimando <[email protected]> wrote: > Hello, > I am currently extending the unit tests for SparkAdapter. > > The following query raises an exception from the query planner, who fails to > come up with a plan (getBestPlan call is null). > >> >> select * >> >> from (values (1, 'a'), (2, 'b')) as t(x, y) >> >> >> >> intersect all >> >> >> >> select * >> from (values (1, 'a'), (2, 'b'), (1, 'b'), (2, 'c'), (2, 'c')) as t(x, y) > > > Note that the exact same query *without* "all" works fine. > > If you want to have a quick look here is my branch: > https://github.com/asolimando/calcite/tree/SPARK-TESTS > > I have started to compare the two executions by tracing which rules are > matching and which (equivalent) relations they generate, and there are > several rules not matched for "interesect all" case, compared to > "intersect", as you can see from the two traces in attachment. > > Depending on the kind of rules this might make sense, as the two queries > differ for duplicate values, and this might prevent some rules to trigger. > > I am still getting acquainted with Calcite's internals, so before digging > too much I preferred to get back to you for: > > 1) Does this relate to any known issue, or should I open a JIRA ticket? > 2) Do you have any suggestion on what to add to the trace? > At the moment the traces show: > the current rule tested in OPTIMIZE phase > TAB content of rule queue > 2xTAB all the relations for all the existing sets (to understand what is > created by each rule) > > Below the full stacktrace: > >>> java.lang.RuntimeException: With materializationsEnabled=false, limit=0 >>> >>> at >>> org.apache.calcite.test.CalciteAssert.assertQuery(CalciteAssert.java:600) >>> >>> at >>> org.apache.calcite.test.CalciteAssert$AssertQuery.returns(CalciteAssert.java:1346) >>> >>> at >>> org.apache.calcite.test.CalciteAssert$AssertQuery.returns(CalciteAssert.java:1329) >>> >>> at >>> org.apache.calcite.test.CalciteAssert$AssertQuery.returnsUnordered(CalciteAssert.java:1357) >>> >>> at >>> org.apache.calcite.test.SparkAdapterTest.commonTester(SparkAdapterTest.java:88) >>> >>> at >>> org.apache.calcite.test.SparkAdapterTest.testIntersectAll(SparkAdapterTest.java:227) >>> >>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >>> >>> at >>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) >>> >>> at >>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >>> >>> at java.lang.reflect.Method.invoke(Method.java:498) >>> >>> at >>> org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50) >>> >>> at >>> org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12) >>> >>> at >>> org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47) >>> >>> at >>> org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17) >>> >>> at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325) >>> >>> at >>> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78) >>> >>> at >>> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57) >>> >>> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290) >>> >>> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71) >>> >>> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288) >>> >>> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58) >>> >>> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268) >>> >>> at org.junit.runners.ParentRunner.run(ParentRunner.java:363) >>> >>> at org.junit.runner.JUnitCore.run(JUnitCore.java:137) >>> >>> at >>> com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:68) >>> >>> at >>> com.intellij.rt.execution.junit.IdeaTestRunner$Repeater.startRunnerWithArgs(IdeaTestRunner.java:47) >>> >>> at >>> com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:242) >>> >>> at >>> com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStarter.java:70) >>> >>> Caused by: java.sql.SQLException: Error while executing SQL "select * >>> >>> from (values (1, 'a'), (2, 'b')) as t(x, y) >>> >>> intersect all >>> >>> select * >>> >>> from (values (1, 'a'), (2, 'b'), (1, 'b'), (2, 'c'), (2, 'c')) as t(x, >>> y)": Node [rel#18:Subset#4.ENUMERABLE.[]] could not be implemented; planner >>> state: >>> >>> >>> Root: rel#18:Subset#4.ENUMERABLE.[] >>> >>> Original rel: >>> >>> LogicalIntersect(subset=[rel#18:Subset#4.ENUMERABLE.[]], all=[true]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 2.0 cpu, 0.0 io}, id = 13 >>> >>> LogicalProject(subset=[rel#9:Subset#1.NONE.[]], X=[$0], Y=[$1]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 4.0 cpu, 0.0 io}, id = 8 >>> >>> LogicalValues(subset=[rel#7:Subset#0.NONE.[]], tuples=[[{ 1, 'a' }, { >>> 2, 'b' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, >>> id = 1 >>> >>> LogicalProject(subset=[rel#12:Subset#3.NONE.[1]], X=[$0], Y=[$1]): >>> rowcount = 5.0, cumulative cost = {5.0 rows, 10.0 cpu, 0.0 io}, id = 11 >>> >>> LogicalValues(subset=[rel#10:Subset#2.NONE.[1]], tuples=[[{ 1, 'a' }, >>> { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]]): rowcount = 5.0, >>> cumulative cost = {5.0 rows, 1.0 cpu, 0.0 io}, id = 4 >>> >>> >>> Sets: >>> >>> Set#0, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#7:Subset#0.NONE.[], best=null, importance=0.81 >>> >>> rel#1:LogicalValues.NONE.[[0, 1], [1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative cost={inf} >>> >>> rel#8:LogicalProject.NONE.[[0, 1], >>> [1]](input=rel#7:Subset#0.NONE.[],X=$0,Y=$1), rowcount=2.0, cumulative >>> cost={inf} >>> >>> rel#21:Subset#0.ENUMERABLE.[], best=rel#25, importance=0.4510687500000001 >>> >>> >>> rel#22:EnumerableProject.ENUMERABLE.[](input=rel#21:Subset#0.ENUMERABLE.[],X=$0,Y=$1), >>> rowcount=2.0, cumulative cost={4.0 rows, 5.0 cpu, 0.0 io} >>> >>> rel#25:EnumerableValues.ENUMERABLE.[[0, 1], [1]](type=RecordType(INTEGER >>> X, CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative >>> cost={2.0 rows, 1.0 cpu, 0.0 io} >>> >>> Set#2, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#10:Subset#2.NONE.[1], best=null, importance=0.81 >>> >>> rel#4:LogicalValues.NONE.[[1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]), >>> rowcount=5.0, cumulative cost={inf} >>> >>> >>> rel#11:LogicalProject.NONE.[[1]](input=rel#10:Subset#2.NONE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={inf} >>> >>> rel#24:Subset#2.ENUMERABLE.[1], best=rel#23, >>> importance=0.4510687500000001 >>> >>> rel#23:EnumerableValues.ENUMERABLE.[[1]](type=RecordType(INTEGER X, >>> CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' >>> }]), rowcount=5.0, cumulative cost={5.0 rows, 1.0 cpu, 0.0 io} >>> >>> >>> rel#26:EnumerableProject.ENUMERABLE.[[1]](input=rel#24:Subset#2.ENUMERABLE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={10.0 rows, 11.0 cpu, 0.0 io} >>> >>> Set#4, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#14:Subset#4.NONE.[], best=null, importance=0.9 >>> >>> >>> rel#13:LogicalIntersect.NONE.[](input#0=rel#7:Subset#0.NONE.[],input#1=rel#10:Subset#2.NONE.[1],all=true), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#17:AbstractConverter.NONE.[](input=rel#15:Subset#4.SPARK.