Re: what does future do after fn finish ?

[Jacek Grzebyta]

HI,

So things works well. In terms of memory usage anyway. I use 50 main
threads (in process-data-by-condition-set) and 20 for replications
(process-growths). However I found that after good performance in the
beginning it slows down rapid and quick. VisualVM shows the threads usage
is poor - mainly they are waiting. Only 1 claypoole thread works + some
lower level threads managed probably by Clojure, etc. CPU usage is poor as
well. I guess the reason is on the lower - Java classes level with IO
operations bottleneck. IMO they are working by blocking. That why I wanted
to separate them. However IO speed operations go down as well.
I've tried async channels but that they were flooded and some data where
lost for some reason.

Regards,
Jacek


On 3 February 2018 at 00:14, Justin Smith  wrote:

> -> is just a list transform performed after reading your code into a list
> data structure containing symbols, and before compiling to byte code - it
> doesn't do anything directly.
>
> On Fri, Feb 2, 2018 at 3:55 PM Jacek Grzebyta 
> wrote:
>
>> OK I found what makes the memory leak.
>>
>> In the project I work with I use a  java Model class which is java
>> Collection proxy/facade for a single transaction. Unfortunately it's not
>> thread safe. In a few places I passed single instance of model into several
>> threads Also I requested the instance with -> which makes new thread as
>> well. I was surprised that -> makes trouble but after thinking that might
>> be expected. Especially that internally the wrapper doesn't do simple
>> mapping - it uses some iterator, etc. Anyway the machinery is fragile. It
>> seems I need to rewrite code and replace all multithreading parts by
>> something simpler.
>>
>>
>>
>> If you want see the stacktrace just look at:
>> https://github.com/jgrzebyta/triple-loader/issues/53
>>
>> On 2 February 2018 at 11:16, Jacek Grzebyta 
>> wrote:
>>
>>>
>>> On 2 February 2018 at 08:34, Niels van Klaveren <
>>> niels.vanklave...@gmail.com> wrote:
>>>
 +1 for Claypoole, it removed the needs of using agents or futures in
 95% of the cases in my code.


>>> Thanks a lot. I modify the code using claypoole. I imagine with-shutdown
>>> will close the pool properly after finish all tasks so there is no need to
>>> watch them?
>>>
>>> J
>>>
>>>
>>
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Re: what does future do after fn finish ?

[Justin Smith]

-> is just a list transform performed after reading your code into a list
data structure containing symbols, and before compiling to byte code - it
doesn't do anything directly.

On Fri, Feb 2, 2018 at 3:55 PM Jacek Grzebyta 
wrote:

> OK I found what makes the memory leak.
>
> In the project I work with I use a  java Model class which is java
> Collection proxy/facade for a single transaction. Unfortunately it's not
> thread safe. In a few places I passed single instance of model into several
> threads Also I requested the instance with -> which makes new thread as
> well. I was surprised that -> makes trouble but after thinking that might
> be expected. Especially that internally the wrapper doesn't do simple
> mapping - it uses some iterator, etc. Anyway the machinery is fragile. It
> seems I need to rewrite code and replace all multithreading parts by
> something simpler.
>
>
>
> If you want see the stacktrace just look at:
> https://github.com/jgrzebyta/triple-loader/issues/53
>
> On 2 February 2018 at 11:16, Jacek Grzebyta 
> wrote:
>
>>
>> On 2 February 2018 at 08:34, Niels van Klaveren <
>> niels.vanklave...@gmail.com> wrote:
>>
>>> +1 for Claypoole, it removed the needs of using agents or futures in 95%
>>> of the cases in my code.
>>>
>>>
>> Thanks a lot. I modify the code using claypoole. I imagine with-shutdown
>> will close the pool properly after finish all tasks so there is no need to
>> watch them?
>>
>> J
>>
>>
>
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Re: what does future do after fn finish ?

[Jacek Grzebyta]

OK I found what makes the memory leak.

In the project I work with I use a  java Model class which is java
Collection proxy/facade for a single transaction. Unfortunately it's not
thread safe. In a few places I passed single instance of model into several
threads Also I requested the instance with -> which makes new thread as
well. I was surprised that -> makes trouble but after thinking that might
be expected. Especially that internally the wrapper doesn't do simple
mapping - it uses some iterator, etc. Anyway the machinery is fragile. It
seems I need to rewrite code and replace all multithreading parts by
something simpler.



If you want see the stacktrace just look at:
https://github.com/jgrzebyta/triple-loader/issues/53

On 2 February 2018 at 11:16, Jacek Grzebyta  wrote:

>
> On 2 February 2018 at 08:34, Niels van Klaveren <
> niels.vanklave...@gmail.com> wrote:
>
>> +1 for Claypoole, it removed the needs of using agents or futures in 95%
>> of the cases in my code.
>>
>>
> Thanks a lot. I modify the code using claypoole. I imagine with-shutdown
> will close the pool properly after finish all tasks so there is no need to
> watch them?
>
> J
>
>

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Re: what does future do after fn finish ?

[Jacek Grzebyta]

On 2 February 2018 at 08:34, Niels van Klaveren  wrote:

> +1 for Claypoole, it removed the needs of using agents or futures in 95%
> of the cases in my code.
>
>
Thanks a lot. I modify the code using claypoole. I imagine with-shutdown
will close the pool properly after finish all tasks so there is no need to
watch them?

J

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Re: what does future do after fn finish ?

[Niels van Klaveren]

+1 for Claypoole, it removed the needs of using agents or futures in 95% of 
the cases in my code.

On Thursday, February 1, 2018 at 9:54:36 PM UTC+1, Alan Thompson wrote:
>
> You may find that using the Claypoole library is the easiest way to handle 
> threadpools:   https://github.com/TheClimateCorporation/claypoole
> Alan
>
> On Thu, Feb 1, 2018 at 11:16 AM, Justin Smith  > wrote:
>
>> yes, that's the idea exactly
>>
>> also, you might want more fine grained control of how much parallelism 
>> occurs (eg. if every thread is writing to the same physical device, you can 
>> often get better throughput by not parallelizing at all, or keeping the 
>> parallelism quite limited - it's worth experimenting) - there are good ways 
>> to control that using ThreadPoolExecutor directly, or using 
>> clojure.lang.PersistentQueue/EMPTY as a control construct, or core.async 
>> channels, or ztellman's manifold library, or the claypoole threading library
>>
>> On Thu, Feb 1, 2018, 03:44 Jacek Grzebyta > > wrote:
>>
>>> Thanks folks. I see now! It should be a list of agents not list of 
>>> futures within agent.  Also any task sent to a agent is processed 
>>> within a thread anyway so I do not need to add future...
>>>
>>> On 1 February 2018 at 02:17, John Newman >> > wrote:
>>>
 Ah, he's using one agent, I see.

