Ivan Budanaev created FLINK-25084:
-------------------------------------

             Summary: Field names must be unique. Found duplicates
                 Key: FLINK-25084
                 URL: https://issues.apache.org/jira/browse/FLINK-25084
             Project: Flink
          Issue Type: Bug
          Components: API / DataStream
    Affects Versions: 1.13.2
         Environment: AWS Kinesis Application in Zeppelin
Apache Flink 1.13, Apache Zeppelin 0.9
 
            Reporter: Ivan Budanaev
         Attachments: Screenshot 2021-11-28 at 13.10.57.png

I am getting a "Field names must be unique. Found duplicates" error when trying 
to aggregate a column used as a descriptor in HOP windowing.

Imagine this example, with *events_table* reading from kinesis stream, the 
definition given below, I am getting the "Field names must be unique. Found 
duplicates: [ts]" when trying to run the following SQL in Kinesis Data 
Analytics Application in Zeppelin:

{code:sql}
%flink.ssql(type=update)

-- insert into learn_actions_deduped 
SELECT window_start, window_end, uuid, event_type, max(ts) as max_event_ts
FROM TABLE(HOP(TABLE events_table, DESCRIPTOR(ts), INTERVAL '5' SECONDS, 
INTERVAL '15' MINUTES))
GROUP BY window_start, window_end, uuid, event_type;
{code}

The question is how can I use the descriptor column in aggregation without 
having to duplicate it?