[],convention=NONE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> rel#15:Subset#4.SPARK.[], best=null, importance=0.81 >>> >>> rel#18:Subset#4.ENUMERABLE.[], best=null, importance=1.0 >>> >>> >>> rel#19:AbstractConverter.ENUMERABLE.[](input=rel#14:Subset#4.NONE.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#20:AbstractConverter.ENUMERABLE.[](input=rel#15:Subset#4.SPARK.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> >>> at org.apache.calcite.avatica.Helper.createException(Helper.java:56) >>> >>> at org.apache.calcite.avatica.Helper.createException(Helper.java:41) >>> >>> at >>> org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:156) >>> >>> at >>> org.apache.calcite.avatica.AvaticaStatement.executeQuery(AvaticaStatement.java:218) >>> >>> at >>> org.apache.calcite.test.CalciteAssert.assertQuery(CalciteAssert.java:568) >>> >>> ... 27 more >>> >>> Caused by: org.apache.calcite.plan.RelOptPlanner$CannotPlanException: >>> Node [rel#18:Subset#4.ENUMERABLE.[]] could not be implemented; planner >>> state: >>> >>> >>> Root: rel#18:Subset#4.ENUMERABLE.[] >>> >>> Original rel: >>> >>> LogicalIntersect(subset=[rel#18:Subset#4.ENUMERABLE.[]], all=[true]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 2.0 cpu, 0.0 io}, id = 13 >>> >>> LogicalProject(subset=[rel#9:Subset#1.NONE.[]], X=[$0], Y=[$1]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 4.0 cpu, 0.0 io}, id = 8 >>> >>> LogicalValues(subset=[rel#7:Subset#0.NONE.[]], tuples=[[{ 1, 'a' }, { >>> 2, 'b' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, >>> id = 1 >>> >>> LogicalProject(subset=[rel#12:Subset#3.NONE.[1]], X=[$0], Y=[$1]): >>> rowcount = 5.0, cumulative cost = {5.0 rows, 10.0 cpu, 0.0 io}, id = 11 >>> >>> LogicalValues(subset=[rel#10:Subset#2.NONE.[1]], tuples=[[{ 1, 'a' }, >>> { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]]): rowcount = 5.0, >>> cumulative cost = {5.0 rows, 1.0 cpu, 0.0 io}, id = 4 >>> >>> >>> Sets: >>> >>> Set#0, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#7:Subset#0.NONE.[], best=null, importance=0.81 >>> >>> rel#1:LogicalValues.NONE.[[0, 1], [1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative cost={inf} >>> >>> rel#8:LogicalProject.NONE.[[0, 1], >>> [1]](input=rel#7:Subset#0.NONE.[],X=$0,Y=$1), rowcount=2.0, cumulative >>> cost={inf} >>> >>> rel#21:Subset#0.ENUMERABLE.[], best=rel#25, importance=0.4510687500000001 >>> >>> >>> rel#22:EnumerableProject.ENUMERABLE.[](input=rel#21:Subset#0.ENUMERABLE.[],X=$0,Y=$1), >>> rowcount=2.0, cumulative cost={4.0 rows, 5.0 cpu, 0.0 io} >>> >>> rel#25:EnumerableValues.ENUMERABLE.[[0, 1], [1]](type=RecordType(INTEGER >>> X, CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative >>> cost={2.0 rows, 1.0 cpu, 0.0 io} >>> >>> Set#2, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#10:Subset#2.NONE.[1], best=null, importance=0.81 >>> >>> rel#4:LogicalValues.NONE.[[1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]), >>> rowcount=5.0, cumulative cost={inf} >>> >>> >>> rel#11:LogicalProject.NONE.[[1]](input=rel#10:Subset#2.NONE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={inf} >>> >>> rel#24:Subset#2.ENUMERABLE.[1], best=rel#23, >>> importance=0.4510687500000001 >>> >>> rel#23:EnumerableValues.ENUMERABLE.[[1]](type=RecordType(INTEGER X, >>> CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' >>> }]), rowcount=5.0, cumulative cost={5.0 rows, 1.0 cpu, 0.0 io} >>> >>> >>> rel#26:EnumerableProject.ENUMERABLE.