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https://issues.apache.org/jira/browse/APEXMALHAR-2085?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15348758#comment-15348758
]
ASF GitHub Bot commented on APEXMALHAR-2085:
--------------------------------------------
Github user chinmaykolhatkar commented on a diff in the pull request:
https://github.com/apache/apex-malhar/pull/319#discussion_r68469300
--- Diff:
library/src/main/java/org/apache/apex/malhar/lib/window/impl/AbstractWindowedOperator.java
---
@@ -0,0 +1,486 @@
+/**
+ * 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.impl;
+
+import java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+
+import javax.validation.ValidationException;
+
+import org.joda.time.Duration;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import org.apache.apex.malhar.lib.window.Accumulation;
+import org.apache.apex.malhar.lib.window.ControlTuple;
+import org.apache.apex.malhar.lib.window.TriggerOption;
+import org.apache.apex.malhar.lib.window.Tuple;
+import org.apache.apex.malhar.lib.window.Window;
+import org.apache.apex.malhar.lib.window.WindowOption;
+import org.apache.apex.malhar.lib.window.WindowState;
+import org.apache.apex.malhar.lib.window.WindowedOperator;
+import org.apache.apex.malhar.lib.window.WindowedStorage;
+import org.apache.hadoop.classification.InterfaceStability;
+
+import com.google.common.base.Function;
+
+import com.datatorrent.api.Context;
+import com.datatorrent.api.DefaultInputPort;
+import com.datatorrent.api.DefaultOutputPort;
+import com.datatorrent.api.annotation.InputPortFieldAnnotation;
+import com.datatorrent.common.util.BaseOperator;
+
+/**
+ * This is the abstract windowed operator class that implements most of
the windowing, triggering, and accumulating
+ * concepts. The subclass of this abstract class is supposed to provide
the implementation of how the accumulated
+ * values are stored in the storage.
+ *
+ */
+@InterfaceStability.Evolving
+public abstract class AbstractWindowedOperator<InputT, OutputT,
DataStorageT extends WindowedStorage, AccumulationT extends Accumulation>
+ extends BaseOperator implements WindowedOperator<InputT>
+{
+
+ protected WindowOption windowOption;
+ protected TriggerOption triggerOption;
+ protected long allowedLatenessMillis = -1;
+ protected WindowedStorage<WindowState> windowStateMap;
+
+ private Function<InputT, Long> timestampExtractor;
+
+ private long currentWatermark;
+ private boolean triggerAtWatermark;
+ private long earlyTriggerCount;
+ private long earlyTriggerMillis;
+ private long lateTriggerCount;
+ private long lateTriggerMillis;
+ private long currentDerivedTimestamp = -1;
+ private long windowWidthMillis;
+ protected DataStorageT dataStorage;
+ protected DataStorageT retractionStorage;
+ protected AccumulationT accumulation;
+
+ private static final transient Logger LOG =
LoggerFactory.getLogger(AbstractWindowedOperator.class);
+
+ public final transient DefaultInputPort<Tuple<InputT>> input = new
DefaultInputPort<Tuple<InputT>>()
+ {
+ @Override
+ public void process(Tuple<InputT> tuple)
+ {
+ processTuple(tuple);
+ }
+ };
+
+ // TODO: This port should be removed when Apex Core has native support
for custom control tuples
+ @InputPortFieldAnnotation(optional = true)
+ public final transient DefaultInputPort<ControlTuple> controlInput = new
DefaultInputPort<ControlTuple>()
+ {
+ @Override
+ public void process(ControlTuple tuple)
+ {
+ if (tuple instanceof ControlTuple.Watermark) {
+ processWatermark((ControlTuple.Watermark)tuple);
+ }
+ }
+ };
+
+
+ // TODO: multiple input ports for join operations
+
+ public final transient DefaultOutputPort<Tuple<OutputT>> output = new
DefaultOutputPort<>();
+
+ // TODO: This port should be removed when Apex Core has native support
for custom control tuples
+ public final transient DefaultOutputPort<ControlTuple> controlOutput =
new DefaultOutputPort<>();
+
+ /**
+ * Process the incoming data tuple
+ *
+ * @param tuple
+ */
+ public void processTuple(Tuple<InputT> tuple)
+ {
+ long timestamp = extractTimestamp(tuple);
--- End diff --
extractTimestamp method is called here, then in getWindowsValue and also in
assignWindow for the same tuple.
If its a TimestampedTuple its fine as as its simple a getter method but if
TimeExtractor is set the operation of extracting timestamp might get costly
depending on the logic in extractor.
Can this call be made only once?
> 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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