 On Jan 31, 2018 9:15 PM, "John Newman"  
 wrote:

> Multiple sen-doffs to one agent will serialize it's calls, but 
> spawning agents on each new task will spawn threads on a bounded thread 
> pool, I believe.
>
> On Jan 31, 2018 8:32 PM, "Justin Smith"  > wrote:
>
>> Doing all the actions via one agent means that the actions are 
>> serialized though - you end up with no performance improvement over 
>> doing 
>> them all in a doseq in one future - the right way to do this tends to be 
>> trickier than it looks at first glance, and depends on your 
>> requirements. 
>> agents, the claypoole library, and reducers are all potentially useful. 
>> If 
>> parallelization leads to complex coordination needs, core.async can help 
>> too.
>>
>> On Wed, Jan 31, 2018 at 5:18 PM John Newman > > wrote:
>>
>>> Agents manage a pool of threads for you. Try doing it without the 
>>> future call and see if that works (unless you're trying to do something 
>>> else).
>>>
>>> John
>>>
>>> On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta >> > wrote:
>>>
 Thanks a lot. I will check it tomorrow. 

 J

 On 1 Feb 2018 12:12 a.m., "Justin Smith"  wrote:

> this is exactly the kind of problem code I was describing - 
> there's no backpressure on existing future tasks to hold up the 
> launching 
> of more futures - the work done by the agent calling conj is 
> negligible. 
> You need to control the size of the pool of threads used, and you 
> need to 
> impose back-pressure.
>
> On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta <
> grzeby...@gmail.com > wrote:
>
>> On 31 January 2018 at 18:08, James Reeves > > wrote:
>>
>>> On 31 January 2018 at 17:59, Jacek Grzebyta >> > wrote:
>>>
 I have application with quite intense tripe store populating 
 ~30/40 k records per chunk (139 portions). The data are wrapped 
 within the 
 future:

 (conj agent (future (apply task args)))

  and that all together is send-off into (agent []). 

>>>
>>> What is "agent"? The first line of code indicates that it's a 
>>> local collection shadowing the code function, while the second code 
>>> snippet 
>>> indicates that you're using the core agent function.
>>>
>>> Also why are you sending off to an agent?
>>>
>>  
>> I have ~8sec computing task for each input dataset which 
>> generates those records. After that I write it into disk (in 
>> software-specific transaction). I just wanted to separate hard 
>> computing 
>> and io operations. I created a side-effect method which is injected 
>> together with the dataset into a future. The futures are async 
>> collected 
>> within a list wrapped in agent. After the computing the main thread 
>> is 
>> waiting until all io tasks will be finished. 
>>  
>>
>>>
>>> At the end of the main thread function I just use await-for and 
 after that:

Re: what does future do after fn finish ?

[Alan Thompson]

You may find that using the Claypoole library is the easiest way to handle
threadpools:   https://github.com/TheClimateCorporation/claypoole
Alan

On Thu, Feb 1, 2018 at 11:16 AM, Justin Smith  wrote:

> yes, that's the idea exactly
>
> also, you might want more fine grained control of how much parallelism
> occurs (eg. if every thread is writing to the same physical device, you can
> often get better throughput by not parallelizing at all, or keeping the
> parallelism quite limited - it's worth experimenting) - there are good ways
> to control that using ThreadPoolExecutor directly, or using
> clojure.lang.PersistentQueue/EMPTY as a control construct, or core.async
> channels, or ztellman's manifold library, or the claypoole threading library
>
> On Thu, Feb 1, 2018, 03:44 Jacek Grzebyta  wrote:
>
>> Thanks folks. I see now! It should be a list of agents not list of
>> futures within agent.  Also any task sent to a agent is processed
>> within a thread anyway so I do not need to add future...
>>
>> On 1 February 2018 at 02:17, John Newman  wrote:
>>
>>> Ah, he's using one agent, I see.
>>>
>>> On Jan 31, 2018 9:15 PM, "John Newman"  wrote:
>>>
 Multiple sen-doffs to one agent will serialize it's calls, but spawning
 agents on each new task will spawn threads on a bounded thread pool, I
 believe.

 On Jan 31, 2018 8:32 PM, "Justin Smith"  wrote:

> Doing all the actions via one agent means that the actions are
> serialized though - you end up with no performance improvement over doing
> them all in a doseq in one future - the right way to do this tends to be
> trickier than it looks at first glance, and depends on your requirements.
> agents, the claypoole library, and reducers are all potentially useful. If
> parallelization leads to complex coordination needs, core.async can help
> too.
>
> On Wed, Jan 31, 2018 at 5:18 PM John Newman  wrote:
>
>> Agents manage a pool of threads for you. Try doing it without the
>> future call and see if that works (unless you're trying to do something
>> else).
>>
>> John
>>
>> On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta <
>> grzebyta@gmail.com> wrote:
>>
>>> Thanks a lot. I will check it tomorrow.
>>>
>>> J
>>>
>>> On 1 Feb 2018 12:12 a.m., "Justin Smith" 
>>> wrote:
>>>
 this is exactly the kind of problem code I was describing - there's
 no backpressure on existing future tasks to hold up the launching of 
 more
 futures - the work done by the agent calling conj is negligible. You 
 need
 to control the size of the pool of threads used, and you need to impose
 back-pressure.

 On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta <
 grzebyta@gmail.com> wrote:

> On 31 January 2018 at 18:08, James Reeves 
> wrote:
>
>> On 31 January 2018 at 17:59, Jacek Grzebyta <
>> grzebyta@gmail.com> wrote:
>>
>>> I have application with quite intense tripe store populating
>>> ~30/40 k records per chunk (139 portions). The data are wrapped 
>>> within the
>>> future:
>>>
>>> (conj agent (future (apply task args)))
>>>
>>>  and that all together is send-off into (agent []).
>>>
>>
>> What is "agent"? The first line of code indicates that it's a
>> local collection shadowing the code function, while the second code 
>> snippet
>> indicates that you're using the core agent function.
>>
>> Also why are you sending off to an agent?
>>
>
> I have ~8sec computing task for each input dataset which generates
> those records. After that I write it into disk (in software-specific
> transaction). I just wanted to separate hard computing and io 
> operations. I
> created a side-effect method which is injected together with the 
> dataset
> into a future. The futures are async collected within a list wrapped 
> in
> agent. After the computing the main thread is waiting until all io 
> tasks
> will be finished.
>
>
>>
>> At the end of the main thread function I just use await-for and
>>> after that:
>>>
>>> (reduce + (map #(deref %) @data-loading-tasks))
>>>
>>
> As a control, tasks return number of written records.
>
>
>
>>
>>> For some reason I see the happy collecting (see attached
>>> screenshot of jconsole).
>>>
>>
>> "happy" = "heap"?
>>
>
> Both. As 

Re: what does future do after fn finish ?

