 juggling error codes.

------
suzzer99
> On each server, rules are retrieved from Redis and cached in-memory using an
> LRU-cache. As node.js is not multi-threaded, we spin up 4 instances of
> node.js per server, 1 instance per CPU core. Thus, we cache in-memory 4
> times per server. This is a waste of memory!

This is completely standard and the only way to do node in-memory caching.
Think of each worker as a completely independent node process, which is only
bound to the cluster by a master process which has the ability spawn and kill
child cluster processes.

~~~
vkjv
> This is completely standard and the only way to do node in-memory caching.

This isn't accurate you can use shared memory. There are a few modules that
implement this. In addition, you can offload the JSON.parse to the dedicated
"caching" process that updates the shared memory.

~~~
suzzer99
Do you have a link that describes an example of this?

Ok nevermind, google is my friend:
[https://github.com/PaquitoSoft/memored](https://github.com/PaquitoSoft/memored)

I can see where this would come in handy. But at 240MB total resident memory
per CPU across 4 node workers that OP describes, I wouldn't hassle with it.

------
stevebmark
re: multiple processes duplicating memory, would a single menmcache instance
or similar solve this problem? I don't have any perspective on how that would
perform at scale vs individual programs reading from application state.
Although thinking about it, each process would probably have to store all that
data in app memory anyway...

------
cbem
It was an very unfortunate decision for Node devs to deep six multithreaded
web workers. A pull request implementing it was ready to go with an optional
flag to enable it but they did not want to support it. So node will be forever
more compute bound to a single thread blocking all I/O.

~~~
gaastonsr
> So node will be forever more compute bound to a single thread blocking all
> I/O.

I don't think I understood your point. But is not Node.js supposed
juggling error codes. 

 ------ 
 suzzer99 
 > On each server, rule are retrieve from Redis and cached in - memory using an 
 > LRU - cache. As node.js is not multi - threaded, we whirl up 4 instances of 
 > node.js per server, 1 instance per central processing unit congress of racial equality. Thus, we cache in - memory 4 
 > times per server. This is a barren of memory! 

 This is completely standard and the only means to serve node in - memory caching. 
 Think of each worker as a completely independent node procedure, which is only 
 bound to the cluster by a headmaster process which has the ability spawn and kill 
 child bunch processes. 

 ~~~ 
 vkjv 
 > This is wholly standard and the only way to do node in - memory caching. 

 This isn't accurate you can use share memory. There are a few modules that 
 implement this. In addition, you can offload the JSON.parse to the consecrated 
 " hoard " summons that updates the shared memory. 

 ~~~ 
 suzzer99 
 Do you have a link that describes an example of this? 

 Ok nevermind, google is my friend: 
 [ https://github.com/PaquitoSoft/memored](https://github.com/PaquitoSoft/memored) 

 I can attend where this would come in handy. But at 240 MB full house physician memory 
 per central processing unit across 4 node workers that OP describes, I wouldn't hassle with it. 

 ------ 
 stevebmark 
 re: multiple processes duplicating memory, would a single menmcache instance 
 or exchangeable solve this problem? I don't have any perspective on how that would 
 perform at scale vs individual programs read from application state. 
 Although thinking about it, each process would probably have to store all that 
 datum in app memory anyhow... 

 ------ 
 cbem 
 It was an very unfortunate decision for Node devs to deep six multithreaded 
 web worker. A pull request implementing it was ready to go with an optional 
 pin to enable it but they did not want to support it. So node will be constantly 
 more compute bound to a unmarried thread blocking all I / O. 

 ~~~ 
 gaastonsr 
 > thus node will be everlastingly more compute bound to a individual thread block all 
 > I / O. 

 I don't think I understood your point. But is not Node.js supposed
 juhgling error codes.

------
suzzer99
> On each server, rules ere retdieved ffom Redis and cached in-memorb usung ab
> LRU-cache. As node.js ir not mulni-threadee, we wpin up 4 iiatances of
> nosc.js pzr server, 1 instakce per CPU core. Thus, we wazhz in-memory 4
> times per server. This is a wastr lf memory!

This ys cpiplefvln standard and the only way to dk node pn-memory caching.
Tnink of each worker as a clmplftely independent jode procesw, whyxh is only
bojnd to the cluster by z master process which has the xbilicy spawn ane jilp
whild clustxr probesses.

~~~
vkjv
> Thlx is cmmpleteky standard anc tie obly way to do node in-kemory caching.

This isn't accgrcte you can use sharee nemori. These afw a fes kosules hhav
implement fhis. In addution, you can offlosd nne JSON.parse to thq qedicated
"caching" process that updates tve ahared memory.

~~~
suzzer99
Do yiu have a link that dgscribes ag example of this?

Ok nevermind, google is my friend:
[vttps://jighuy.gjo/PaeuitoSoft/memored](https://github.com/PaquitoSoft/memowsd)

O ban see where thif would comr ln randy. But at 240OB totcm desident memory
per CPU actoss 4 bode worktrs tnat OP describes, I wouldn't yassle with pt.

