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From: Stig Rohde Døssing <[email protected]>
Sent: Thursday, August 1, 2019 5:55 AM
To: [email protected] <[email protected]>
Subject: Re: Strange time aggregation behavior exhibited by BaseWindowedBolt

> Does the watermark ever gets generated based on actual clock, window interval
No, not when you're using the .withTimestampField method. The watermark gets 
created on a set (wall clock time) interval, but the watermark value is based 
on the timestamp values extracted from your tuples. The reason this behavior 
makes sense is that when you use .withTimestampField, you're essentially saying 
"use the tuple timestamps to keep track of time, instead of using real wall 
clock time to keep track of time".

No, if tuples 9 and 10 are the last tuples in the stream, they never get 
delivered. The real wall clock time doesn't matter when you use 
.withTimestampField. The only way "time passes" for the watermark generator is 
if we receive new tuples with newer timestamps. If you want to use real wall 
clock time instead, you shouldn't call .withTimestampField. In that case, the 
windowing code would be based on real time instead, so 9 and 10 would get 
delivered as soon as 3 seconds have passed. The disadvantage to using real time 
is that processing becomes a little less predictable when e.g. the machine 
running the processing is slow, or in case you're reprocessing old messages.

> that explains why only first few were getting flushed in time window
Great, happy you found the cause.

Den tor. 1. aug. 2019 kl. 14.04 skrev Sandeep Singh 
<[email protected]<mailto:[email protected]>>:
Thank you very much for the response. Please see my comments inline   sandeep>>

On Thu, Aug 1, 2019 at 5:17 AM Stig Rohde Døssing 
<[email protected]<mailto:[email protected]>> wrote:
Regarding why you need the 5th tuple, it is happening because you are using 
timestamp fields. The windowing code will receive the first 4 tuples and add 
them to the same window. Until it receives the 5th tuple, there is no way to 
tell whether the window is "done", as we might receive more tuples that fall 
within the window. The 5th tuple acts as a trigger that tells the windowing 
code that the window with the first 4 tuples is now over, and should be 
delivered to your bolt.

More specifically, the way it works is that there's a thread running which 
periodically (every 10 seconds in your case) sets a watermark. The watermark is 
set to be the timestamp of the newest received tuple, minus the lag. The 
watermark is then passed on to a trigger policy, which decides how to generate 
windows. The windows are generated from the watermark backwards, so if e.g. 
your watermark is 10, your lag is 2 and your interval is 3, it will try to 
generate windows for 0-2, 2-5, 5-8. Note that any tuples with timestamp 9 and 
10 aren't delivered yet, as you've said you expect up to 2 seconds of lag, so 
it isn't safe to close the window containing them yet. We can't deliver 9 and 
10 until we see a tuple with timestamp 10 plus the lag, so 12.

sandeep>> Got that. Does the watermark ever gets generated based on actual 
clock, window interval? For above example, will tuple with timestamps 9 and 10 
will ever get emitted if tuple 10 was the last tuple in the stream and then 
there is no activity say for more tuples for next 2 minutes?
I think my confusion was that they will eventually flushed out after (window 
interval + lag).

See 
https://github.com/apache/storm/blob/21bb1388414d373572779289edc785c7e5aa52aa/storm-client/src/jvm/org/apache/storm/windowing/WaterMarkEventGenerator.java<https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fapache%2Fstorm%2Fblob%2F21bb1388414d373572779289edc785c7e5aa52aa%2Fstorm-client%2Fsrc%2Fjvm%2Forg%2Fapache%2Fstorm%2Fwindowing%2FWaterMarkEventGenerator.java&data=02%7C01%7Cmaurgi%40microsoft.com%7C825bc2456a524cb6f1cc08d7167f89e0%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637002609349043209&sdata=edMoP2SqtwVZJVXCknkqozGOcshYfcKFLQYkMfR5Ibk%3D&reserved=0>
 and 
https://github.com/apache/storm/blob/925422a5b5ad1c3329a2c2b44db460ae94f70806/storm-client/src/jvm/org/apache/storm/windowing/WatermarkTimeTriggerPolicy.java<https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fapache%2Fstorm%2Fblob%2F925422a5b5ad1c3329a2c2b44db460ae94f70806%2Fstorm-client%2Fsrc%2Fjvm%2Forg%2Fapache%2Fstorm%2Fwindowing%2FWatermarkTimeTriggerPolicy.java&data=02%7C01%7Cmaurgi%40microsoft.com%7C825bc2456a524cb6f1cc08d7167f89e0%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637002609349053210&sdata=nId0RXwbQ4HuZMbRLSA%2BMwITPgxo5bUKrept2j3sKNI%3D&reserved=0>

Regarding why your tuples are getting split, I don't know. Are you maybe 
running multiple tasks of the windowing bolt?

sandeep>> Checked the code I was running only 1 task. However I was using Kafka 
Spout to receive the messages in my topology. It was possible to get tuples 
with higher time to get processed earlier than other. I started sending the 
messaged in blocking mode (wait for previous sent to complete). If the 
watermark and trigger in based on order in which tuples arrived,  that explains 
why only first few were getting flushed in time window


Den tir. 30. jul. 2019 kl. 16.11 skrev Sandeep Singh 
<[email protected]<mailto:[email protected]>>:
Sorry for multiple message with same subject as I had to register with 
different email address.
To follow up on the thread, can someone explain to me why the tuples with same 
timestamp are sometimes sent in two different time windows? And also why 
sending an extra 5th tuple is required before storm invokes execute method? Do 
I need to set a different value for tumbling window duration or lag?
Thank you for your help in advance
Sandeep

On Mon, Jul 29, 2019 at 7:27 PM Sandeep Singh 
<[email protected]<mailto:[email protected]>> wrote:

During testing of my topology which uses Storm's Tumbling window, I see strange 
behavior how my stream of tuples are handled and split into different time 
windows.

I am using a Tumbling window with duration and lag set to 10 seconds:

                val duration = BaseWindowedBolt.Duration.seconds(10)

                
myBolt.withTumblingWindow(duration).withTimestampField("timestampField").withLag(duration)



When I send four tuples with timestamp set to same value "now - 1 second" 
(where now = System.currentTimeMillis()), I see log messages that storm is able 
to extract the time information from tuples. However bolt's 
"execute(inputWindow: TupleWindow)" method never gets invoked. In my test I 
wait for 2 minutes. I do not see any log message about late tuples.



When I send five tuples,  the first four with timestamp  "now - 1 second" and 
last one with "now + 1 hour", I see Storm is able to extract all the five 
tuples.  However the execute(inputWindow: TupleWindow) method is either invoked

  a) only once with first four tuple (the behavior I expected)  or,

  b) twice, first invocation with tuple 1 & 2, second invocation with tuple 3 & 
4. Since all the four tuples have exactly same timestamp, I don't understand 
why tuples are partitined in different time windows.

Also the bolt's execute method never get's invoked with 5th tuple. However, 
sending 5th tuple (which is well outside the time duration window of 10 
seconds) ensure that execute method is called once or twice for the first four 
tuples.


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