[Justin Smith]

yes, that's the idea exactly

also, you might want more fine grained control of how much parallelism
occurs (eg. if every thread is writing to the same physical device, you can
often get better throughput by not parallelizing at all, or keeping the
parallelism quite limited - it's worth experimenting) - there are good ways
to control that using ThreadPoolExecutor directly, or using
clojure.lang.PersistentQueue/EMPTY as a control construct, or core.async
channels, or ztellman's manifold library, or the claypoole threading library

On Thu, Feb 1, 2018, 03:44 Jacek Grzebyta  wrote:

> Thanks folks. I see now! It should be a list of agents not list of futures
> within agent.  Also any task sent to a agent is processed within a
> thread anyway so I do not need to add future...
>
> On 1 February 2018 at 02:17, John Newman  wrote:
>
>> Ah, he's using one agent, I see.
>>
>> On Jan 31, 2018 9:15 PM, "John Newman"  wrote:
>>
>>> Multiple sen-doffs to one agent will serialize it's calls, but spawning
>>> agents on each new task will spawn threads on a bounded thread pool, I
>>> believe.
>>>
>>> On Jan 31, 2018 8:32 PM, "Justin Smith"  wrote:
>>>
 Doing all the actions via one agent means that the actions are
 serialized though - you end up with no performance improvement over doing
 them all in a doseq in one future - the right way to do this tends to be
 trickier than it looks at first glance, and depends on your requirements.
 agents, the claypoole library, and reducers are all potentially useful. If
 parallelization leads to complex coordination needs, core.async can help
 too.

 On Wed, Jan 31, 2018 at 5:18 PM John Newman  wrote:

> Agents manage a pool of threads for you. Try doing it without the
> future call and see if that works (unless you're trying to do something
> else).
>
> John
>
> On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta <
> grzebyta@gmail.com> wrote:
>
>> Thanks a lot. I will check it tomorrow.
>>
>> J
>>
>> On 1 Feb 2018 12:12 a.m., "Justin Smith" 
>> wrote:
>>
>>> this is exactly the kind of problem code I was describing - there's
>>> no backpressure on existing future tasks to hold up the launching of 
>>> more
>>> futures - the work done by the agent calling conj is negligible. You 
>>> need
>>> to control the size of the pool of threads used, and you need to impose
>>> back-pressure.
>>>
>>> On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta <
>>> grzebyta@gmail.com> wrote:
>>>
 On 31 January 2018 at 18:08, James Reeves 
 wrote:

> On 31 January 2018 at 17:59, Jacek Grzebyta <
> grzebyta@gmail.com> wrote:
>
>> I have application with quite intense tripe store populating
>> ~30/40 k records per chunk (139 portions). The data are wrapped 
>> within the
>> future:
>>
>> (conj agent (future (apply task args)))
>>
>>  and that all together is send-off into (agent []).
>>
>
> What is "agent"? The first line of code indicates that it's a
> local collection shadowing the code function, while the second code 
> snippet
> indicates that you're using the core agent function.
>
> Also why are you sending off to an agent?
>

 I have ~8sec computing task for each input dataset which generates
 those records. After that I write it into disk (in software-specific
 transaction). I just wanted to separate hard computing and io 
 operations. I
 created a side-effect method which is injected together with the 
 dataset
 into a future. The futures are async collected within a list wrapped in
 agent. After the computing the main thread is waiting until all io 
 tasks
 will be finished.


>
> At the end of the main thread function I just use await-for and
>> after that:
>>
>> (reduce + (map #(deref %) @data-loading-tasks))
>>
>
 As a control, tasks return number of written records.



>
>> For some reason I see the happy collecting (see attached
>> screenshot of jconsole).
>>
>
> "happy" = "heap"?
>

 Both. As you can see on attached screenshot the heap usage grows
 easy until aver. ~2 1/4 G than keep that  for a few minutes. In that 
 moment
 I stopped. After that starts grow till ~4G with tendency to do jumps a 
 bit
 more that 4G.


>
>
>> After seeing the source code of future I suppose 

Re: what does future do after fn finish ?

[Jacek Grzebyta]

Thanks folks. I see now! It should be a list of agents not list of futures
within agent.  Also any task sent to a agent is processed within a
thread anyway so I do not need to add future...

On 1 February 2018 at 02:17, John Newman  wrote:

> Ah, he's using one agent, I see.
>
> On Jan 31, 2018 9:15 PM, "John Newman"  wrote:
>
>> Multiple sen-doffs to one agent will serialize it's calls, but spawning
>> agents on each new task will spawn threads on a bounded thread pool, I
>> believe.
>>
>> On Jan 31, 2018 8:32 PM, "Justin Smith"  wrote:
>>
>>> Doing all the actions via one agent means that the actions are
>>> serialized though - you end up with no performance improvement over doing
>>> them all in a doseq in one future - the right way to do this tends to be
>>> trickier than it looks at first glance, and depends on your requirements.
>>> agents, the claypoole library, and reducers are all potentially useful. If
>>> parallelization leads to complex coordination needs, core.async can help
>>> too.
>>>
>>> On Wed, Jan 31, 2018 at 5:18 PM John Newman  wrote:
>>>
 Agents manage a pool of threads for you. Try doing it without the
 future call and see if that works (unless you're trying to do something
 else).