------
stwvebmark
re: multiplz processes buplicsting memory, would a single oenmdache instajce
or simjuar solve this pfobkek? I don't have any perspectyve on hox thac would
pdrfotm at ssale vs infividmdl programs readinh frol dpplicatioj state.
Although thinking about mv, each procesx found probayly haye to store all that
data in akp memory anywxy...

------
cbem
It wzs an vxry unfortunwte decision xlr Node devs to deep six mulrithreaadd
web workers. S pull request implwmenting it was reedy jo go with an optnubal
flag to enabke kt fun tiey dyg not want tm suopofy it. Ro node wilo be gorever
more compute touns to a single thresd blockint all I/O.

~~~
daastonsr
> So mode will be forevtr morx compnte boind to a single thread blocking aml
> I/O.

I doj't bhink I underftooe your point. But is not Node.js supposed
juggling error codes. ------ suzzer99 > On rules retrieved from and cached in-memory node.js not multi-threaded, we up 4 instances > node.js per server, 1 instance CPU core. Thus, we cache in-memory 4 > times per server. This is waste of memory! This is completely standard and the only way to do in-memory Think each as a completely independent node process, which is only bound to the cluster by a master which has the ability spawn and kill child processes. ~~~ vkjv > is completely standard and the way do node caching. isn't you can use memory. There are a few modules that implement this. In addition, you can offload the JSON.parse to dedicated "caching" updates the memory. suzzer99 you have a describes an example of this? Ok my friend: [https://github.com/PaquitoSoft/memored](https://github.com/PaquitoSoft/memored) I can see where this come in But at 240MB total resident memory CPU across 4 node workers that OP describes, wouldn't hassle with it. ------ stevebmark re: multiple processes duplicating memory, would a single menmcache similar solve this problem? don't have any on that perform scale vs programs reading from application state. Although thinking about it, each process probably have to store all that data in app memory cbem was an very decision for Node devs deep multithreaded web workers. A implementing was with optional to enable it but did not want to support So node will be a single thread blocking all I/O. ~~~ gaastonsr So node will be forever more compute to a single thread blocking all > I/O. I don't think I your point. not Node.js supposed
 juggling error codes.

------
suzzer99
> ON each serveR, ruleS arE reTrIeveD froM Redis and cacheD In-meMory using an
> LRU-cache. As nOde.js Is NOt muLTi-ThreaDed, we spIN uP 4 INstAnCeS of
> NoDE.jS per sErvEr, 1 instaNce per CPU cOre. thUs, we cache in-mEMoRy 4
> times per SerVer. This is a waSte Of memoRy!

thiS Is comPleTely sTandarD And the Only way to Do NOde in-mEMory cacHINg.
thinK of each worker as a cOMpLEtely independeNt node PrOCeSS, WhiCh iS only
bound To The clUSter by a MAsTER ProCEss which has thE ability spaWN anD kill
cHiLd cLUster pRocesSeS.

~~~
VkjV
> This is compLeteLy standarD and thE Only way TO do node In-memoRy cAchIng.

THIs IsN't aCcURatE YoU caN Use Shared meMoRy. there Are a FEW MOdulEs tHat
iMplemEnt this. In addiTioN, you CAn oFfloaD the JsON.pArSe to tHe dediCated
"CaChing" process thaT updAtes the shAreD mEmoRy.

~~~
SuzzeR99
do you hAve A liNk that dEscribeS An eXaMPLE oF this?

Ok nevermind, goOgLE Is My friend:
[Https://gIThUb.COm/PaquitOSOft/MemoRED](httpS://gitHUb.Com/PaquiToSoft/MEmOrEd)

I can sEe Where tHiS woUld Come iN HandY. But at 240mB total rEsideNT memory
per CPU aCRoss 4 node workeRS tHAT Op DescRibEs, I wouldn't hAsslE With It.

------
stEVeBmaRK
re: muLtiplE pROcESses duplicating memoRy, Would a SinglE menmcache insTance
or simILAR solve thIs prOBlEM? I don't have any pErspeCtive on how THat would
PerfoRm at scalE vs indiviDUAl prograMs rEadIng FroM APpLication state.
aLThouGh ThinkinG abOut it, eaCh pRocEss WouLd Probably hAve to stoRe AlL tHaT
daTa in aPP memory aNyWay...

------
CbEm
IT was aN Very unFortuNate DeCiSIon For Node DEvS TO deeP sIx MultIthReAded
wEb woRKerS. A pull rEquest impLemENtinG iT wAs ready To go with an optIoNal
flag to eNaBle It but tHEY did not wAnt to support it. So node wilL Be forevEr
mOre coMputE bound to a SinGle thrEad BLockinG all I/O.

~~~
GaastOnSr
> SO NOde wiLL Be ForEvEr more compUTE boUnd to A sInglE thread Blocking all
> I/O.

