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."