 John

 On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta  wrote:

> Thanks a lot. I will check it tomorrow.
>
> J
>
> On 1 Feb 2018 12:12 a.m., "Justin Smith"  wrote:
>
>> this is exactly the kind of problem code I was describing - there's
>> no backpressure on existing future tasks to hold up the launching of more
>> futures - the work done by the agent calling conj is negligible. You need
>> to control the size of the pool of threads used, and you need to impose
>> back-pressure.
>>
>> On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta <
>> grzebyta@gmail.com> wrote:
>>
>>> On 31 January 2018 at 18:08, James Reeves 
>>> wrote:
>>>
 On 31 January 2018 at 17:59, Jacek Grzebyta  wrote:

> I have application with quite intense tripe store populating
> ~30/40 k records per chunk (139 portions). The data are wrapped 
> within the
> future:
>
> (conj agent (future (apply task args)))
>
>  and that all together is send-off into (agent []).
>

 What is "agent"? The first line of code indicates that it's a local
 collection shadowing the code function, while the second code snippet
 indicates that you're using the core agent function.

 Also why are you sending off to an agent?

>>>
>>> I have ~8sec computing task for each input dataset which generates
>>> those records. After that I write it into disk (in software-specific
>>> transaction). I just wanted to separate hard computing and io 
>>> operations. I
>>> created a side-effect method which is injected together with the dataset
>>> into a future. The futures are async collected within a list wrapped in
>>> agent. After the computing the main thread is waiting until all io tasks
>>> will be finished.
>>>
>>>

 At the end of the main thread function I just use await-for and
> after that:
>
> (reduce + (map #(deref %) @data-loading-tasks))
>

>>> As a control, tasks return number of written records.
>>>
>>>
>>>

> For some reason I see the happy collecting (see attached
> screenshot of jconsole).
>

 "happy" = "heap"?

>>>
>>> Both. As you can see on attached screenshot the heap usage grows
>>> easy until aver. ~2 1/4 G than keep that  for a few minutes. In that 
>>> moment
>>> I stopped. After that starts grow till ~4G with tendency to do jumps a 
>>> bit
>>> more that 4G.
>>>
>>>


> After seeing the source code of future I suppose that the memory
> (data are kept as #{} set) is not released. The task returns only 
> integer
> so I do not think that might cause the problem.
>

 Can you provide more detail? You keep alluding to things that you
 don't provide code for, such as the sets of data.

>>>
>>>
>>> The code is attached. However the important code is
>>>
>>> L123 .
>>>   (let [;; keeps all data loading futures.
>>> ;; waiting until all futures are finished
>>> ;; should be done outside the main loop
>>> data-loading-tasks (agent [])]
>>>
>>> L128
>>> (doseq
>>>  (let [r1 (long operation)]   L133
>>>  (doseq
>>> (let [r2 

Re: what does future do after fn finish ?

[John Newman]

Ah, he's using one agent, I see.

On Jan 31, 2018 9:15 PM, "John Newman"  wrote:

> Multiple sen-doffs to one agent will serialize it's calls, but spawning
> agents on each new task will spawn threads on a bounded thread pool, I
> believe.
>
> On Jan 31, 2018 8:32 PM, "Justin Smith"  wrote:
>
>> Doing all the actions via one agent means that the actions are serialized
>> though - you end up with no performance improvement over doing them all in
>> a doseq in one future - the right way to do this tends to be trickier than
>> it looks at first glance, and depends on your requirements. agents, the
>> claypoole library, and reducers are all potentially useful. If
>> parallelization leads to complex coordination needs, core.async can help
>> too.
>>
>> On Wed, Jan 31, 2018 at 5:18 PM John Newman  wrote:
>>
>>> Agents manage a pool of threads for you. Try doing it without the future
>>> call and see if that works (unless you're trying to do something else).
>>>
>>> John
>>>
>>> On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta 
>>> wrote:
>>>
 Thanks a lot. I will check it tomorrow.

 J

 On 1 Feb 2018 12:12 a.m., "Justin Smith"  wrote:

> this is exactly the kind of problem code I was describing - there's no
> backpressure on existing future tasks to hold up the launching of more
> futures - the work done by the agent calling conj is negligible. You need
> to control the size of the pool of threads used, and you need to impose
> back-pressure.
>
> On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta 
> wrote:
>
>> On 31 January 2018 at 18:08, James Reeves 
>> wrote:
>>
>>> On 31 January 2018 at 17:59, Jacek Grzebyta 
>>> wrote:
>>>
 I have application with quite intense tripe store populating ~30/40
 k records per chunk (139 portions). The data are wrapped within the 
 future:

 (conj agent (future (apply task args)))

  and that all together is send-off into (agent []).

>>>
>>> What is "agent"? The first line of code indicates that it's a local
>>> collection shadowing the code function, while the second code snippet
>>> indicates that you're using the core agent function.
>>>
>>> Also why are you sending off to an agent?
>>>
>>
>> I have ~8sec computing task for each input dataset which generates
>> those records. After that I write it into disk (in software-specific
>> transaction). I just wanted to separate hard computing and io 
>> operations. I
>> created a side-effect method which is injected together with the dataset
>> into a future. The futures are async collected within a list wrapped in
>> agent. After the computing the main thread is waiting until all io tasks
>> will be finished.
>>
>>
>>>
>>> At the end of the main thread function I just use await-for and
 after that:

 (reduce + (map #(deref %) @data-loading-tasks))

>>>
>> As a control, tasks return number of written records.
>>
>>
>>
>>>
 For some reason I see the happy collecting (see attached screenshot
 of jconsole).

>>>
>>> "happy" = "heap"?
>>>
>>
>> Both. As you can see on attached screenshot the heap usage grows easy
>> until aver. ~2 1/4 G than keep that  for a few minutes. In that moment I
>> stopped. After that starts grow till ~4G with tendency to do jumps a bit
>> more that 4G.
>>
>>
>>>
>>>
 After seeing the source code of future I suppose that the memory
 (data are kept as #{} set) is not released. The task returns only 
 integer
 so I do not think that might cause the problem.

>>>
>>> Can you provide more detail? You keep alluding to things that you
>>> don't provide code for, such as the sets of data.
>>>
>>
>>
>> The code is attached. However the important code is
>>
>> L123 .
>>   (let [;; keeps all data loading futures.
>> ;; waiting until all futures are finished
>> ;; should be done outside the main loop
>> data-loading-tasks (agent [])]
>>
>> L128
>> (doseq
>>  (let [r1 (long operation)]   L133
>>  (doseq
>> (let [r2 (v.v. long)]   L155
>>
>>   L163   (send-off data-loading-task conj-task)
>>
>>  )
>>  )
>> )
>> )
>>
>>
>> I guess first I will move data-loading-tasks list into one of inner
>> lets. Also I will create within an injecting function a separate abstract
>> function let inside. The task will populate tmp variable which will be
>> returned as a 

Re: what does future do after fn finish ?