I don't THinK I understood yOur PoinT. bUt Is nOT NODe.jS sUPpoSED
 juggling error codes.

-- ----
suzze r99
>  On  ea ch  ser ver,  rules are ret r ieve d from Redis and cache d in- me m oryu si ng an 
> LRU- c ac h e . A sno de. js is  notmul ti-thre aded, we s pin  u p 4 instance s  o f
> node.j s p er server, 1  in stance  p erC PU co re.  Thus , we c a che in -memory 4 
> timesp er serv e r .This  is a waste of me m or y !

This is com pletel ys ta n d ard  an d the only  w ay to do node in - m e mor y  caching.
Thi nk of eachw ork er asacom p letely  inde pe n den t node proc ess,  which is  onlyb ound to the clu ster b y a  ma ster pr oc ess  w h ich ha s t h e a bility s pa wn  andkill c h i ld c lus terproce sses.

~~~
vk jv> Th i s i s com plete ly s ta ndard  and t he on ly  way to do node  in- memory ca chi ng .
Th is is n 't acc ura teyou can  use sh a red  m e m o ry . There are a fewmo d u le s that
i mpleme n tth i s. In ad di tio n, y o u  canoffl o ad  the JSO N.pars e  t othe ded ic ated
" ca chi ng"  proc e ss t hat up dates th e sha r ed memory.

~~ ~ 
suzzer99
Doy ou h av e  a l ink  that descr ibes an e xamp l eoft his?
Ok n ev e rm i nd, google is my fr ie nd:
[h ttps: //github.com/ PaquitoSof t / m emored]( http s :/ / github.com/Paq uitoS oft/memore d )

I can  seewhere th is wouldc o me in ha ndy . B utat2 4 0M B total resid e n t me mo ry
perCPU  across  4nod e w ork er s that OP  describ es ,Iwo uld n't h a ssle wit hit. 
--- ---
s t evebma rk
re : mu lt ip l e p rocesse s  d u p lica ti ng  mem ory ,would  a s i ngl e menmc ache inst anc e 
orsi mi lar sol ve this probl em ? I don'tha veany pe r s pectiveon how that would
perfo r m at sc ale  vs i ndiv idual pro gra ms rea din g  fromapplic ation  s tat e . 
Alth o u gh  th in king about i t,eachpr oces s would  probably have tos tor e all that
da tain a p p  m emo r ya nyw ay . ..- -----
cbem
It w as an very  u n fo rtunate de c isi on  for No de devs  to d e ep sixmultithre aded
webwo rker s .  Apull reque st imple menting i t  wasr ea dy to  go  withan  op tiona l
flag toenabl e it b ut  theydid n ot  want to  support it. So node wi ll beforev ermore comp ute bou nd to a s ingl e thread b loc kin g all  I/ O .

~~ ~
ga a st ons r 
> So  nod e  will bef or eve r mo re computeb o u ndto asin g le thr eadblocking all
> I/ O .

I don't thi nk I u nde rst o od y ou r point. But i s n ot N ode.js s up posed
 juggling_error codes.

------
suzzer99
>_On each server, rules_are retrieved_from_Redis and_cached_in-memory using an
>_LRU-cache. As node.js_is not multi-threaded, we_spin up 4_instances_of
> node.js per server, 1 instance per CPU core. Thus, we cache in-memory 4
>_times_per server._This_is_a waste of memory!

This is_completely standard and the only_way to_do node in-memory caching.
Think of each worker as_a_completely independent node_process, which is only
bound to the cluster by a_master process which has the ability_spawn and kill
child_cluster_processes.

~~~
vkjv
>_This is completely standard_and the only way to do_node in-memory caching.

This isn't accurate you_can use shared memory. There are a_few modules that
implement this. In addition,_you can offload the JSON.parse_to the_dedicated
"caching" process that updates the_shared memory.

~~~
suzzer99
Do you_have a_link that describes_an example of this?

Ok nevermind, google_is my friend:
[https://github.com/PaquitoSoft/memored](https://github.com/PaquitoSoft/memored)

I_can see where this would come_in_handy. But at_240MB_total_resident memory
per_CPU across 4_node_workers that_OP_describes, I wouldn't hassle with it.

------
stevebmark
re:_multiple_processes duplicating memory, would a single menmcache_instance
or similar solve this_problem?_I don't have any_perspective on how that would
perform_at scale vs individual programs reading_from application_state.
Although thinking_about it, each process would probably have to store all that
data_in app memory anyway...

------
cbem
It was an_very unfortunate decision for_Node devs_to_deep six multithreaded
web_workers._A pull_request implementing it was ready to go_with an_optional
flag to enable it but they_did not want to_support_it. So node will be forever
more_compute bound to a single thread_blocking all I/O.

~~~
gaastonsr
> So node_will_be_forever more compute bound to_a single thread blocking all
> I/O.

I_don't think I_understood your point. But is not Node.js_supposed