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https://issues.apache.org/jira/browse/FLINK-5658?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15904367#comment-15904367
]
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_r105323083
--- 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))
+ }
+
+ /** test sliding event-time unbounded window with later record **/
+ @Test
+ def testWithLater(): Unit = {
+ val env = StreamExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+ env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
+ env.getConfig.setAutoWatermarkInterval(10000);
+ StreamITCase.testResults = mutable.MutableList()
+
+ val sqlQuery = "SELECT d, SUM(a) " +
+ "over (order by rowtime() range between unbounded preceding and
current row) from T1"
+
+ val t1 = StreamTestData.getSmall4TupleEventTimeDataStream(env)
+ .assignTimestampsAndWatermarks(new
AssignerWithPeriodicWatermarks[Small4Tuple] {
+ var cur = 1200000L;
+
+ def getCurrentWatermark: Watermark = new Watermark({cur += 10;
cur;})
+
+ def extractTimestamp(element: Small4Tuple,
previousElementTimestamp: Long): Long =
+ element.d
--- End diff --
Can we set the value of `cur` based on the data?
> 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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