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https://issues.apache.org/jira/browse/FLINK-5658?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15904371#comment-15904371
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ASF GitHub Bot commented on FLINK-5658:
---------------------------------------

Github user sunjincheng121 commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3386#discussion_r105322914
  
    --- Diff: 
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/UnboundedRowtimeOverTest.scala
 ---
    @@ -0,0 +1,133 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one
    + * or more contributor license agreements.  See the NOTICE file
    + * distributed with this work for additional information
    + * regarding copyright ownership.  The ASF licenses this file
    + * to you under the Apache License, Version 2.0 (the
    + * "License"); you may not use this file except in compliance
    + * with the License.  You may obtain a copy of the License at
    + *
    + *     http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.flink.table.api.scala.stream.sql
    +
    +import org.apache.flink.api.scala._
    +import org.apache.flink.streaming.api.TimeCharacteristic
    +import 
org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks
    +import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
    +import org.apache.flink.streaming.api.watermark.Watermark
    +import org.apache.flink.table.api.{TableEnvironment, TableException}
    +import org.apache.flink.table.api.scala._
    +import 
org.apache.flink.table.api.scala.stream.utils.StreamTestData.Small4Tuple
    +import org.apache.flink.table.api.scala.stream.utils.{StreamITCase, 
StreamTestData, StreamingWithStateTestBase}
    +import org.apache.flink.types.Row
    +import org.junit.Assert._
    +import org.junit._
    +
    +import scala.collection.mutable
    +
    +class UnboundedRowtimeOverTest extends StreamingWithStateTestBase {
    +
    +  /** test sliding event-time unbounded window with partition by **/
    +  @Test
    +  def testWithPartition(): Unit = {
    +    val env = StreamExecutionEnvironment.getExecutionEnvironment
    +    val tEnv = TableEnvironment.getTableEnvironment(env)
    +    env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
    +    StreamITCase.testResults = mutable.MutableList()
    +
    +    val sqlQuery = "SELECT a, b, SUM(a) over (partition by b order by 
rowtime() range between " +
    +      "unbounded preceding and current row) from T1"
    +
    +    val t1 = StreamTestData.getSmall3TupleDataStream(env)
    +      .assignTimestampsAndWatermarks(new 
AssignerWithPeriodicWatermarks[(Int, Long, String)] {
    +
    +        def getCurrentWatermark: Watermark = new Watermark(1300000L)
    +
    +        def extractTimestamp(element: (Int, Long, String), 
previousElementTimestamp: Long): Long =
    +          1400000
    +      }).toTable(tEnv).as('a, 'b, 'c)
    +    tEnv.registerTable("T1", t1)
    +
    +    val result = tEnv.sql(sqlQuery).toDataStream[Row]
    +    result.addSink(new StreamITCase.StringSink)
    +    env.execute()
    +
    +    val expected1 = mutable.MutableList(
    +      "1,1,1", "2,2,2", "3,2,5")
    +    val expected2 = mutable.MutableList(
    +      "1,1,1", "2,2,5", "3,2,3")
    +    assertTrue(expected1.equals(StreamITCase.testResults.sorted) ||
    +      expected2.equals(StreamITCase.testResults.sorted))
    +  }
    +
    +  /** test sliding event-time unbounded window without partitiion by **/
    +  @Test
    +  def testWithoutPartition(): Unit = {
    +    val env = StreamExecutionEnvironment.getExecutionEnvironment
    +    val tEnv = TableEnvironment.getTableEnvironment(env)
    +    env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
    +    StreamITCase.testResults = mutable.MutableList()
    +
    +    val sqlQuery = "SELECT SUM(a) " +
    +      "over (order by rowtime() range between unbounded preceding and 
current row) from T1"
    +
    +    val t1 = StreamTestData.getSmall3TupleDataStream(env)
    +      .assignTimestampsAndWatermarks(new 
AssignerWithPeriodicWatermarks[(Int, Long, String)] {
    +
    +        def getCurrentWatermark: Watermark = new Watermark(1300000L)
    +
    +        def extractTimestamp(element: (Int, Long, String), 
previousElementTimestamp: Long): Long =
    +          1400000
    +      }).toTable(tEnv).as('a, 'b, 'c)
    +    tEnv.registerTable("T1", t1)
    +
    +    val result = tEnv.sql(sqlQuery).toDataStream[Row]
    +    result.addSink(new StreamITCase.StringSink)
    +    env.execute()
    +
    +    assertEquals(Some("6"), 
StreamITCase.testResults.sorted.get(StreamITCase.testResults.size - 1))
    --- End diff --
    
    Can you test the results of each output?


> Add event time OVER RANGE BETWEEN UNBOUNDED PRECEDING aggregation to SQL
> ------------------------------------------------------------------------
>
>                 Key: FLINK-5658
>                 URL: https://issues.apache.org/jira/browse/FLINK-5658
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API & SQL
>            Reporter: Fabian Hueske
>            Assignee: Yuhong Hong
>
> The goal of this issue is to add support for OVER RANGE aggregations on event 
> time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT 
>   a, 
>   SUM(b) OVER (PARTITION BY c ORDER BY rowTime() RANGE BETWEEN UNBOUNDED 
> PRECEDING AND CURRENT ROW) AS sumB,
>   MIN(b) OVER (PARTITION BY c ORDER BY rowTime() RANGE BETWEEN UNBOUNDED 
> PRECEDING AND CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The PARTITION BY clause is optional (no partitioning results in single 
> threaded execution).
> - The ORDER BY clause may only have rowTime() as parameter. rowTime() is a 
> parameterless scalar function that just indicates processing time mode.
> - bounded PRECEDING is not supported (see FLINK-5655)
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some 
> of the restrictions are trivial to address, we can add the functionality in 
> this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with 
> RexOver expression).



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