[[1]](input=rel#24:Subset#2.ENUMERABLE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={10.0 rows, 11.0 cpu, 0.0 io} >>> >>> Set#4, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#14:Subset#4.NONE.[], best=null, importance=0.9 >>> >>> >>> rel#13:LogicalIntersect.NONE.[](input#0=rel#7:Subset#0.NONE.[],input#1=rel#10:Subset#2.NONE.[1],all=true), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#17:AbstractConverter.NONE.[](input=rel#15:Subset#4.SPARK.[],convention=NONE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> rel#15:Subset#4.SPARK.[], best=null, importance=0.81 >>> >>> rel#18:Subset#4.ENUMERABLE.[], best=null, importance=1.0 >>> >>> >>> rel#19:AbstractConverter.ENUMERABLE.[](input=rel#14:Subset#4.NONE.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#20:AbstractConverter.ENUMERABLE.[](input=rel#15:Subset#4.SPARK.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> >>> at >>> org.apache.calcite.plan.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:441) >>> >>> at >>> org.apache.calcite.plan.volcano.RelSubset.buildCheapestPlan(RelSubset.java:291) >>> >>> at >>> org.apache.calcite.plan.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:666) >>> >>> at org.apache.calcite.tools.Programs$5.run(Programs.java:326) >>> >>> at >>> org.apache.calcite.tools.Programs$SequenceProgram.run(Programs.java:387) >>> >>> at org.apache.calcite.prepare.Prepare.optimize(Prepare.java:188) >>> >>> at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:319) >>> >>> at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:230) >>> >>> at >>> org.apache.calcite.prepare.CalcitePrepareImpl.prepare2_(CalcitePrepareImpl.java:781) >>> >>> at >>> org.apache.calcite.prepare.CalcitePrepareImpl.prepare_(CalcitePrepareImpl.java:640) >>> >>> at >>> org.apache.calcite.prepare.CalcitePrepareImpl.prepareSql(CalcitePrepareImpl.java:610) >>> >>> at >>> org.apache.calcite.jdbc.CalciteConnectionImpl.parseQuery(CalciteConnectionImpl.java:221) >>> >>> at >>> org.apache.calcite.jdbc.CalciteMetaImpl.prepareAndExecute(CalciteMetaImpl.java:603) >>> >>> at >>> org.apache.calcite.avatica.AvaticaConnection.prepareAndExecuteInternal(AvaticaConnection.java:638) >>> >>> at >>> org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:149) >>> >>> ... 29 more >>> >>> >>> java.lang.RuntimeException: exception while executing [select * >>> >>> from (values (1, 'a'), (2, 'b')) as t(x, y) >>> >>> intersect all >>> >>> select * >>> >>> from (values (1, 'a'), (2, 'b'), (1, 'b'), (2, 'c'), (2, 'c')) as t(x, >>> y)] >>> >>> >>> at >>> org.apache.calcite.test.CalciteAssert$AssertQuery.returns(CalciteAssert.java:1351) >>> >>> at >>> org.apache.calcite.test.CalciteAssert$AssertQuery.returns(CalciteAssert.java:1329) >>> >>> at >>> org.apache.calcite.test.CalciteAssert$AssertQuery.returnsUnordered(CalciteAssert.java:1357) >>> >>> at >>> org.apache.calcite.test.SparkAdapterTest.commonTester(SparkAdapterTest.java:88) >>> >>> at >>> org.apache.calcite.test.SparkAdapterTest.testIntersectAll(SparkAdapterTest.java:227) >>> >>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >>> >>> at >>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) >>> >>> at >>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >>> >>> at java.lang.reflect.Method.invoke(Method.java:498) >>> >>> at >>> org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:50) >>> >>> at >>> org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12) >>> >>> at >>> org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:47) >>> >>> at >>> org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17) >>> >>> at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:325) >>> >>> at >>> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:78) >>> >>> at >>> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:57) >>> >>> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:290) >>> >>> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:71) >>> >>> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:288) >>> >>> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:58) >>> >>> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:268) >>> >>> at org.junit.runners.ParentRunner.run(ParentRunner.java:363) >>> >>> at org.junit.runner.JUnitCore.run(JUnitCore.java:137) >>> >>> at >>> com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:68) >>> >>> at >>> com.intellij.rt.execution.junit.IdeaTestRunner$Repeater.startRunnerWithArgs(IdeaTestRunner.java:47) >>> >>> at >>> com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:242) >>> >>> at >>> com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStarter.java:70) >>> >>> Caused by: java.lang.RuntimeException: With >>> materializationsEnabled=false, limit=0 >>> >>> at >>> org.apache.calcite.test.CalciteAssert.assertQuery(CalciteAssert.java:600) >>> >>> at >>> org.apache.calcite.test.CalciteAssert$AssertQuery.returns(CalciteAssert.java:1346) >>> >>> ... 26 more >>> >>> Caused by: java.sql.SQLException: Error while executing SQL "select * >>> >>> from (values (1, 'a'), (2, 'b')) as t(x, y) >>> >>> intersect all >>> >>> select * >>> >>> from (values (1, 'a'), (2, 'b'), (1, 'b'), (2, 'c'), (2, 'c')) as t(x, >>> y)": Node [rel#18:Subset#4.ENUMERABLE.[]] could not be implemented; planner >>> state: >>> >>> >>> Root: rel#18:Subset#4.ENUMERABLE.[] >>> >>> Original rel: >>> >>> LogicalIntersect(subset=[rel#18:Subset#4.ENUMERABLE.[]], all=[true]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 2.0 cpu, 0.0 io}, id = 13 >>> >>> LogicalProject(subset=[rel#9:Subset#1.NONE.[]], X=[$0], Y=[$1]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 4.0 cpu, 0.0 io}, id = 8 >>> >>> LogicalValues(subset=[rel#7:Subset#0.NONE.[]], tuples=[[{ 1, 'a' }, { >>> 2, 'b' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, >>> id = 1 >>> >>> LogicalProject(subset=[rel#12:Subset#3.NONE.[1]], X=[$0], Y=[$1]): >>> rowcount = 5.0, cumulative cost = {5.0 rows, 10.0 cpu, 0.0 io}, id = 11 >>> >>> LogicalValues(subset=[rel#10:Subset#2.NONE.[1]], tuples=[[{ 1, 'a' }, >>> { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]]): rowcount = 5.0, >>> cumulative cost = {5.0 rows, 1.0 cpu, 0.0 io}, id = 4 >>> >>> >>> Sets: >>> >>> Set#0, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#7:Subset#0.NONE.[], best=null, importance=0.81 >>> >>> rel#1:LogicalValues.NONE.[[0, 1], [1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative cost={inf} >>> >>> rel#8:LogicalProject.NONE.[[0, 1], >>> [1]](input=rel#7:Subset#0.NONE.[],X=$0,Y=$1), rowcount=2.0, cumulative >>> cost={inf} >>> >>> rel#21:Subset#0.ENUMERABLE.[], best=rel#25, importance=0.4510687500000001 >>> >>> >>> rel#22:EnumerableProject.ENUMERABLE.[](input=rel#21:Subset#0.ENUMERABLE.[],X=$0,Y=$1), >>> rowcount=2.0, cumulative cost={4.0 rows, 5.0 cpu, 0.0 io} >>> >>> rel#25:EnumerableValues.ENUMERABLE.[[0, 1], [1]](type=RecordType(INTEGER >>> X, CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative >>> cost={2.0 rows, 1.0 cpu, 0.0 io} >>> >>> Set#2, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#10:Subset#2.NONE.