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https://issues.apache.org/jira/browse/APEXMALHAR-2085?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15363475#comment-15363475
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ASF GitHub Bot commented on APEXMALHAR-2085:
--------------------------------------------
Github user vrozov commented on a diff in the pull request:
https://github.com/apache/apex-malhar/pull/319#discussion_r69656309
--- Diff:
library/src/main/java/org/apache/apex/malhar/lib/window/Accumulation.java ---
@@ -0,0 +1,76 @@
+/**
+ * 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.apex.malhar.lib.window;
+
+import org.apache.hadoop.classification.InterfaceStability;
+
+/**
+ * This interface is for the processing part of the WindowedOperator.
+ * We can assume that all stateful processing of the WindowedOperator is a
form of accumulation.
+ *
+ * In most cases, AccumT is the same as OutputT. But in some cases, the
accumulated type and the output type may be
+ * different. For example, if we are doing the AVERAGE of doubles, InputT
will be double, and we need the SUM and the
+ * COUNT stored as type AccumT, and AccumT will be a pair of double and
long, in which double is the sum of the inputs,
+ * and long is the number of inputs. OutputT will be double, because it
represents the average of the inputs.
+ */
[email protected]
+public interface Accumulation<InputT, AccumT, OutputT>
+{
+ /**
+ * Returns the default accumulated value when nothing has been
accumulated
+ *
+ * @return
+ */
+ AccumT defaultAccumulatedValue();
+
+ /**
+ * Accumulates the input to the accumulated value
+ *
+ * @param accumulatedValue
+ * @param input
+ * @return
+ */
+ AccumT accumulate(AccumT accumulatedValue, InputT input);
--- End diff --
My suggestion is to delegate to a class that implements Accumulation
interface handling of accumulation and change interface to
```
void accumulate(InputT input);
void merge(Accumulation accumulatedValue);
OutputT getOutput();
```
The implementation class will need to define how it handles accumulation
and how AccumT is defined. The implementation may use Collection for AccumT or
may use primitive types such as int, long or double to accumulate values.
> Implement Windowed Operators
> ----------------------------
>
> Key: APEXMALHAR-2085
> URL: https://issues.apache.org/jira/browse/APEXMALHAR-2085
> Project: Apache Apex Malhar
> Issue Type: New Feature
> Reporter: Siyuan Hua
> Assignee: David Yan
>
> As per our recent several discussions in the community. A group of Windowed
> Operators that delivers the window semantic follows the google Data Flow
> model(https://cloud.google.com/dataflow/) is very important.
> The operators should be designed and implemented in a way for
> High-level API
> Beam translation
> Easy to use with other popular operator
> {panel:title=Operator Hierarchy}
> Hierarchy of the operators,
> The windowed operators should cover all possible transformations that require
> window, and batch processing is also considered as special window called
> global window
> {code}
> +-------------------+
> +---------> | WindowedOperator | <--------+
> | +--------+----------+ |
> | ^ ^--------------------------------+
> | | | |
> | | | |
> +------+--------+ +------+------+ +-------+-----+ +------+-----+
> |CombineOperator| |GroupOperator| |KeyedOperator| |JoinOperator|
> +---------------+ +-------------+ +------+------+ +-----+------+
> +---------^ ^ ^
> | | |
> +--------+---+ +-----+----+ +----+----+
> |KeyedCombine| |KeyedGroup| | CoGroup |
> +------------+ +----------+ +---------+
> {code}
> Combine operation includes all operations that combine all tuples in one
> window into one or small number of tuples, Group operation group all tuples
> in one window, Join and CoGroup are used to join and group tuples from
> different inputs.
> {panel}
> {panel:title=Components}
> * Window Component
> It includes configuration, window state that should be checkpointed, etc. It
> should support NonMergibleWindow(fixed or slide) MergibleWindow(Session)
> * Trigger
> It should support early trigger, late trigger with customizable trigger
> behaviour
> * Other related components:
> ** Watermark generator, can be plugged into input source to generate watermark
> ** Tuple schema support:
> It should handle either predefined tuple type or give a declarative API to
> describe the user defined tuple class
> {panel}
> Most component API should be reused in High-Level API
> This is the umbrella ticket, separate tickets would be created for different
> components and operators respectively
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