[John Newman]

Multiple sen-doffs to one agent will serialize it's calls, but spawning
agents on each new task will spawn threads on a bounded thread pool, I
believe.

On Jan 31, 2018 8:32 PM, "Justin Smith"  wrote:

> Doing all the actions via one agent means that the actions are serialized
> though - you end up with no performance improvement over doing them all in
> a doseq in one future - the right way to do this tends to be trickier than
> it looks at first glance, and depends on your requirements. agents, the
> claypoole library, and reducers are all potentially useful. If
> parallelization leads to complex coordination needs, core.async can help
> too.
>
> On Wed, Jan 31, 2018 at 5:18 PM John Newman  wrote:
>
>> Agents manage a pool of threads for you. Try doing it without the future
>> call and see if that works (unless you're trying to do something else).
>>
>> John
>>
>> On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta 
>> wrote:
>>
>>> Thanks a lot. I will check it tomorrow.
>>>
>>> J
>>>
>>> On 1 Feb 2018 12:12 a.m., "Justin Smith"  wrote:
>>>
 this is exactly the kind of problem code I was describing - there's no
 backpressure on existing future tasks to hold up the launching of more
 futures - the work done by the agent calling conj is negligible. You need
 to control the size of the pool of threads used, and you need to impose
 back-pressure.

 On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta 
 wrote:

> On 31 January 2018 at 18:08, James Reeves 
> wrote:
>
>> On 31 January 2018 at 17:59, Jacek Grzebyta 
>> wrote:
>>
>>> I have application with quite intense tripe store populating ~30/40
>>> k records per chunk (139 portions). The data are wrapped within the 
>>> future:
>>>
>>> (conj agent (future (apply task args)))
>>>
>>>  and that all together is send-off into (agent []).
>>>
>>
>> What is "agent"? The first line of code indicates that it's a local
>> collection shadowing the code function, while the second code snippet
>> indicates that you're using the core agent function.
>>
>> Also why are you sending off to an agent?
>>
>
> I have ~8sec computing task for each input dataset which generates
> those records. After that I write it into disk (in software-specific
> transaction). I just wanted to separate hard computing and io operations. 
> I
> created a side-effect method which is injected together with the dataset
> into a future. The futures are async collected within a list wrapped in
> agent. After the computing the main thread is waiting until all io tasks
> will be finished.
>
>
>>
>> At the end of the main thread function I just use await-for and after
>>> that:
>>>
>>> (reduce + (map #(deref %) @data-loading-tasks))
>>>
>>
> As a control, tasks return number of written records.
>
>
>
>>
>>> For some reason I see the happy collecting (see attached screenshot
>>> of jconsole).
>>>
>>
>> "happy" = "heap"?
>>
>
> Both. As you can see on attached screenshot the heap usage grows easy
> until aver. ~2 1/4 G than keep that  for a few minutes. In that moment I
> stopped. After that starts grow till ~4G with tendency to do jumps a bit
> more that 4G.
>
>
>>
>>
>>> After seeing the source code of future I suppose that the memory
>>> (data are kept as #{} set) is not released. The task returns only 
>>> integer
>>> so I do not think that might cause the problem.
>>>
>>
>> Can you provide more detail? You keep alluding to things that you
>> don't provide code for, such as the sets of data.
>>
>
>
> The code is attached. However the important code is
>
> L123 .
>   (let [;; keeps all data loading futures.
> ;; waiting until all futures are finished
> ;; should be done outside the main loop
> data-loading-tasks (agent [])]
>
> L128
> (doseq
>  (let [r1 (long operation)]   L133
>  (doseq
> (let [r2 (v.v. long)]   L155
>
>   L163   (send-off data-loading-task conj-task)
>
>  )
>  )
> )
> )
>
>
> I guess first I will move data-loading-tasks list into one of inner
> lets. Also I will create within an injecting function a separate abstract
> function let inside. The task will populate tmp variable which will be
> returned as a future result:
>
>
> L114 (conj agent (future (apply (fn [] (let [result (apply task
> args)]  result)
>
>
>>
>> --
>> James Reeves
>> booleanknot.com
>>
>> --
>> You received this message 

Re: what does future do after fn finish ?

[Justin Smith]

Doing all the actions via one agent means that the actions are serialized
though - you end up with no performance improvement over doing them all in
a doseq in one future - the right way to do this tends to be trickier than
it looks at first glance, and depends on your requirements. agents, the
claypoole library, and reducers are all potentially useful. If
parallelization leads to complex coordination needs, core.async can help
too.

On Wed, Jan 31, 2018 at 5:18 PM John Newman  wrote:

> Agents manage a pool of threads for you. Try doing it without the future
> call and see if that works (unless you're trying to do something else).
>
> John
>
> On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta 
> wrote:
>
>> Thanks a lot. I will check it tomorrow.
>>
>> J
>>
>> On 1 Feb 2018 12:12 a.m., "Justin Smith"  wrote:
>>
>>> this is exactly the kind of problem code I was describing - there's no
>>> backpressure on existing future tasks to hold up the launching of more
>>> futures - the work done by the agent calling conj is negligible. You need
>>> to control the size of the pool of threads used, and you need to impose
>>> back-pressure.
>>>
>>> On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta 
>>> wrote:
>>>
 On 31 January 2018 at 18:08, James Reeves 
 wrote:

> On 31 January 2018 at 17:59, Jacek Grzebyta 
> wrote:
>
>> I have application with quite intense tripe store populating ~30/40 k
>> records per chunk (139 portions). The data are wrapped within the future:
>>
>> (conj agent (future (apply task args)))
>>
>>  and that all together is send-off into (agent []).
>>
>
> What is "agent"? The first line of code indicates that it's a local
> collection shadowing the code function, while the second code snippet
> indicates that you're using the core agent function.
>
> Also why are you sending off to an agent?
>

 I have ~8sec computing task for each input dataset which generates
 those records. After that I write it into disk (in software-specific
 transaction). I just wanted to separate hard computing and io operations. I
 created a side-effect method which is injected together with the dataset
 into a future. The futures are async collected within a list wrapped in
 agent. After the computing the main thread is waiting until all io tasks
 will be finished.


>
> At the end of the main thread function I just use await-for and after
>> that:
>>
>> (reduce + (map #(deref %) @data-loading-tasks))
>>
>
 As a control, tasks return number of written records.



