Hi, 我理解这边两个问题。 1. `Row` 2 `Row` 的转换在 1.12 支持了：https://issues.apache.org/jira/browse/FLINK-17049 2. 这个 Select 语句貌似不会产生这个错误，方便发个完整的不
Best, hailong 在 2020-12-09 12:51:21，"bigdata" <[email protected]> 写道： >flink1.10.1，应该如何计算error_1006_cnt_permillage >sql如下： >SELECT >| DATE_FORMAT(TIMESTAMPADD(HOUR, 8, TUMBLE_START(proctime, INTERVAL '10' >SECOND)), 'yyyy-MM-dd') `day`, >| UNIX_TIMESTAMP(DATE_FORMAT(TIMESTAMPADD(HOUR, 8, TUMBLE_START(proctime, >INTERVAL '10' SECOND)), 'yyyy-MM-dd HH:mm:ss')) * 1000 AS `time`, >| CAST(COUNT(res_code) AS INT) AS request_cnt, >| CAST(COUNT(res_code) FILTER(WHERE res_code = '500') AS INT) AS >error_500_cnt, >| CAST(COUNT(res_code) FILTER(WHERE res_code = '1002') AS INT) AS >error_1002_cnt, >| CAST(COUNT(res_code) FILTER(WHERE res_code = '1003') AS INT) AS >error_1003_cnt, >| CAST(COUNT(res_code) FILTER(WHERE res_code = '1004') AS INT) AS >error_1004_cnt, >| CAST(COUNT(res_code) FILTER(WHERE res_code = '1005') AS INT) AS >error_1005_cnt, >| CAST(COUNT(res_code) FILTER(WHERE res_code = '1006') AS INT) AS >error_1006_cnt, >| CAST(COUNT(res_code) FILTER(WHERE res_code = >'1006')*1.0/COUNT(res_code)*100 as numeric(10,1)) error_1006_cnt_permillage >| FROM >| ${databaseName}.metric_stream >| WHERE >| metric = 'http_common_request' >| GROUP BY >| TUMBLE(proctime, INTERVAL '10' SECOND)Exception in thread "main" >org.apache.flink.table.planner.codegen.CodeGenException: Unsupported cast from >'ROW' to 'ROW'. at >org.apache.flink.table.planner.codegen.calls.ScalarOperatorGens$.generateCast(ScalarOperatorGens.scala:1284) > at >org.apache.flink.table.planner.codegen.ExprCodeGenerator.generateCallExpression(ExprCodeGenerator.scala:690) > at >org.apache.flink.table.planner.codegen.ExprCodeGenerator.visitCall(ExprCodeGenerator.scala:485) > at >org.apache.flink.table.planner.codegen.ExprCodeGenerator.visitCall(ExprCodeGenerator.scala:51) > at org.apache.calcite.rex.RexCall.accept(RexCall.java:191) at >org.apache.flink.table.planner.codegen.ExprCodeGenerator.generateExpression(ExprCodeGenerator.scala:131) > at >org.apache.flink.table.planner.codegen.CalcCodeGenerator$$anonfun$5.apply(CalcCodeGenerator.scala:152) > at >org.apache.flink.table.planner.codegen.CalcCodeGenerator$$anonfun$5.apply(CalcCodeGenerator.scala:152) > at >scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at >scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at >scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) >at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) > at scala.collection.AbstractTraversable.map(Traversable.scala:104) at >org.apache.flink.table.planner.codegen.CalcCodeGenerator$.produceProjectionCode$1(CalcCodeGenerator.scala:152) > at >org.apache.flink.table.planner.codegen.CalcCodeGenerator$.generateProcessCode(CalcCodeGenerator.scala:179) > at >org.apache.flink.table.planner.codegen.CalcCodeGenerator$.generateCalcOperator(CalcCodeGenerator.scala:49) > at >org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalc.translateToPlanInternal(StreamExecCalc.scala:77) > at >org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalc.translateToPlanInternal(StreamExecCalc.scala:39) > at >org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:58) > at >org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalcBase.translateToPlan(StreamExecCalcBase.scala:38) > at >org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToTransformation(StreamExecSink.scala:184) > at >org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:118) > at >org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:48) > at >org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:58) > at >org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlan(StreamExecSink.scala:48) > at >org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:60) > at >org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:59) > at >scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at >scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at scala.collection.Iterator$class.foreach(Iterator.scala:893) at >scala.collection.AbstractIterator.foreach(Iterator.scala:1336) at >scala.collection.IterableLike$class.foreach(IterableLike.scala:72) at >scala.collection.AbstractIterable.foreach(Iterable.scala:54) at >scala.collection.TraversableLike$class.map(TraversableLike.scala:234) >at scala.collection.AbstractTraversable.map(Traversable.scala:104) at >org.apache.flink.table.planner.delegation.StreamPlanner.translateToPlan(StreamPlanner.scala:59) > at >org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:153) > at >org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:685) > at >org.apache.flink.table.api.internal.TableEnvironmentImpl.sqlUpdate(TableEnvironmentImpl.java:495)
