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From Pavel Ciorba <pavli...@gmail.com>
Subject Flink 1.4 SQL API Streaming TableException
Date Fri, 09 Mar 2018 20:49:13 GMT
Hi everyone!

I decided to try the Time-windowed join functionality of Flink 1.4+.

My SQL query is an exact copy of the example in the documentation, and the
program reads and writes from Kafka.

I used the example from here:
https://ci.apache.org/projects/flink/flink-docs-release-1.4/dev/table/sql.html#joins

Code:
https://gist.github.com/invoker27/ecb4f4b38a52642089e41f6f49886c28

Dependencies:
compile group: 'org.apache.flink', name: 'flink-table_2.11', version:
'1.4.0'
compile group: 'org.apache.flink', name: 'flink-streaming-scala_2.11',
version: '1.4.0'
compile group: 'org.apache.flink', name: 'flink-connector-kafka-0.11_2.11',
version: '1.4.0'

Error:
Exception in thread "main" org.apache.flink.table.api.TableException:
Cannot generate a valid execution plan for the given query:

FlinkLogicalJoin(condition=[AND(=($0, $5), >=($3, -($8, 14400000)), <=($3,
$8))], joinType=[inner])
  FlinkLogicalTableSourceScan(table=[[TABLE1]], fields=[id, value1,
timestamp], source=[KafkaJSONTableSource])
  FlinkLogicalTableSourceScan(table=[[TABLE2]], fields=[id, value2,
timestamp], source=[KafkaJSONTableSource])

This exception indicates that the query uses an unsupported SQL feature.
Please check the documentation for the set of currently supported SQL
features.
at
org.apache.flink.table.api.TableEnvironment.runVolcanoPlanner(TableEnvironment.scala:274)
at
org.apache.flink.table.api.StreamTableEnvironment.optimize(StreamTableEnvironment.scala:683)
at
org.apache.flink.table.api.StreamTableEnvironment.writeToSink(StreamTableEnvironment.scala:251)
at org.apache.flink.table.api.Table.writeToSink(table.scala:862)
at org.apache.flink.table.api.Table.writeToSink(table.scala:830)
at
com.sheffield.healthmonitoring.join.conditionalhr.JoinSQL.main(JoinSQL.java:72)


I get the error in 1.4.0, 1.4.1 and 1.4.2, but 1.5-SNAPSHOT works.

>From what I can see the feature should work in 1.4.

What might be the issue?

Thank you!

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