>
>> For some reason I see the happy collecting (see attached screenshot
>> of jconsole).
>>
>
> "happy" = "heap"?
>

 Both. As you can see on attached screenshot the heap usage grows easy
 until aver. ~2 1/4 G than keep that  for a few minutes. In that moment I
 stopped. After that starts grow till ~4G with tendency to do jumps a bit
 more that 4G.


>
>
>> After seeing the source code of future I suppose that the memory
>> (data are kept as #{} set) is not released. The task returns only integer
>> so I do not think that might cause the problem.
>>
>
> Can you provide more detail? You keep alluding to things that you
> don't provide code for, such as the sets of data.
>


 The code is attached. However the important code is

 L123 .
   (let [;; keeps all data loading futures.
 ;; waiting until all futures are finished
 ;; should be done outside the main loop
 data-loading-tasks (agent [])]

 L128
 (doseq
  (let [r1 (long operation)]   L133
  (doseq
 (let [r2 (v.v. long)]   L155

   L163   (send-off data-loading-task conj-task)

  )
  )
 )
 )


 I guess first I will move data-loading-tasks list into one of inner
 lets. Also I will create within an injecting function a separate abstract
 function let inside. The task will populate tmp variable which will be
 returned as a future result:


 L114 (conj agent (future (apply (fn [] (let [result (apply task args)]
 result)


>
> --
> James Reeves
> booleanknot.com
>
> --
> You received this message because you are subscribed to the Google
> Groups "Clojure" group.
> To post to this group, send email to clojure@googlegroups.com
> Note that posts from new members are moderated - please be patient
> with your first post.
> To unsubscribe from this group, send email to
> clojure+unsubscr...@googlegroups.com
> For more options, visit this group at
> 

Re: what does future do after fn finish ?

[John Newman]

Agents manage a pool of threads for you. Try doing it without the future
call and see if that works (unless you're trying to do something else).

John

On Wed, Jan 31, 2018 at 7:31 PM, Jacek Grzebyta 
wrote:

> Thanks a lot. I will check it tomorrow.
>
> J
>
> On 1 Feb 2018 12:12 a.m., "Justin Smith"  wrote:
>
>> this is exactly the kind of problem code I was describing - there's no
>> backpressure on existing future tasks to hold up the launching of more
>> futures - the work done by the agent calling conj is negligible. You need
>> to control the size of the pool of threads used, and you need to impose
>> back-pressure.
>>
>> On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta 
>> wrote:
>>
>>> On 31 January 2018 at 18:08, James Reeves  wrote:
>>>
 On 31 January 2018 at 17:59, Jacek Grzebyta 
 wrote:

> I have application with quite intense tripe store populating ~30/40 k
> records per chunk (139 portions). The data are wrapped within the future:
>
> (conj agent (future (apply task args)))
>
>  and that all together is send-off into (agent []).
>

 What is "agent"? The first line of code indicates that it's a local
 collection shadowing the code function, while the second code snippet
 indicates that you're using the core agent function.

 Also why are you sending off to an agent?

>>>
>>> I have ~8sec computing task for each input dataset which generates those
>>> records. After that I write it into disk (in software-specific
>>> transaction). I just wanted to separate hard computing and io operations. I
>>> created a side-effect method which is injected together with the dataset
>>> into a future. The futures are async collected within a list wrapped in
>>> agent. After the computing the main thread is waiting until all io tasks
>>> will be finished.
>>>
>>>

 At the end of the main thread function I just use await-for and after
> that:
>
> (reduce + (map #(deref %) @data-loading-tasks))
>

>>> As a control, tasks return number of written records.
>>>
>>>
>>>

> For some reason I see the happy collecting (see attached screenshot of
> jconsole).
>

 "happy" = "heap"?

>>>
>>> Both. As you can see on attached screenshot the heap usage grows easy
>>> until aver. ~2 1/4 G than keep that  for a few minutes. In that moment I
>>> stopped. After that starts grow till ~4G with tendency to do jumps a bit
>>> more that 4G.
>>>
>>>


> After seeing the source code of future I suppose that the memory (data
> are kept as #{} set) is not released. The task returns only integer so I 
> do
> not think that might cause the problem.
>

 Can you provide more detail? You keep alluding to things that you don't
 provide code for, such as the sets of data.

>>>
>>>
>>> The code is attached. However the important code is
>>>
>>> L123 .
>>>   (let [;; keeps all data loading futures.
>>> ;; waiting until all futures are finished
>>> ;; should be done outside the main loop
>>> data-loading-tasks (agent [])]
>>>
>>> L128
>>> (doseq
>>>  (let [r1 (long operation)]   L133
>>>  (doseq
>>> (let [r2 (v.v. long)]   L155
>>>
>>>   L163   (send-off data-loading-task conj-task)
>>>
>>>  )
>>>  )
>>> )
>>> )
>>>
>>>
>>> I guess first I will move data-loading-tasks list into one of inner
>>> lets. Also I will create within an injecting function a separate abstract
>>> function let inside. The task will populate tmp variable which will be
>>> returned as a future result:
>>>
>>>
>>> L114 (conj agent (future (apply (fn [] (let [result (apply task args)]
>>> result)
>>>
>>>

 --
 James Reeves
 booleanknot.com

 --
 You received this message because you are subscribed to the Google
 Groups "Clojure" group.
 To post to this group, send email to clojure@googlegroups.com
 Note that posts from new members are moderated - please be patient with
 your first post.
 To unsubscribe from this group, send email to
 clojure+unsubscr...@googlegroups.com
 For more options, visit this group at
 http://groups.google.com/group/clojure?hl=en
 ---
 You received this message because you are subscribed to the Google
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 To unsubscribe from this group and stop receiving emails from it, send
 an email to clojure+unsubscr...@googlegroups.com.
 For more options, visit https://groups.google.com/d/optout.

>>> --
>>> You received this message because you are subscribed to the Google
>>> Groups "Clojure" group.
>>> To post to this group, send email to clojure@googlegroups.com
>>> Note that posts from new members are moderated - please be patient with
>>> your first post.
>>> To unsubscribe from this group, 

Re: what does future do after fn finish ?

[Jacek Grzebyta]

Thanks a lot. I will check it tomorrow.

J

On 1 Feb 2018 12:12 a.m., "Justin Smith"  wrote:

> this is exactly the kind of problem code I was describing - there's no
> backpressure on existing future tasks to hold up the launching of more
> futures - the work done by the agent calling conj is negligible. You need
> to control the size of the pool of threads used, and you need to impose
> back-pressure.
>
> On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta 
> wrote:
>
>> On 31 January 2018 at 18:08, James Reeves  wrote:
>>
>>> On 31 January 2018 at 17:59, Jacek Grzebyta 
>>> wrote:
>>>
 I have application with quite intense tripe store populating ~30/40 k
 records per chunk (139 portions). The data are wrapped within the future:

 (conj agent (future (apply task args)))

  and that all together is send-off into (agent []).