[1], best=null, importance=0.81 >>> >>> rel#4:LogicalValues.NONE.[[1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]), >>> rowcount=5.0, cumulative cost={inf} >>> >>> >>> rel#11:LogicalProject.NONE.[[1]](input=rel#10:Subset#2.NONE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={inf} >>> >>> rel#24:Subset#2.ENUMERABLE.[1], best=rel#23, >>> importance=0.4510687500000001 >>> >>> rel#23:EnumerableValues.ENUMERABLE.[[1]](type=RecordType(INTEGER X, >>> CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' >>> }]), rowcount=5.0, cumulative cost={5.0 rows, 1.0 cpu, 0.0 io} >>> >>> >>> rel#26:EnumerableProject.ENUMERABLE.[[1]](input=rel#24:Subset#2.ENUMERABLE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={10.0 rows, 11.0 cpu, 0.0 io} >>> >>> Set#4, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#14:Subset#4.NONE.[], best=null, importance=0.9 >>> >>> >>> rel#13:LogicalIntersect.NONE.[](input#0=rel#7:Subset#0.NONE.[],input#1=rel#10:Subset#2.NONE.[1],all=true), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#17:AbstractConverter.NONE.[](input=rel#15:Subset#4.SPARK.[],convention=NONE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> rel#15:Subset#4.SPARK.[], best=null, importance=0.81 >>> >>> rel#18:Subset#4.ENUMERABLE.[], best=null, importance=1.0 >>> >>> >>> rel#19:AbstractConverter.ENUMERABLE.[](input=rel#14:Subset#4.NONE.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#20:AbstractConverter.ENUMERABLE.[](input=rel#15:Subset#4.SPARK.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> >>> at org.apache.calcite.avatica.Helper.createException(Helper.java:56) >>> >>> at org.apache.calcite.avatica.Helper.createException(Helper.java:41) >>> >>> at >>> org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:156) >>> >>> at >>> org.apache.calcite.avatica.AvaticaStatement.executeQuery(AvaticaStatement.java:218) >>> >>> at >>> org.apache.calcite.test.CalciteAssert.assertQuery(CalciteAssert.java:568) >>> >>> ... 27 more >>> >>> Caused by: org.apache.calcite.plan.RelOptPlanner$CannotPlanException: >>> Node [rel#18:Subset#4.ENUMERABLE.[]] could not be implemented; planner >>> state: >>> >>> >>> Root: rel#18:Subset#4.ENUMERABLE.[] >>> >>> Original rel: >>> >>> LogicalIntersect(subset=[rel#18:Subset#4.ENUMERABLE.[]], all=[true]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 2.0 cpu, 0.0 io}, id = 13 >>> >>> LogicalProject(subset=[rel#9:Subset#1.NONE.[]], X=[$0], Y=[$1]): >>> rowcount = 2.0, cumulative cost = {2.0 rows, 4.0 cpu, 0.0 io}, id = 8 >>> >>> LogicalValues(subset=[rel#7:Subset#0.NONE.[]], tuples=[[{ 1, 'a' }, { >>> 2, 'b' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, >>> id = 1 >>> >>> LogicalProject(subset=[rel#12:Subset#3.NONE.[1]], X=[$0], Y=[$1]): >>> rowcount = 5.0, cumulative cost = {5.0 rows, 10.0 cpu, 0.0 io}, id = 11 >>> >>> LogicalValues(subset=[rel#10:Subset#2.NONE.[1]], tuples=[[{ 1, 'a' }, >>> { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]]): rowcount = 5.0, >>> cumulative cost = {5.0 rows, 1.0 cpu, 0.0 io}, id = 4 >>> >>> >>> Sets: >>> >>> Set#0, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#7:Subset#0.NONE.[], best=null, importance=0.81 >>> >>> rel#1:LogicalValues.NONE.[[0, 1], [1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative cost={inf} >>> >>> rel#8:LogicalProject.NONE.[[0, 1], >>> [1]](input=rel#7:Subset#0.NONE.[],X=$0,Y=$1), rowcount=2.0, cumulative >>> cost={inf} >>> >>> rel#21:Subset#0.ENUMERABLE.