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https://issues.apache.org/jira/browse/STORM-1187?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15057637#comment-15057637
 ] 

ASF GitHub Bot commented on STORM-1187:
---------------------------------------

Github user arunmahadevan commented on a diff in the pull request:

    https://github.com/apache/storm/pull/900#discussion_r47610293
  
    --- Diff: 
storm-core/src/jvm/backtype/storm/windowing/WaterMarkEventGenerator.java ---
    @@ -0,0 +1,110 @@
    +/**
    + * 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 backtype.storm.windowing;
    +
    +import backtype.storm.generated.GlobalStreamId;
    +import backtype.storm.topology.FailedException;
    +import org.slf4j.Logger;
    +import org.slf4j.LoggerFactory;
    +
    +import java.util.Map;
    +import java.util.Set;
    +import java.util.concurrent.ConcurrentHashMap;
    +import java.util.concurrent.ExecutionException;
    +import java.util.concurrent.Executors;
    +import java.util.concurrent.ScheduledExecutorService;
    +import java.util.concurrent.ScheduledFuture;
    +import java.util.concurrent.TimeUnit;
    +
    +/**
    + * Tracks tuples across input streams and periodically emits watermark 
events.
    + * Watermark event timestamp is the minimum of the latest tuple timestamps
    + * across all the input streams (minus the lag). Once a watermark event is 
emitted
    + * any tuple coming with an earlier timestamp can be considered as late 
events.
    + */
    +public class WaterMarkEventGenerator<T> implements Runnable {
    +    private static final Logger LOG = 
LoggerFactory.getLogger(WaterMarkEventGenerator.class);
    +    private final WindowManager<T> windowManager;
    +    private final int eventTsLag;
    +    private final Set<GlobalStreamId> inputStreams;
    +    private final Map<GlobalStreamId, Long> streamToTs;
    +    private final ScheduledExecutorService executorService;
    +    private final ScheduledFuture<?> executorFuture;
    +    private long lastWaterMarkTs = 0;
    +
    +    public WaterMarkEventGenerator(WindowManager<T> windowManager, int 
interval,
    +                                   int eventTsLag, Set<GlobalStreamId> 
inputStreams) {
    +        this.windowManager = windowManager;
    +        streamToTs = new ConcurrentHashMap<>();
    +        executorService = Executors.newSingleThreadScheduledExecutor();
    +        this.executorFuture = executorService.scheduleAtFixedRate(this, 
interval, interval, TimeUnit.MILLISECONDS);
    +        this.eventTsLag = eventTsLag;
    +        this.inputStreams = inputStreams;
    +    }
    +
    +    public void track(GlobalStreamId stream, long ts) {
    +        Long currentVal = streamToTs.get(stream);
    +        if (currentVal == null || ts > currentVal) {
    +            streamToTs.put(stream, ts);
    +        }
    +        checkFailures();
    +    }
    +
    +    @Override
    +    public void run() {
    +        try {
    +            long waterMarkTs = computeWaterMarkTs();
    +            if (waterMarkTs > lastWaterMarkTs) {
    +                this.windowManager.add(new WaterMarkEvent<T>(waterMarkTs - 
eventTsLag));
    +                lastWaterMarkTs = waterMarkTs;
    +            }
    +        } catch (Throwable th) {
    +            LOG.error("Failed while processing watermark event ", th);
    +            throw th;
    +        }
    +    }
    +
    +    /**
    +     * Computes the min ts across all streams.
    +     */
    +    private long computeWaterMarkTs() {
    +        long ts = Long.MIN_VALUE;
    +        // only if some data has arrived on each input stream
    --- End diff --
    
    The minimum of the latest event timestamps across all input streams (minus 
the lag) is considered as the watermark timestamp. This is so that if events 
from one of the streams is delayed more, we don't treat all events from that 
stream as late events.


> Support for late and out of order events in time based windows
> --------------------------------------------------------------
>
>                 Key: STORM-1187
>                 URL: https://issues.apache.org/jira/browse/STORM-1187
>             Project: Apache Storm
>          Issue Type: Sub-task
>            Reporter: Arun Mahadevan
>            Assignee: Arun Mahadevan
>
> Right now the time based windows uses the timestamp when the tuple is 
> received by the bolt. 
> However there are use cases where the tuples can be processed based on the 
> time when they are actually generated vs the time when they are received. So 
> we need to add support for processing events with a time lag and also have 
> some way to specify and read tuple timestamps.



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