当至少有一个表具有时间属性列时，我在使用Flink的SQL语法连接多个表时遇到了一些问题。
我有一个使用模式(id，value1，rowtime(的表Table1，当rowtime用作flink rowtime时。
我想将此表与使用模式(id，value2(的表Table2连接起来。联接必须在匹配的id上完成。
最后，我想通过使用翻滚时间窗口对该连接的结果进行分组。
是否可以仅使用SQL语法来完成此操作？
下面是我想做的一个例子：
SELECT
Table1.id as id,
TUMBLE_END(rowtime, INTERVAL '10' SECOND),
MAX(value1) as value1,
MAX(value2) as value2
FROM Table1 JOIN TABLE2 ON Table1.id = Table2.id
GROUP BY Table1.id, TUMBLE(rowtime, INTERVAL '10' SECOND)
但它给了我以下错误：
2019-11-12 16:37:57.191 [main] ERROR - Cannot generate a valid execution plan for the given query:
FlinkLogicalCalc(expr#0..6=[{inputs}], id=[$t0], EXPR$1=[$t4], value1=[$t1], value2=[$t2])
FlinkLogicalWindowAggregate(group=[{0}], value1=[MAX($2)], value2=[MAX($3)])
FlinkLogicalCalc(expr#0..2=[{inputs}], expr#3=[0], proj#0..1=[{exprs}], value1=[$t3], value2=[$t3])
FlinkLogicalJoin(condition=[=($0, $2)], joinType=[inner])
FlinkLogicalTableSourceScan(table=[[Table1]], fields=[id, value1, rowtime], source=[KafkaTableSource(id, value1, rowtime)])
FlinkLogicalTableSourceScan(table=[[Table2]], fields=[id, value2], source=[Table2_Type(id, value2)])
Rowtime attributes must not be in the input rows of a regular join. As a workaround you can cast the time attributes of input tables to TIMESTAMP before.
Please check the documentation for the set of currently supported SQL features.
org.apache.flink.table.api.TableException: Cannot generate a valid execution plan for the given query:
FlinkLogicalCalc(expr#0..6=[{inputs}], id=[$t0], EXPR$1=[$t4], value1=[$t1], value2=[$t2])
FlinkLogicalWindowAggregate(group=[{0}], value1=[MAX($2)], value2=[MAX($3)])
FlinkLogicalCalc(expr#0..2=[{inputs}], expr#3=[0], proj#0..1=[{exprs}], value1=[$t3], value2=[$t3])
FlinkLogicalJoin(condition=[=($0, $2)], joinType=[inner])
FlinkLogicalTableSourceScan(table=[[kafkaDataStream]], fields=[id, value1, rowtime], source=[KafkaTableSource(id, value1, rowtime)])
FlinkLogicalTableSourceScan(table=[[SensorConfigurationUpdateHTTP]], fields=[id, value2], source=[Table2_Type(id, value2)])
Rowtime attributes must not be in the input rows of a regular join. As a workaround you can cast the time attributes of input tables to TIMESTAMP before.
Please check the documentation for the set of currently supported SQL features.
at org.apache.flink.table.api.TableEnvironment.runVolcanoPlanner(TableEnvironment.scala:387)
at org.apache.flink.table.api.TableEnvironment.optimizePhysicalPlan(TableEnvironment.scala:302)
at org.apache.flink.table.api.StreamTableEnvironment.optimize(StreamTableEnvironment.scala:816)
at org.apache.flink.table.api.StreamTableEnvironment.writeToSink(StreamTableEnvironment.scala:379)
at org.apache.flink.table.api.TableEnvironment.insertInto(TableEnvironment.scala:879)
at org.apache.flink.table.api.Table.insertInto(table.scala:1126)
...
我还尝试将我的rowtime强制转换为TIMESTAMP类型(如错误消息所建议的(，但之后我就无法再处理时间窗口了。这会导致以下错误：
2019-11-12 16:44:52.473 [main] ERROR - Window can only be defined over a time attribute column.
org.apache.flink.table.api.ValidationException: Window can only be defined over a time attribute column.
at org.apache.flink.table.plan.rules.datastream.DataStreamLogicalWindowAggregateRule.getOperandAsTimeIndicator$1(DataStreamLogicalWindowAggregateRule.scala:84)
at org.apache.flink.table.plan.rules.datastream.DataStreamLogicalWindowAggregateRule.translateWindowExpression(DataStreamLogicalWindowAggregateRule.scala:89)
at org.apache.flink.table.plan.rules.common.LogicalWindowAggregateRule.onMatch(LogicalWindowAggregateRule.scala:65)
at org.apache.calcite.plan.AbstractRelOptPlanner.fireRule(AbstractRelOptPlanner.java:315)
at org.apache.calcite.plan.hep.HepPlanner.applyRule(HepPlanner.java:556)
at org.apache.calcite.plan.hep.HepPlanner.applyRules(HepPlanner.java:415)
at org.apache.calcite.plan.hep.HepPlanner.executeInstruction(HepPlanner.java:252)
at org.apache.calcite.plan.hep.HepInstruction$RuleInstance.execute(HepInstruction.java:127)
at org.apache.calcite.plan.hep.HepPlanner.executeProgram(HepPlanner.java:211)
at org.apache.calcite.plan.hep.HepPlanner.findBestExp(HepPlanner.java:198)
at org.apache.flink.table.api.TableEnvironment.runHepPlanner(TableEnvironment.scala:360)
at org.apache.flink.table.api.TableEnvironment.runHepPlannerSequentially(TableEnvironment.scala:326)
at org.apache.flink.table.api.TableEnvironment.optimizeNormalizeLogicalPlan(TableEnvironment.scala:282)
at org.apache.flink.table.api.StreamTableEnvironment.optimize(StreamTableEnvironment.scala:813)
at org.apache.flink.table.api.StreamTableEnvironment.writeToSink(StreamTableEnvironment.scala:379)
at org.apache.flink.table.api.TableEnvironment.insertInto(TableEnvironment.scala:879)
at org.apache.flink.table.api.Table.insertInto(table.scala:1126)
联接结果不能包含时间属性，因为联接不能保证时间戳的顺序得到保留。Flink假设两个表都是动态的，并且可以在任何时间点更改。表Table2中的一个新记录可能与Table1的第一个记录连接，从而产生具有"随机"顺序的时间戳的结果。
您可以通过在联接中添加时间约束来更改这一点。要么用时间窗口联接定义查询，要么将Table2建模为时态表并用它联接Table1