>>>
>>> What is "agent"? The first line of code indicates that it's a local
>>> collection shadowing the code function, while the second code snippet
>>> indicates that you're using the core agent function.
>>>
>>> Also why are you sending off to an agent?
>>>
>>
>> I have ~8sec computing task for each input dataset which generates those
>> records. After that I write it into disk (in software-specific
>> transaction). I just wanted to separate hard computing and io operations. I
>> created a side-effect method which is injected together with the dataset
>> into a future. The futures are async collected within a list wrapped in
>> agent. After the computing the main thread is waiting until all io tasks
>> will be finished.
>>
>>
>>>
>>> At the end of the main thread function I just use await-for and after
 that:

 (reduce + (map #(deref %) @data-loading-tasks))

>>>
>> As a control, tasks return number of written records.
>>
>>
>>
>>>
 For some reason I see the happy collecting (see attached screenshot of
 jconsole).

>>>
>>> "happy" = "heap"?
>>>
>>
>> Both. As you can see on attached screenshot the heap usage grows easy
>> until aver. ~2 1/4 G than keep that  for a few minutes. In that moment I
>> stopped. After that starts grow till ~4G with tendency to do jumps a bit
>> more that 4G.
>>
>>
>>>
>>>
 After seeing the source code of future I suppose that the memory (data
 are kept as #{} set) is not released. The task returns only integer so I do
 not think that might cause the problem.

>>>
>>> Can you provide more detail? You keep alluding to things that you don't
>>> provide code for, such as the sets of data.
>>>
>>
>>
>> The code is attached. However the important code is
>>
>> L123 .
>>   (let [;; keeps all data loading futures.
>> ;; waiting until all futures are finished
>> ;; should be done outside the main loop
>> data-loading-tasks (agent [])]
>>
>> L128
>> (doseq
>>  (let [r1 (long operation)]   L133
>>  (doseq
>> (let [r2 (v.v. long)]   L155
>>
>>   L163   (send-off data-loading-task conj-task)
>>
>>  )
>>  )
>> )
>> )
>>
>>
>> I guess first I will move data-loading-tasks list into one of inner lets.
>> Also I will create within an injecting function a separate abstract
>> function let inside. The task will populate tmp variable which will be
>> returned as a future result:
>>
>>
>> L114 (conj agent (future (apply (fn [] (let [result (apply task args)]
>> result)
>>
>>
>>>
>>> --
>>> James Reeves
>>> booleanknot.com
>>>
>>> --
>>> You received this message because you are subscribed to the Google
>>> Groups "Clojure" group.
>>> To post to this group, send email to clojure@googlegroups.com
>>> Note that posts from new members are moderated - please be patient with
>>> your first post.
>>> To unsubscribe from this group, send email to
>>> clojure+unsubscr...@googlegroups.com
>>> For more options, visit this group at
>>> http://groups.google.com/group/clojure?hl=en
>>> ---
>>> You received this message because you are subscribed to the Google
>>> Groups "Clojure" group.
>>> To unsubscribe from this group and stop receiving emails from it, send
>>> an email to clojure+unsubscr...@googlegroups.com.
>>> For more options, visit https://groups.google.com/d/optout.
>>>
>> --
>> You received this message because you are subscribed to the Google
>> Groups "Clojure" group.
>> To post to this group, send email to clojure@googlegroups.com
>> Note that posts from new members are moderated - please be patient with
>> your first post.
>> To unsubscribe from this group, send email to
>> clojure+unsubscr...@googlegroups.com
>> For more options, visit this group at
>> http://groups.google.com/group/clojure?hl=en
>> ---
>> You received this message because you are subscribed to the Google Groups
>> "Clojure" group.
>> To unsubscribe from this group and stop receiving emails from it, send an
>> email to clojure+unsubscr...@googlegroups.com.
>> For more 

Re: what does future do after fn finish ?

[Justin Smith]

this is exactly the kind of problem code I was describing - there's no
backpressure on existing future tasks to hold up the launching of more
futures - the work done by the agent calling conj is negligible. You need
to control the size of the pool of threads used, and you need to impose
back-pressure.

On Wed, Jan 31, 2018 at 3:46 PM Jacek Grzebyta 
wrote:

> On 31 January 2018 at 18:08, James Reeves  wrote:
>
>> On 31 January 2018 at 17:59, Jacek Grzebyta 
>> wrote:
>>
>>> I have application with quite intense tripe store populating ~30/40 k
>>> records per chunk (139 portions). The data are wrapped within the future:
>>>
>>> (conj agent (future (apply task args)))
>>>
>>>  and that all together is send-off into (agent []).
>>>
>>
>> What is "agent"? The first line of code indicates that it's a local
>> collection shadowing the code function, while the second code snippet
>> indicates that you're using the core agent function.
>>
>> Also why are you sending off to an agent?
>>
>
> I have ~8sec computing task for each input dataset which generates those
> records. After that I write it into disk (in software-specific
> transaction). I just wanted to separate hard computing and io operations. I
> created a side-effect method which is injected together with the dataset
> into a future. The futures are async collected within a list wrapped in
> agent. After the computing the main thread is waiting until all io tasks
> will be finished.
>
>
>>
>> At the end of the main thread function I just use await-for and after
>>> that:
>>>
>>> (reduce + (map #(deref %) @data-loading-tasks))
>>>
>>
> As a control, tasks return number of written records.
>
>
>
>>
>>> For some reason I see the happy collecting (see attached screenshot of
>>> jconsole).
>>>
>>
>> "happy" = "heap"?
>>
>
> Both. As you can see on attached screenshot the heap usage grows easy
> until aver. ~2 1/4 G than keep that  for a few minutes. In that moment I
> stopped. After that starts grow till ~4G with tendency to do jumps a bit
> more that 4G.
>
>
>>
>>
>>> After seeing the source code of future I suppose that the memory (data
>>> are kept as #{} set) is not released. The task returns only integer so I do
>>> not think that might cause the problem.
>>>
>>
>> Can you provide more detail? You keep alluding to things that you don't
>> provide code for, such as the sets of data.
>>
>
>
> The code is attached. However the important code is
>
> L123 .
>   (let [;; keeps all data loading futures.
> ;; waiting until all futures are finished
> ;; should be done outside the main loop
> data-loading-tasks (agent [])]
>
> L128
> (doseq
>  (let [r1 (long operation)]   L133
>  (doseq
> (let [r2 (v.v. long)]   L155
>
>   L163   (send-off data-loading-task conj-task)
>
>  )
>  )
> )
> )
>
>
> I guess first I will move data-loading-tasks list into one of inner lets.
> Also I will create within an injecting function a separate abstract
> function let inside. The task will populate tmp variable which will be
> returned as a future result:
>
>
> L114 (conj agent (future (apply (fn [] (let [result (apply task args)]
> result)
>
>
>>
>> --
>> James Reeves
>> booleanknot.com
>>
>> --
>> You received this message because you are subscribed to the Google
>> Groups "Clojure" group.
>> To post to this group, send email to clojure@googlegroups.com
>> Note that posts from new members are moderated - please be patient with
>> your first post.
>> To unsubscribe from this group, send email to
>> clojure+unsubscr...@googlegroups.com
>> For more options, visit this group at
>> http://groups.google.com/group/clojure?hl=en
>> ---
>> You received this message because you are subscribed to the Google Groups
>> "Clojure" group.
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Re: what does future do after fn finish ?

