Shuyi, The fix works for me. Thanks!
Regards, Anton On Thu, Mar 22, 2018 at 9:46 AM Anton Kedin <[email protected]> wrote: > I think we're talking about the same thing. In my case the index is also > not adjusted for the flattened row. And I also see the wrong field ordinal > which causes the same kind of mismatch, but it happens higher up in the > user land for me because of how we wrap Calcite code (I'm not working with > Calcite source at the moment). > > I will build the Calcite with your fix and will report if it fixes my > issue. Thanks for the help! > > Regards, > Anton > > > > On Thu, Mar 22, 2018 at 1:18 AM Shuyi Chen <[email protected]> wrote: > >> Also, you can try to patch in this PR to see if that fixes your issue, >> https://github.com/apache/calcite/pull/651. >> >> On Thu, Mar 22, 2018 at 12:14 AM, Shuyi Chen <[email protected]> wrote: >> >> > I think the following is what happened: >> > >> > Calcite is trying to remove all structured type in the plan right below, >> > so optimizer and codegen rules never have to deal with structured types. >> > >> > LogicalProject(EXPR$0=[ITEM($3, 1)]) >> > LogicalTableScan(table=[[CATALOG, SALES, DEPT_NESTED]]) >> > >> > First, it flatten the LogicalTableScan, and generate the following: >> > >> > LogicalProject(DEPTNO=[$0], NAME=[$1], TYPE=[$2.TYPE], DESC=[$2.DESC], >> > EMPLOYEES=[$3]) >> > LogicalTableScan(table=[[CATALOG, SALES, DEPT_NESTED]]) >> > >> > Then it tries to flatten "LogicalProject(EXPR$0=[ITEM($3, 1)])", and >> > generate the following: >> > >> > LogicalProject(EXPR$0$0=[ITEM($3, 1).EMPNO], EXPR$0$1=[ITEM($3, >> > 1).ENAME], EXPR$0$2=[ITEM($3, 1).SKILLS]) >> > >> > However, when it combines the 2 flattening results, it did not correctly >> > adjust the ordinal post-flattening, which should be $4 now, not $3. So >> this >> > cause the exception since it is a type mismatch. >> > >> > I think I've already developed a fix for this. Will create a PR to >> address >> > both issues. >> > >> > @Anton, although my test error and your issue look similar, I still >> can't >> > reproduce your case (mine throws an error). Can you create a test for >> it? >> > Thanks a lot. >> > >> > >> > >> > >> > >> > On Wed, Mar 21, 2018 at 9:31 PM, Anton Kedin <[email protected]> >> > wrote: >> > >> >> Shuyi, >> >> >> >> Thank you for looking into this. Can this error in your case be caused >> by >> >> a >> >> similar problem? E.g. SKILLRECORD gets flattened, then when you try to >> >> select employees[1] you get SKILLRECORD.DESC field instead of actual >> >> employees[1] because input ref index is not adjusted for the flattened >> >> SKILLRECORD? >> >> >> >> Thank you, >> >> Anton >> >> >> >> >> >> On Wed, Mar 21, 2018 at 8:53 PM Shuyi Chen <[email protected]> wrote: >> >> >> >> > Actually, the cause for my previous findings is: for the first case, >> >> > SqlToRelConverterTest introduce another LogicalProject >> (RelRoot.project) >> >> > after applying the SqlToRelConverter to remove fields that are not >> >> needed. >> >> > But this function does not work with Record type and flattened >> fields. >> >> It >> >> > simply projects the first several fields from input index-wise, and >> does >> >> > not take into account the flattening behavior. The second case does >> not >> >> > trigger the extra project because it's trivial. >> >> > >> >> > For your case, I tried below: >> >> > >> >> > MockTable deptNestedTable = >> >> > MockTable.create(this, salesSchema, "DEPT_NESTED", false, 4); >> >> > deptNestedTable.addColumn("DEPTNO", f.intType, true); >> >> > deptNestedTable.addColumn("NAME", f.varchar10Type); >> >> > deptNestedTable.addColumn("SKILLRECORD", f.skillRecordType); >> >> > deptNestedTable.addColumn("EMPLOYEES", f.empListType); >> >> > registerTable(deptNestedTable); >> >> > >> >> > Run