Flink SQL CodeGenException

2021-05-15 文章 sherlock c 
Flink version: 1.12.0 

在使用 Flink 执行 Flink SQL  流表 join 维表, 运行报错(流表SQL 和维表SQL单独运行都没有问题), 错误堆栈信息如下:

Exception in thread "main" java.lang.RuntimeException: 
org.apache.flink.table.planner.codegen.CodeGenException: Unable to find common 
type of GeneratedExpression(field$18,isNull$17,,STRING,None) and 
ArrayBuffer(GeneratedExpression(((int) 4),false,,INT NOT NULL,Some(4)), 
GeneratedExpression(((int) 8),false,,INT NOT NULL,Some(8))).
at com.hmd.stream.SqlSubmit.main(SqlSubmit.java:47)
Caused by: org.apache.flink.table.planner.codegen.CodeGenException: Unable to 
find common type of GeneratedExpression(field$18,isNull$17,,STRING,None) and 
ArrayBuffer(GeneratedExpression(((int) 4),false,,INT NOT NULL,Some(4)), 
GeneratedExpression(((int) 8),false,,INT NOT NULL,Some(8))).
at 
org.apache.flink.table.planner.codegen.calls.ScalarOperatorGens$.$anonfun$generateIn$2(ScalarOperatorGens.scala:307)
at scala.Option.orElse(Option.scala:289)
at 
org.apache.flink.table.planner.codegen.calls.ScalarOperatorGens$.generateIn(ScalarOperatorGens.scala:307)
at 
org.apache.flink.table.planner.codegen.ExprCodeGenerator.generateCallExpression(ExprCodeGenerator.scala:724)
at 
org.apache.flink.table.planner.codegen.ExprCodeGenerator.visitCall(ExprCodeGenerator.scala:507)
at 
org.apache.flink.table.planner.codegen.ExprCodeGenerator.visitCall(ExprCodeGenerator.scala:56)
at org.apache.calcite.rex.RexCall.accept(RexCall.java:174)
at 
org.apache.flink.table.planner.codegen.ExprCodeGenerator.$anonfun$visitCall$2(ExprCodeGenerator.scala:526)
at 
scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:233)
at 
scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:58)
at 
scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:51)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at scala.collection.TraversableLike.map(TraversableLike.scala:233)
at scala.collection.TraversableLike.map$(TraversableLike.scala:226)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at 
org.apache.flink.table.planner.codegen.ExprCodeGenerator.visitCall(ExprCodeGenerator.scala:517)
at 
org.apache.flink.table.planner.codegen.ExprCodeGenerator.visitCall(ExprCodeGenerator.scala:56)
at org.apache.calcite.rex.RexCall.accept(RexCall.java:174)
at 
org.apache.flink.table.planner.codegen.ExprCodeGenerator.generateExpression(ExprCodeGenerator.scala:155)
at 
org.apache.flink.table.planner.codegen.CalcCodeGenerator$.$anonfun$generateProcessCode$5(CalcCodeGenerator.scala:143)
at 
scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:233)
at 
scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:58)
at 
scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:51)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at scala.collection.TraversableLike.map(TraversableLike.scala:233)
at scala.collection.TraversableLike.map$(TraversableLike.scala:226)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at 
org.apache.flink.table.planner.codegen.CalcCodeGenerator$.produceProjectionCode$1(CalcCodeGenerator.scala:143)
at 
org.apache.flink.table.planner.codegen.CalcCodeGenerator$.generateProcessCode(CalcCodeGenerator.scala:190)
at 
org.apache.flink.table.planner.codegen.CalcCodeGenerator$.generateCalcOperator(CalcCodeGenerator.scala:59)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalc.translateToPlanInternal(StreamExecCalc.scala:84)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalc.translateToPlanInternal(StreamExecCalc.scala:39)
at 
org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan(ExecNode.scala:59)
at 
org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan$(ExecNode.scala:57)
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.StreamExecLookupJoin.translateToPlanInternal(StreamExecLookupJoin.scala:84)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecLookupJoin.translateToPlanInternal(StreamExecLookupJoin.scala:38)
at 
org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan(ExecNode.scala:59)
at 
org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan$(ExecNode.scala:57)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecLookupJoin.translateToPlan(StreamExecLookupJoin.scala:38)
at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalc.translateToPlanInternal(StreamExecCalc.scala:54)

回复: 请教flink cep如何对无序数据处理

2021-05-15 文章 sherlock zw 
老哥，这个图片好像我这边好像显示不出来。能否再重新发一次


发件人: Peihui He
发送时间: 2021年5月14日 19:55
收件人: user-zh@flink.apache.org
主题: Re: 请教flink cep如何对无序数据处理

[cid:ii_koo9jn4u1]

这样可以不？

sherlock zw mailto:zw30...@live.com>> 于2021年5月14日周五 上午8:52写道：
兄弟们，想问下Flink的CEP能够对无序数据流进行处理匹配嘛？
我这里指的无序事件是：例如有两个事件，事件A和事件B，在一个时间窗口内，只要匹配到了A和B，不论A和B的到来顺序，我都认为是符合我的条件