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https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15928961#comment-15928961
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ASF GitHub Bot commented on FLINK-5653:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3547#discussion_r106528174
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/aggregate/BoundedProcessingOverAllWindowFunction.scala
---
@@ -0,0 +1,97 @@
+/*
+ * 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.runtime.aggregate
+
+import org.apache.flink.api.java.tuple.Tuple
+import org.apache.flink.types.Row
+import org.apache.flink.configuration.Configuration
+import
org.apache.flink.streaming.api.functions.windowing.RichWindowFunction
+import org.apache.flink.streaming.api.windowing.windows.Window
+import org.apache.flink.util.Collector
+import org.apache.flink.table.functions.AggregateFunction
+import org.apache.flink.api.java.typeutils.RowTypeInfo
+import org.apache.flink.util.Preconditions
+import org.apache.flink.table.functions.Accumulator
+import java.lang.Iterable
+import
org.apache.flink.streaming.api.functions.windowing.RichAllWindowFunction
+
+class BoundedProcessingOverAllWindowFunction[W <: Window](
+ private val aggregates: Array[AggregateFunction[_]],
+ private val aggFields: Array[Int],
+ private val forwardedFieldCount: Int)
+ extends RichAllWindowFunction[Row, Row, W] {
+
+ Preconditions.checkNotNull(aggregates)
+ Preconditions.checkNotNull(aggFields)
+ Preconditions.checkArgument(aggregates.length == aggFields.length)
+
+ private var output: Row = _
+ private var accumulators: Row = _
+ private var reuse: Row = _
+
+ output = new Row(forwardedFieldCount + aggregates.length)
+ if (null == accumulators) {
+ accumulators = new Row(aggregates.length)
+ }
+
+ override def apply(
+ window: W,
+ records: Iterable[Row],
+ out: Collector[Row]): Unit = {
+
+ var i = 0
+ // setting the accumulators for each aggregation
+ while (i < aggregates.length) {
+ accumulators.setField(i, aggregates(i).createAccumulator())
--- End diff --
accumulators can be reset with `aggregate.resetAccumulator(acc)`. So we can
initialize once and reuse them
> 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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