The error details:
java.io.IOException: Fail to run stream sql job
        at 
org.apache.zeppelin.flink.sql.AbstractStreamSqlJob.run(AbstractStreamSqlJob.java:172)
        at 
org.apache.zeppelin.flink.sql.AbstractStreamSqlJob.run(AbstractStreamSqlJob.java:105)
        at 
org.apache.zeppelin.flink.FlinkStreamSqlInterpreter.callInnerSelect(FlinkStreamSqlInterpreter.java:89)
        at 
org.apache.zeppelin.flink.FlinkSqlInterrpeter.callSelect(FlinkSqlInterrpeter.java:503)
        at 
org.apache.zeppelin.flink.FlinkSqlInterrpeter.callCommand(FlinkSqlInterrpeter.java:266)
        at 
org.apache.zeppelin.flink.FlinkSqlInterrpeter.runSqlList(FlinkSqlInterrpeter.java:160)
        at 
org.apache.zeppelin.flink.FlinkSqlInterrpeter.internalInterpret(FlinkSqlInterrpeter.java:112)
        at 
org.apache.zeppelin.interpreter.AbstractInterpreter.interpret(AbstractInterpreter.java:47)
        at 
org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:110)
        at 
org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:852)
        at 
org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:744)
        at org.apache.zeppelin.scheduler.Job.run(Job.java:172)
        at 
org.apache.zeppelin.scheduler.AbstractScheduler.runJob(AbstractScheduler.java:132)
        at 
org.apache.zeppelin.scheduler.ParallelScheduler.lambda$runJobInScheduler$0(ParallelScheduler.java:46)
        at 
java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
        at 
java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
        at java.base/java.lang.Thread.run(Thread.java:829)
Caused by: java.lang.RuntimeException: Error while applying rule 
PullUpWindowTableFunctionIntoWindowAggregateRule, args 
[rel#1172:StreamPhysicalWindowAggregate.STREAM_PHYSICAL.any.None: 
0.[NONE].[NONE](input=RelSubset#1170,groupBy=uuid, 
event_type,window=HOP(win_start=[window_start], win_end=[window_end], size=[15 
min], slide=[5 s]),select=uuid, event_type, MAX(ts) AS max_event_ts, start('w$) 
AS window_start, end('w$) AS window_end), 
rel#1179:StreamPhysicalExchange.STREAM_PHYSICAL.hash[2, 3]true.None: 
0.[NONE].[NONE](input=RelSubset#1169,distribution=hash[uuid, event_type]), 
rel#1168:StreamPhysicalCalc.STREAM_PHYSICAL.any.None: 
0.[NONE].[NONE](input=RelSubset#1167,select=window_start, window_end, uuid, 
event_type, CAST(ts) AS ts), 
rel#1166:StreamPhysicalWindowTableFunction.STREAM_PHYSICAL.any.None: 
0.[NONE].[NONE](input=RelSubset#1165,window=HOP(time_col=[ts], size=[15 min], 
slide=[5 s]))]
        at 
org.apache.calcite.plan.volcano.VolcanoRuleCall.onMatch(VolcanoRuleCall.java:256)
        at 
org.apache.calcite.plan.volcano.IterativeRuleDriver.drive(IterativeRuleDriver.java:58)
        at 
org.apache.calcite.plan.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:510)
        at 
org.apache.calcite.tools.Programs$RuleSetProgram.run(Programs.java:312)
        at 
org.apache.flink.table.planner.plan.optimize.program.FlinkVolcanoProgram.optimize(FlinkVolcanoProgram.scala:69)
        at 
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.$anonfun$optimize$1(FlinkChainedProgram.scala:62)
        at 
scala.collection.TraversableOnce.$anonfun$foldLeft$1(TraversableOnce.scala:156)
        at 
scala.collection.TraversableOnce.$anonfun$foldLeft$1$adapted(TraversableOnce.scala:156)
        at scala.collection.Iterator.foreach(Iterator.scala:937)
        at scala.collection.Iterator.foreach$(Iterator.scala:937)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1425)
        at scala.collection.IterableLike.foreach(IterableLike.scala:70)
        at scala.collection.IterableLike.foreach$(IterableLike.scala:69)
        at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
        at scala.collection.TraversableOnce.foldLeft(TraversableOnce.scala:156)
        at scala.collection.TraversableOnce.foldLeft$(TraversableOnce.scala:154)
        at scala.collection.AbstractTraversable.foldLeft(Traversable.scala:104)
        at 
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.optimize(FlinkChainedProgram.scala:58)
        at 
org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.optimizeTree(StreamCommonSubGraphBasedOptimizer.scala:163)
        at 
org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.doOptimize(StreamCommonSubGraphBasedOptimizer.scala:83)
        at 
org.apache.flink.table.planner.plan.optimize.CommonSubGraphBasedOptimizer.optimize(CommonSubGraphBasedOptimizer.scala:77)
        at 
org.apache.flink.table.planner.delegation.PlannerBase.optimize(PlannerBase.scala:279)
        at 
org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:163)
        at 
org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:1518)
        at 
org.apache.flink.table.api.internal.TableEnvironmentImpl.translateAndClearBuffer(TableEnvironmentImpl.java:1510)
        at 
org.apache.flink.table.api.internal.TableEnvironmentImpl.execute(TableEnvironmentImpl.java:1460)
        at 
org.apache.zeppelin.flink.sql.AbstractStreamSqlJob.run(AbstractStreamSqlJob.java:161)
        ... 16 more
Caused by: java.lang.RuntimeException: Error occurred while applying rule 
PullUpWindowTableFunctionIntoWindowAggregateRule
        at 
org.apache.calcite.plan.volcano.VolcanoRuleCall.transformTo(VolcanoRuleCall.java:161)
        at 
org.apache.calcite.plan.RelOptRuleCall.transformTo(RelOptRuleCall.java:268)
        at 
org.apache.calcite.plan.RelOptRuleCall.transformTo(RelOptRuleCall.java:283)
        at 
org.apache.flink.table.planner.plan.rules.physical.stream.PullUpWindowTableFunctionIntoWindowAggregateRule.onMatch(PullUpWindowTableFunctionIntoWindowAggregateRule.scala:143)
        at 
org.apache.calcite.plan.volcano.VolcanoRuleCall.onMatch(VolcanoRuleCall.java:229)
        ... 42 more
Caused by: org.apache.flink.table.api.ValidationException: Field names must be 
unique. Found duplicates: [ts]
        at 
org.apache.flink.table.types.logical.RowType.validateFields(RowType.java:272)
        at org.apache.flink.table.types.logical.RowType.(RowType.java:157)
        at org.apache.flink.table.types.logical.RowType.of(RowType.java:297)
        at org.apache.flink.table.types.logical.RowType.of(RowType.java:289)
        at 
org.apache.flink.table.planner.calcite.FlinkTypeFactory$.toLogicalRowType(FlinkTypeFactory.scala:657)
        at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamPhysicalWindowAggregate.aggInfoList$lzycompute(StreamPhysicalWindowAggregate.scala:60)
        at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamPhysicalWindowAggregate.aggInfoList(StreamPhysicalWindowAggregate.scala:59)
        at 
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamPhysicalWindowAggregate.explainTerms(StreamPhysicalWindowAggregate.scala:86)
        at 
org.apache.calcite.rel.AbstractRelNode.getDigestItems(AbstractRelNode.java:409)
        at 
org.apache.calcite.rel.AbstractRelNode.deepHashCode(AbstractRelNode.java:391)
        at 
org.apache.calcite.rel.AbstractRelNode$InnerRelDigest.hashCode(AbstractRelNode.java:443)
        at java.base/java.util.HashMap.hash(HashMap.java:339)
        at java.base/java.util.HashMap.get(HashMap.java:552)
        at 
org.apache.calcite.plan.volcano.VolcanoPlanner.registerImpl(VolcanoPlanner.java:1150)
        at 
org.apache.calcite.plan.volcano.VolcanoPlanner.register(VolcanoPlanner.java:589)
        at 
org.apache.calcite.plan.volcano.VolcanoPlanner.ensureRegistered(VolcanoPlanner.java:604)
        at 
org.apache.calcite.plan.volcano.VolcanoRuleCall.transformTo(VolcanoRuleCall.java:148)
        ... 46 more

{code:sql}
CREATE TABLE events_table (
    uuid varchar(36),
    event_type VARCHAR(20),
    ts TIMESTAMP(3),
    WATERMARK FOR ts AS ts - INTERVAL '5' SECOND
)
PARTITIONED BY (event_type)
WITH (
    'connector' = 'kinesis',
    'stream' = 'kinesis-event-stream',
    'aws.region' = 'us-west-2',
    'scan.stream.initpos' = 'TRIM_HORIZON',
    'format' = 'json',
    'scan.stream.recordpublisher' = 'EFO',
    'scan.stream.efo.consumername' = 'learn-actions-efo',
    'scan.stream.efo.registration' = 'LAZY', -- EAGER
    'json.timestamp-format.standard' = 'ISO-8601'
);
{code}




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