flink-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-5658) Add event time OVER RANGE BETWEEN UNBOUNDED PRECEDING aggregation to SQL
Date Fri, 10 Mar 2017 03:40:39 GMT

    [ https://issues.apache.org/jira/browse/FLINK-5658?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15904371#comment-15904371
] 

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).



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

Mime
View raw message