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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-5654) Add processing time OVER RANGE BETWEEN x PRECEDING aggregation to SQL
Date Wed, 29 Mar 2017 17:00:47 GMT

    [ https://issues.apache.org/jira/browse/FLINK-5654?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15947515#comment-15947515
] 

ASF GitHub Bot commented on FLINK-5654:
---------------------------------------

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

    https://github.com/apache/flink/pull/3641#discussion_r108729682
  
    --- Diff: flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/SqlITCase.scala
---
    @@ -696,6 +713,205 @@ class SqlITCase extends StreamingWithStateTestBase {
           "6,8,Hello world,51,9,5,9,1")
         assertEquals(expected.sorted, StreamITCase.testResults.sorted)
       }
    +
    +  @Test
    +  def testAvgSumAggregatationPartition(): Unit = {
    +
    +    val env = StreamExecutionEnvironment.getExecutionEnvironment
    +    val tEnv = TableEnvironment.getTableEnvironment(env)
    +    env.setParallelism(1)
    +    StreamITCase.testResults = mutable.MutableList()
    +
    +    val sqlQuery = "SELECT a, AVG(c) OVER (PARTITION BY a ORDER BY procTime()" +
    +      "RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW) AS avgC," +
    +      "SUM(c) OVER (PARTITION BY a ORDER BY procTime()" +
    +      "RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW) as sumC FROM MyTable"
    +
    +    val t = StreamTestData.get5TupleDataStream(env)
    +      .toTable(tEnv).as('a, 'b, 'c, 'd, 'e)
    +
    +    tEnv.registerTable("MyTable", t)
    +
    +    val result = tEnv.sql(sqlQuery).toDataStream[Row]
    +    result.addSink(new StreamITCase.StringSink)
    +    env.execute()
    +
    +    val expected = mutable.MutableList(
    +      "1,0,0",
    +      "2,1,1",
    +      "2,1,3",
    +      "3,3,3",
    +      "3,3,7",
    +      "3,4,12",
    +      "4,6,13",
    +      "4,6,6",
    +      "4,7,21",
    +      "4,7,30",
    +      "5,10,10",
    +      "5,10,21",
    +      "5,11,33",
    +      "5,11,46",
    +      "5,12,60")
    +
    +    assertEquals(expected.sorted, StreamITCase.testResults.sorted)
    +  }
    +
    +  @Test
    +  def testAvgSumAggregatationNonPartition(): Unit = {
    +
    +    val env = StreamExecutionEnvironment.getExecutionEnvironment
    +    val tEnv = TableEnvironment.getTableEnvironment(env)
    +    env.setParallelism(1)
    +    StreamITCase.testResults = mutable.MutableList()
    +
    +    val sqlQuery = "SELECT a, Count(c) OVER (ORDER BY procTime()" +
    +      "RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW) AS avgC," +
    +      "MIN(c) OVER (ORDER BY procTime()" +
    +      "RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW) as sumC FROM MyTable"
    +
    +    val t = StreamTestData.get5TupleDataStream(env)
    +      .toTable(tEnv).as('a, 'b, 'c, 'd, 'e)
    +
    +    tEnv.registerTable("MyTable", t)
    +
    +    val result = tEnv.sql(sqlQuery).toDataStream[Row]
    +    result.addSink(new StreamITCase.StringSink)
    +    env.execute()
    +
    +    val expected = mutable.MutableList(
    +      "1,1,0",
    +      "2,2,0",
    +      "2,3,0",
    +      "3,4,0",
    +      "3,5,0",
    +      "3,6,0",
    +      "4,7,0",
    +      "4,8,0",
    +      "4,9,0",
    +      "4,10,0",
    +      "5,11,0",
    +      "5,12,0",
    +      "5,13,0",
    +      "5,14,0",
    +      "5,15,0")
    +
    +    assertEquals(expected.sorted, StreamITCase.testResults.sorted)
    +  }
    +
    +  
    +  @Test
    +  def testCountAggregatationProcTimeHarnessPartitioned(): Unit = {
    +    val env = StreamExecutionEnvironment.getExecutionEnvironment
    +    val tEnv = TableEnvironment.getTableEnvironment(env)
    --- End diff --
    
    The test harness test does not need `StreamExecutionEnvironment` and `TableEnvironment`.


> Add processing time OVER RANGE BETWEEN x PRECEDING aggregation to SQL
> ---------------------------------------------------------------------
>
>                 Key: FLINK-5654
>                 URL: https://issues.apache.org/jira/browse/FLINK-5654
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API & SQL
>            Reporter: Fabian Hueske
>            Assignee: radu
>
> The goal of this issue is to add support for OVER RANGE aggregations on processing 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 procTime() RANGE BETWEEN INTERVAL '1' HOUR PRECEDING
AND CURRENT ROW) AS sumB,
>   MIN(b) OVER (PARTITION BY c ORDER BY procTime() RANGE BETWEEN INTERVAL '1' HOUR 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 procTime() as parameter. procTime() is a parameterless
scalar function that just indicates processing time mode.
> - UNBOUNDED PRECEDING is not supported (see FLINK-5657)
> - 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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