[Jacek Grzebyta]

On 31 January 2018 at 18:08, James Reeves  wrote:

> On 31 January 2018 at 17:59, Jacek Grzebyta 
> wrote:
>
>> I have application with quite intense tripe store populating ~30/40 k
>> records per chunk (139 portions). The data are wrapped within the future:
>>
>> (conj agent (future (apply task args)))
>>
>>  and that all together is send-off into (agent []).
>>
>
> What is "agent"? The first line of code indicates that it's a local
> collection shadowing the code function, while the second code snippet
> indicates that you're using the core agent function.
>
> Also why are you sending off to an agent?
>

I have ~8sec computing task for each input dataset which generates those
records. After that I write it into disk (in software-specific
transaction). I just wanted to separate hard computing and io operations. I
created a side-effect method which is injected together with the dataset
into a future. The futures are async collected within a list wrapped in
agent. After the computing the main thread is waiting until all io tasks
will be finished.


>
> At the end of the main thread function I just use await-for and after that:
>>
>> (reduce + (map #(deref %) @data-loading-tasks))
>>
>
As a control, tasks return number of written records.



>
>> For some reason I see the happy collecting (see attached screenshot of
>> jconsole).
>>
>
> "happy" = "heap"?
>

Both. As you can see on attached screenshot the heap usage grows easy until
aver. ~2 1/4 G than keep that  for a few minutes. In that moment I stopped.
After that starts grow till ~4G with tendency to do jumps a bit more that
4G.


>
>
>> After seeing the source code of future I suppose that the memory (data
>> are kept as #{} set) is not released. The task returns only integer so I do
>> not think that might cause the problem.
>>
>
> Can you provide more detail? You keep alluding to things that you don't
> provide code for, such as the sets of data.
>


The code is attached. However the important code is

L123 .
  (let [;; keeps all data loading futures.
;; waiting until all futures are finished
;; should be done outside the main loop
data-loading-tasks (agent [])]

L128
(doseq
 (let [r1 (long operation)]   L133
 (doseq
(let [r2 (v.v. long)]   L155

  L163   (send-off data-loading-task conj-task)

 )
 )
)
)


I guess first I will move data-loading-tasks list into one of inner lets.
Also I will create within an injecting function a separate abstract
function let inside. The task will populate tmp variable which will be
returned as a future result:


L114 (conj agent (future (apply (fn [] (let [result (apply task args)]
result)


>
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> booleanknot.com
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experiment_result.clj
Description: Binary data

Re: what does future do after fn finish ?

[Justin Smith]

As a shot in the dark, a common problem with memory usage and futures that
I have seen is the antipattern of launching a future for each piece of data
in a collection. The problem that occurs is that the code works for small
input collections and a small load of running tasks / requests, but for a
larger input and more requests it uses up the heap easily. Then, a dev
assumes that somehow the future itself is leaking or otherwise taking up
space it shouldn't, when the true problem is that the undbounded creation
of futures happens to exhaust your available memory space. If you aren't
doing such a thing feel free to disregard.

On Wed, Jan 31, 2018 at 10:09 AM James Reeves  wrote:

> On 31 January 2018 at 17:59, Jacek Grzebyta 
> wrote:
>
>> I have application with quite intense tripe store populating ~30/40 k
>> records per chunk (139 portions). The data are wrapped within the future:
>>
>> (conj agent (future (apply task args)))
>>
>>  and that all together is send-off into (agent []).
>>
>
> What is "agent"? The first line of code indicates that it's a local
> collection shadowing the code function, while the second code snippet
> indicates that you're using the core agent function.
>
> Also why are you sending off to an agent?
>
> At the end of the main thread function I just use await-for and after that:
>>
>> (reduce + (map #(deref %) @data-loading-tasks))
>>
>> For some reason I see the happy collecting (see attached screenshot of
>> jconsole).
>>
>
> "happy" = "heap"?
>
>
>> After seeing the source code of future I suppose that the memory (data
>> are kept as #{} set) is not released. The task returns only integer so I do
>> not think that might cause the problem.
>>
>
> Can you provide more detail? You keep alluding to things that you don't
> provide code for, such as the sets of data.
>
> --
> James Reeves
> booleanknot.com
>
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Re: what does future do after fn finish ?

[James Reeves]

On 31 January 2018 at 17:59, Jacek Grzebyta  wrote:

> I have application with quite intense tripe store populating ~30/40 k
> records per chunk (139 portions). The data are wrapped within the future:
>
> (conj agent (future (apply task args)))
>
>  and that all together is send-off into (agent []).
>

What is "agent"? The first line of code indicates that it's a local
collection shadowing the code function, while the second code snippet
indicates that you're using the core agent function.

Also why are you sending off to an agent?

At the end of the main thread function I just use await-for and after that:
>
> (reduce + (map #(deref %) @data-loading-tasks))
>
> For some reason I see the happy collecting (see attached screenshot of
> jconsole).
>

"happy" = "heap"?


> After seeing the source code of future I suppose that the memory (data are
> kept as #{} set) is not released. The task returns only integer so I do not
> think that might cause the problem.
>

Can you provide more detail? You keep alluding to things that you don't
provide code for, such as the sets of data.

-- 
James Reeves
booleanknot.com

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