[], best=rel#25, importance=0.4510687500000001 >>> >>> >>> rel#22:EnumerableProject.ENUMERABLE.[](input=rel#21:Subset#0.ENUMERABLE.[],X=$0,Y=$1), >>> rowcount=2.0, cumulative cost={4.0 rows, 5.0 cpu, 0.0 io} >>> >>> rel#25:EnumerableValues.ENUMERABLE.[[0, 1], [1]](type=RecordType(INTEGER >>> X, CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }]), rowcount=2.0, cumulative >>> cost={2.0 rows, 1.0 cpu, 0.0 io} >>> >>> Set#2, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#10:Subset#2.NONE.[1], best=null, importance=0.81 >>> >>> rel#4:LogicalValues.NONE.[[1]](type=RecordType(INTEGER X, CHAR(1) >>> Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' }]), >>> rowcount=5.0, cumulative cost={inf} >>> >>> >>> rel#11:LogicalProject.NONE.[[1]](input=rel#10:Subset#2.NONE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={inf} >>> >>> rel#24:Subset#2.ENUMERABLE.[1], best=rel#23, >>> importance=0.4510687500000001 >>> >>> rel#23:EnumerableValues.ENUMERABLE.[[1]](type=RecordType(INTEGER X, >>> CHAR(1) Y),tuples=[{ 1, 'a' }, { 2, 'b' }, { 1, 'b' }, { 2, 'c' }, { 2, 'c' >>> }]), rowcount=5.0, cumulative cost={5.0 rows, 1.0 cpu, 0.0 io} >>> >>> >>> rel#26:EnumerableProject.ENUMERABLE.[[1]](input=rel#24:Subset#2.ENUMERABLE.[1],X=$0,Y=$1), >>> rowcount=5.0, cumulative cost={10.0 rows, 11.0 cpu, 0.0 io} >>> >>> Set#4, type: RecordType(INTEGER X, CHAR(1) Y) >>> >>> rel#14:Subset#4.NONE.[], best=null, importance=0.9 >>> >>> >>> rel#13:LogicalIntersect.NONE.[](input#0=rel#7:Subset#0.NONE.[],input#1=rel#10:Subset#2.NONE.[1],all=true), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#17:AbstractConverter.NONE.[](input=rel#15:Subset#4.SPARK.[],convention=NONE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> rel#15:Subset#4.SPARK.[], best=null, importance=0.81 >>> >>> rel#18:Subset#4.ENUMERABLE.[], best=null, importance=1.0 >>> >>> >>> rel#19:AbstractConverter.ENUMERABLE.[](input=rel#14:Subset#4.NONE.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> rel#20:AbstractConverter.ENUMERABLE.[](input=rel#15:Subset#4.SPARK.[],convention=ENUMERABLE,sort=[]), >>> rowcount=2.0, cumulative cost={inf} >>> >>> >>> >>> at >>> org.apache.calcite.plan.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:441) >>> >>> at >>> org.apache.calcite.plan.volcano.RelSubset.buildCheapestPlan(RelSubset.java:291) >>> >>> at >>> org.apache.calcite.plan.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:666) >>> >>> at org.apache.calcite.tools.Programs$5.run(Programs.java:326) >>> >>> at >>> org.apache.calcite.tools.Programs$SequenceProgram.run(Programs.java:387) >>> >>> at org.apache.calcite.prepare.Prepare.optimize(Prepare.java:188) >>> >>> at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:319) >>> >>> at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:230) >>> >>> at >>> org.apache.calcite.prepare.CalcitePrepareImpl.prepare2_(CalcitePrepareImpl.java:781) >>> >>> at >>> org.apache.calcite.prepare.CalcitePrepareImpl.prepare_(CalcitePrepareImpl.java:640) >>> >>> at >>> org.apache.calcite.prepare.CalcitePrepareImpl.prepareSql(CalcitePrepareImpl.java:610) >>> >>> at >>> org.apache.calcite.jdbc.CalciteConnectionImpl.parseQuery(CalciteConnectionImpl.java:221) >>> >>> at >>> org.apache.calcite.jdbc.CalciteMetaImpl.prepareAndExecute(CalciteMetaImpl.java:603) >>> >>> at >>> org.apache.calcite.avatica.AvaticaConnection.prepareAndExecuteInternal(AvaticaConnection.java:638) >>> >>> at >>> org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:149) >>> >>> ... 29 more > > > Best regards, > Alessandro
