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https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15927555#comment-15927555
]
ASF GitHub Bot commented on FLINK-5653:
---------------------------------------
Github user sunjincheng121 commented on a diff in the pull request:
https://github.com/apache/flink/pull/3547#discussion_r106344891
--- Diff:
flink-libraries/flink-table/src/test/java/org/apache/flink/table/api/java/stream/sql/ProcTimeRowStreamAggregationSqlITCase.java
---
@@ -0,0 +1,317 @@
+/*
+ * 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.java.stream.sql;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.flink.api.java.tuple.Tuple5;
+import org.apache.flink.streaming.api.datastream.DataStream;
+import
org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
+import org.apache.flink.streaming.util.StreamingMultipleProgramsTestBase;
+import org.apache.flink.table.api.Table;
+import org.apache.flink.table.api.TableEnvironment;
+import org.apache.flink.table.api.java.StreamTableEnvironment;
+import org.apache.flink.table.api.java.stream.utils.StreamTestData;
+import org.apache.flink.table.api.scala.stream.utils.StreamITCase;
+import org.apache.flink.types.Row;
+import org.junit.Ignore;
+import org.junit.Test;
+
+public class ProcTimeRowStreamAggregationSqlITCase extends
StreamingMultipleProgramsTestBase {
+
+
+ @Test
+ public void testMaxAggregatation() throws Exception {
+ StreamExecutionEnvironment env =
StreamExecutionEnvironment.getExecutionEnvironment();
+ StreamTableEnvironment tableEnv =
TableEnvironment.getTableEnvironment(env);
+ StreamITCase.clear();
+
+ env.setParallelism(1);
+
+ DataStream<Tuple5<Integer, Long, Integer, String, Long>> ds =
StreamTestData.get5TupleDataStream(env);
+ Table in = tableEnv.fromDataStream(ds, "a,b,c,d,e");
+ tableEnv.registerTable("MyTable", in);
+
+ String sqlQuery = "SELECT a, MAX(c) OVER (PARTITION BY a ORDER
BY procTime() ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS maxC FROM MyTable";
+ Table result = tableEnv.sql(sqlQuery);
+
+ DataStream<Row> resultSet = tableEnv.toDataStream(result,
Row.class);
+ resultSet.addSink(new StreamITCase.StringSink());
+ env.execute();
+
+ List<String> expected = new ArrayList<>();
+ expected.add("1,0");
+ expected.add("2,1");
+ expected.add("2,2");
+ expected.add("3,3");
+ expected.add("3,4");
+ expected.add("3,5");
+ expected.add("4,6");
+ expected.add("4,7");
+ expected.add("4,8");
+ expected.add("4,9");
+ expected.add("5,10");
+ expected.add("5,11");
+ expected.add("5,12");
+ expected.add("5,14");
+ expected.add("5,14");
+
+ StreamITCase.compareWithList(expected);
+ }
+
+ @Test
+ public void testMinAggregatation() throws Exception {
+ StreamExecutionEnvironment env =
StreamExecutionEnvironment.getExecutionEnvironment();
+ StreamTableEnvironment tableEnv =
TableEnvironment.getTableEnvironment(env);
+ StreamITCase.clear();
+
+ env.setParallelism(1);
+
+ DataStream<Tuple5<Integer, Long, Integer, String, Long>> ds =
StreamTestData.get5TupleDataStream(env);
+ Table in = tableEnv.fromDataStream(ds, "a,b,c,d,e");
+ tableEnv.registerTable("MyTable", in);
+
+ String sqlQuery = "SELECT a, MIN(c) OVER (PARTITION BY a ORDER
BY procTime() ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS maxC FROM MyTable";
+ Table result = tableEnv.sql(sqlQuery);
+
+ DataStream<Row> resultSet = tableEnv.toDataStream(result,
Row.class);
+ resultSet.addSink(new StreamITCase.StringSink());
+ env.execute();
+
+ List<String> expected = new ArrayList<>();
+ expected.add("1,0");
+ expected.add("2,1");
+ expected.add("2,1");
+ expected.add("3,3");
+ expected.add("3,3");
+ expected.add("3,4");
+ expected.add("4,6");
+ expected.add("4,6");
+ expected.add("4,7");
+ expected.add("4,8");
+ expected.add("5,10");
+ expected.add("5,10");
+ expected.add("5,11");
+ expected.add("5,12");
--- End diff --
This result incorrect.The reason for the error I left the comments in
`DataStreamOverAggregate.scala`
> Add processing time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
> --------------------------------------------------------------------
>
> Key: FLINK-5653
> URL: https://issues.apache.org/jira/browse/FLINK-5653
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: Fabian Hueske
> Assignee: Stefano Bortoli
>
> The goal of this issue is to add support for OVER ROWS 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() ROWS BETWEEN 2 PRECEDING
> AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY procTime() ROWS BETWEEN 2 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-5656)
> - 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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