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https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15891448#comment-15891448
]
ASF GitHub Bot commented on FLINK-5653:
---------------------------------------
Github user hongyuhong commented on a diff in the pull request:
https://github.com/apache/flink/pull/3443#discussion_r103835080
--- Diff:
flink-libraries/flink-table/src/main/java/org/apache/flink/table/plan/nodes/datastream/DataStreamProcTimeRowAggregate.java
---
@@ -0,0 +1,160 @@
+/*
+ * 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.plan.nodes.datastream;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.calcite.plan.RelOptCluster;
+import org.apache.calcite.plan.RelTraitSet;
+import org.apache.calcite.rel.RelNode;
+import org.apache.calcite.rel.RelWriter;
+import org.apache.calcite.rel.core.Window.Group;
+import org.apache.calcite.rel.core.Window.RexWinAggCall;
+import org.apache.calcite.rel.logical.LogicalWindow;
+import org.apache.calcite.rel.type.RelDataType;
+import org.apache.calcite.rel.type.RelDataTypeField;
+import org.apache.calcite.rex.RexInputRef;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.java.tuple.Tuple;
+import org.apache.flink.api.java.typeutils.RowTypeInfo;
+import org.apache.flink.streaming.api.datastream.DataStream;
+import org.apache.flink.streaming.api.datastream.KeyedStream;
+import org.apache.flink.table.api.StreamTableEnvironment;
+import org.apache.flink.table.api.TableConfig;
+import org.apache.flink.table.calcite.FlinkTypeFactory;
+import org.apache.flink.table.plan.logical.rel.util.WindowAggregateUtil;
+import
org.apache.flink.table.plan.nodes.datastream.function.DataStreamProcTimeAggregateRowGlobalWindowFunction;
+import
org.apache.flink.table.plan.nodes.datastream.function.DataStreamProcTimeAggregateRowKeyedWindowFunction;
+import org.apache.flink.types.Row;
+
+public class DataStreamProcTimeRowAggregate extends DataStreamRelJava {
+
+ protected LogicalWindow windowRef;
+ protected String description;
+ protected WindowAggregateUtil winUtil;
+
+ public DataStreamProcTimeRowAggregate(RelOptCluster cluster,
RelTraitSet traitSet, RelNode input,
+ RelDataType rowType, String description, LogicalWindow
window) {
+ super(cluster, traitSet, input);
+ this.windowRef = window;
+ this.rowType = rowType;
+ this.description = description;
+ this.winUtil = new WindowAggregateUtil();
+ }
+
+ @Override
+ protected RelDataType deriveRowType() {
+ return super.deriveRowType();
+ }
+
+ @Override
+ public RelNode copy(RelTraitSet traitSet, java.util.List<RelNode>
inputs) {
+
+ if (inputs.size() != 1) {
+ System.err.println(this.getClass().getName() + " :
Input size must be one!");
+ }
+
+ return new DataStreamProcTimeRowAggregate(getCluster(),
traitSet, inputs.get(0), getRowType(), getDescription(),
+ windowRef);
+ }
+
+ @Override
+ public DataStream<Row> translateToPlan(StreamTableEnvironment tableEnv,
Row ignore) {
+
+ TableConfig config = tableEnv.getConfig();
+
+ DataStream<Row> inputDS = ((DataStreamRel)
getInput()).translateToPlan(tableEnv);
+
+ System.out.println(inputDS);
--- End diff --
That should be removed.
> 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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