the following test: >> >> > >> >> > @Test public void testArrayOfRecord() { >> >> > sql("select employees[1] from dept_nested").ok(); >> >> > } >> >> > >> >> > I am actually getting the following error when run: >> >> > >> >> > java.lang.AssertionError: type mismatch: >> >> > ref: >> >> > RecordType(INTEGER NOT NULL EMPNO, VARCHAR(10) CHARACTER SET >> >> "ISO-8859-1" >> >> > COLLATE "ISO-8859-1$en_US$primary" NOT NULL ENAME, >> >> RecordType(VARCHAR(10) >> >> > CHARACTER SET "ISO-8859-1" COLLATE "ISO-8859-1$en_US$primary" NOT >> NULL >> >> > TYPE, VARCHAR(20) CHARACTER SET "ISO-8859-1" COLLATE >> >> > "ISO-8859-1$en_US$primary" NOT NULL DESC) NOT NULL ARRAY NOT NULL >> >> SKILLS) >> >> > NOT NULL ARRAY NOT NULL >> >> > input: >> >> > VARCHAR(20) CHARACTER SET "ISO-8859-1" COLLATE >> >> "ISO-8859-1$en_US$primary" >> >> > NOT NULL >> >> > >> >> > at org.apache.calcite.util.Litmus$1.fail(Litmus.java:31) >> >> > at org.apache.calcite.plan.RelOptUtil.eq(RelOptUtil.java:1838) >> >> > at >> org.apache.calcite.rex.RexChecker.visitInputRef(RexChecker.java:125) >> >> > at >> org.apache.calcite.rex.RexChecker.visitInputRef(RexChecker.java:57) >> >> > at org.apache.calcite.rex.RexInputRef.accept(RexInputRef.java:112) >> >> > at org.apache.calcite.rex.RexChecker.visitCall(RexChecker.java:140) >> >> > at org.apache.calcite.rex.RexChecker.visitCall(RexChecker.java:57) >> >> > at org.apache.calcite.rex.RexCall.accept(RexCall.java:107) >> >> > at >> >> > >> >> > org.apache.calcite.rex.RexVisitorImpl.visitFieldAccess(RexVi >> >> sitorImpl.java:98) >> >> > at org.apache.calcite.rex.RexChecker.visitFieldAccess(RexChecke >> >> r.java:149) >> >> > at org.apache.calcite.rex.RexChecker.visitFieldAccess(RexChecke >> >> r.java:57) >> >> > at >> org.apache.calcite.rex.RexFieldAccess.accept(RexFieldAccess.java:81) >> >> > at org.apache.calcite.rel.core.Project.isValid(Project.java:187) >> >> > at org.apache.calcite.rel.core.Project.<init>(Project.java:84) >> >> > at >> >> > >> >> > org.apache.calcite.rel.logical.LogicalProject.<init>(Logical >> >> Project.java:65) >> >> > at >> >> > >> >> > org.apache.calcite.rel.logical.LogicalProject.create(Logical >> >> Project.java:120) >> >> > at >> >> > >> >> > org.apache.calcite.rel.logical.LogicalProject.create(Logical >> >> Project.java:103) >> >> > at >> >> > >> >> > org.apache.calcite.rel.core.RelFactories$ProjectFactoryImpl. >> >> createProject(RelFactories.java:127) >> >> > at org.apache.calcite.tools.RelBuilder.project(RelBuilder.java:1064) >> >> > at org.apache.calcite.plan.RelOptUtil.createProject(RelOptUtil. >> >> java:2956) >> >> > at org.apache.calcite.plan.RelOptUtil.createProject(RelOptUtil. >> >> java:2873) >> >> > at >> >> > >> >> > org.apache.calcite.sql2rel.RelStructuredTypeFlattener.rewrit >> >> eRel(RelStructuredTypeFlattener.java:477) >> >> > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> >> > at >> >> > >> >> > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAcce >> >> ssorImpl.java:62) >> >> > at >> >> > >> >> > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMe >> >> thodAccessorImpl.java:43) >> >> > at java.lang.reflect.Method.invoke(Method.java:498) >> >> > at >> >> > >> >> > org.apache.calcite.util.ReflectUtil.invokeVisitorInternal(Re >> >> flectUtil.java:257) >> >> > at org.apache.calcite.util.ReflectUtil.invokeVisitor(ReflectUti >> >> l.java:214) >> >> > at >> >> > org.apache.calcite.util.ReflectUtil$1.invokeVisitor(ReflectU >> >> til.java:464) >> >> > at >> >> > >> >> > org.apache.calcite.sql2rel.RelStructuredTypeFlattener$Rewrit >> >> eRelVisitor.visit(RelStructuredTypeFlattener.java:721) >> >> > at >> >> > >> >> > org.apache.calcite.sql2rel.RelStructuredTypeFlattener.rewrit >> >> e(RelStructuredTypeFlattener.java:177) >> >> > at >> >> > >> >> > org.apache.calcite.sql2rel.SqlToRelConverter.flattenTypes(Sq >> >> lToRelConverter.java:462) >> >> > at >> >> > >> >> > org.apache.calcite.test.SqlToRelTestBase$TesterImpl.convertS >> >> qlToRel(SqlToRelTestBase.java:585) >> >> > at >> >> > >> >> > org.apache.calcite.test.SqlToRelTestBase$TesterImpl.assertCo >> >> nvertsTo(SqlToRelTestBase.java:690) >> >> > at >> >> > >> >> > org.apache.calcite.test.SqlToRelConverterTest$Sql.convertsTo >> >> (SqlToRelConverterTest.java:2784) >> >> > at >> >> > >> >> > org.apache.calcite.test.SqlToRelConverterTest$Sql.ok(SqlToRe >> >> lConverterTest.java:2776) >> >> > at >> >> > >> >> > org.apache.calcite.test.SqlToRelConverterTest.testArrayOfRec >> >> ord(SqlToRelConverterTest.java:1059) >> >> > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> >> > at >> >> > >> >> > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAcce >> >> ssorImpl.java:62) >> >> > at >> >> > >> >> > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMe >> >> thodAccessorImpl.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(Refl >> >> ectiveCallable.java:12) >> >> > at >> >> > >> >> > org.junit.runners.model.FrameworkMethod.invokeExplosively(Fr >> >> ameworkMethod.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(BlockJUnit >> >> 4ClassRunner.java:78) >> >> > at >> >> > >> >> > org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit >> >> 4ClassRunner.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:117) >> >> > at >> >> > >> >> > com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs >> >> (JUnit4IdeaTestRunner.java:42) >> >> > at >> >> > >> >> > com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsA >> >> ndStart(JUnitStarter.java:262) >> >> > at com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStart >> >> er.java:84) >> >> > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> >> > at >> >> > >> >> > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAcce >> >> ssorImpl.java:62) >> >> > at >> >> > >> >> > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMe >> >> thodAccessorImpl.java:43) >> >> > at java.lang.reflect.Method.invoke(Method.java:498) >> >> > at >> com.intellij.rt.execution.application.AppMain.main(AppMain.java:147) >> >> > >> >> > Shuyi >> >> > >> >> > >> >> > On Wed, Mar 21, 2018 at 6:09 PM, Shuyi Chen <[email protected]> >> wrote: >> >> > >> >> > > Thanks a lot, Anton. This seems to be a bug in Calcite. When the >> >> > statement >> >> > > involving record types, sql validation seems to work, but the rel >> plan >> >> > > generated might be wrong. I can also reproduce your case: >> >> > > >> >> > > MockTable deptNestedTable = >> >> > > MockTable.create(this, salesSchema, "DEPT_NESTED", false, 4); >> >> > > deptNestedTable.addColumn("DEPTNO", f.intType, true); >> >> > > deptNestedTable.addColumn("NAME", f.varchar10Type); >> >> > > deptNestedTable.addColumn("SKILLRECORD", f.skillRecordType); >> >> > > deptNestedTable.addColumn("EMPLOYEES", f.empListType); >> >> > > registerTable(deptNestedTable); >> >> > > >> >> > > Run the following test: >> >> > > >> >> > > @Test public void testArrayOfRecord() { >> >> > > sql("select skillrecord, employees from dept_nested").ok(); >> >> > > } >> >> > > >> >> > > yield: >> >> > > LogicalProject(SKILLRECORD=[$0], EMPLOYEES=[$1]) >> >> > > LogicalProject(SKILLRECORD=[$2], SKILLRECORD1=[$3], >> EMPLOYEES=[$4]) >> >> > > LogicalProject(DEPTNO=[$0], NAME=[$1], TYPE=[$2.TYPE], >> >> > DESC=[$2.DESC], >> >> > > EMPLOYEES=[$3]) >> >> > > LogicalTableScan(table=[[CATALOG, SALES, DEPT_NESTED]]) >> >> > > >> >> > > Sometimes, it works: >> >> > > >> >> > > @Test public void testArrayOfRecord() { >> >> > > sql("select name, employees from dept_nested").ok(); >> >> > > } >> >> > > >> >> > > yield: >> >> > > >> >> > > LogicalProject(NAME=[$1], EMPLOYEES=[$4]) >> >> > > LogicalProject(DEPTNO=[$0], NAME=[$1], TYPE=[$2.TYPE], >> >> DESC=[$2.DESC], >> >> > > EMPLOYEES=[$3]) >> >> > > LogicalTableScan(table=[[CATALOG, SALES, DEPT_NESTED]]) >> >> > > >> >> > > I can take a deeper look. >> >> > > >> >> > > Shuyi >> >> > > >> >> > > On Wed, Mar 21, 2018 at 11:06 AM, Anton Kedin >> >> <[email protected]> >> >> > > wrote: >> >> > > >> >> > >> Hi, >> >> > >> >> >> > >> I have an issue I am not sure how to handle, would appreciate any >> >> > >> pointers. >> >> > >> >> >> > >> I have a table with row type: >> >> > >> RecordType( >> >> > >> INTEGER orderId, >> >> > >> RecordType(VARCHAR name, INTEGER personId) >> >> > >> person, >> >> > >> RecordType(VARCHAR sku, INTEGER price, VARCHAR currency, >> VARCHAR >> >> > ARRAY >> >> > >> tags) >> >> > >> ARRAY items >> >> > >> ) >> >> > >> >> >> > >> With this row type I am trying to model a JSON object which looks >> >> like >> >> > >> this: >> >> > >> { "orderId" : 1, >> >> > >> "person" : { "name" : "john", "personId" : 12, }, >> >> > >> "items": [ >> >> > >> { "sku" : "aaa01", "price" : 12, "currency" : "USD", "tags" : >> >> > ["blue", >> >> > >> "book"] } >> >> > >> ]} >> >> > >> >> >> > >> When selecting the whole items array I get the following plan: >> >> > >> SELECT items FROM PCOLLECTION >> >> > >> >> >> > >> LogicalProject(items=[$3]) >> >> > >> LogicalProject(orderId=[$0], name=[$1.name], >> >> personId=[$1.personId], >> >> > >> items >> >> > >> =[$2]) >> >> > >> LogicalTableScan(table=[[PCOLLECTION]]) >> >> > >> >> >> > >> Which looks correct and it works. One thing to note here is that >> >> Calcite >> >> > >> flattens the person row, and makes the input ref for the items >> field >> >> as >> >> > >> $3, >> >> > >> as expected. >> >> > >> >> >> > >> But when I want to get a specific element from that array I get >> the >> >> > >> following: >> >> > >> SELECT items[0] FROM PCOLLECTION >> >> > >> >> >> > >> LogicalProject(EXPR$0$0=[ITEM($2, 0).sku], EXPR$0$1=[ITEM($2, >> >> 0).price], >> >> > >> EXPR$0$2=[ITEM($2, 0).currency], EXPR$0$3=[ITEM($2, 0).tags]) >> >> > >> LogicalProject(orderId=[$0], name=[$1.name], >> >> personId=[$1.personId], >> >> > >> items >> >> > >> =[$2]) >> >> > >> LogicalTableScan(table=[[PCOLLECTION]]) >> >> > >> >> >> > >> The first project looks the same. Flattened person row, items >> array, >> >> all >> >> > >> looks similar to the above. >> >> > >> But the outer project calls ITEM($2, i). I would expect it to be >> >> > >> ITEM($3, i) instead, >> >> > >> to adjust for the flattened person row, but it keeps the index as >> $2, >> >> > >> which >> >> > >> would have been the correct index if the row was not flattened, >> but >> >> it >> >> > >> should be $3 for flattened row, similar to the previous example. >> >> > >> >> >> > >> Is there something I am missing or is it a bug and Calcite should >> >> adjust >> >> > >> the input ref index to account for flattened rows in this case as >> >> well? >> >> > >> >> >> > >> Thank you, >> >> > >> Anton >> >> > >> >> >> > > >> >> > > >> >> > > >> >> > > -- >> >> > > "So you have to trust that the dots will somehow connect in your >> >> future." >> >> > > >> >> > >> >> > >> >> > >> >> > -- >> >> > "So you have to trust that the dots will somehow connect in your >> >> future." >> >> > >> >> >> > >> > >> > >> > -- >> > "So you have to trust that the dots will somehow connect in your >> future." >> > >> >> >> >> -- >> "So you have to trust that the dots will somehow connect in your future." >> >
