How to read Flamegraph for reply.send fastify perf issue
matt212 opened this issue · comments
Hi All,
below is my graph generated from autocannon and 0x
rather than issue my concern is how to find find bottleneck and optimized the code
the problem here is the reply.send is fastify function and it is pointing to that line so how can one optimize in that situation.
any help or pointer would suffice
There is a lot of inlining happening in your application. One of the things reply.send() does is calling the JSON serializers...
You can visualize all of those by passing --interpreted-frames-native-stack to Node.js
Hi @mcollina ,
Sure on it and would provide an update on same
thanks again also
how one can call JSON serializer kinda new to fastify that's all
how one can call JSON serializer kinda new to fastify that's all
I don't understand... reply.send({ hello: 'world' }) would render that as JSON.
HI @mcollina
this is my reply.send json content
reply.send({
"rows": [
{
"employeesid": 20667907,
"first_name": "Xinglin",
"last_name": "Morrin",
"gender": "F",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667906,
"first_name": "Xinglin",
"last_name": "Morrin",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667905,
"first_name": "Ortrud",
"last_name": "Binding",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667904,
"first_name": "Gennady",
"last_name": "Thiran",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667903,
"first_name": "Goh",
"last_name": "Demke",
"gender": "F",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667902,
"first_name": "Taegyun",
"last_name": "Zschoche",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667901,
"first_name": "Sugwoo",
"last_name": "Muniz",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667900,
"first_name": "Haldun",
"last_name": "Peek",
"gender": "F",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667899,
"first_name": "Tsz",
"last_name": "England",
"gender": "F",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667898,
"first_name": "Gererd",
"last_name": "Plesums",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667897,
"first_name": "Prasadram",
"last_name": "Dusink",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667896,
"first_name": "Basem",
"last_name": "Ashish",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667895,
"first_name": "Lenore",
"last_name": "Schieder",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667894,
"first_name": "Francesca",
"last_name": "Covnot",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667893,
"first_name": "Aiman",
"last_name": "Vecchi",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667892,
"first_name": "Mechthild",
"last_name": "Luft",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667891,
"first_name": "Goh",
"last_name": "Ermel",
"gender": "F",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667890,
"first_name": "Dzung",
"last_name": "Candan",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667889,
"first_name": "Mabry",
"last_name": "Berstel",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
},
{
"employeesid": 20667888,
"first_name": "Sanjiv",
"last_name": "Frezza",
"gender": "M",
"birth_date": "2018-01-11T18:30:00.000Z",
"recordstate": true,
"created_date": "2019-02-28T16:38:09.849Z",
"updated_date": "2019-02-28T16:38:09.849Z"
}
],
"count": "2088338"
})
Hi @mcollina
I tried to run 0x with --interpreted-frames-native-stack but I am getting below error
is not a recognized flag
`yarn run v1.22.5
$ cd ./app/utils && 0x --interpreted-frames-native-stack app2.js
Error:
� --interpreted-frames-native-stack is not a recognized flag`
Since I am using 0x to generate the heat graph
could you please suggest how should use --interpreted-frames-native-stack in 0x run
Hi @mcollina
got it
using below snippet
0x -- node --interpreted-frames-native-stack --perf-basic-prof-only-functions app2.js
Hi @mcollina
I tried running with flag mentioned and please find below zip file for end result
31042.0x.zip
In essence, the view is the same . it would great if you have look at it and suggest pointers on the same
If you click on "native", you'd see that the hottest function is within Node.js core, called from .send(). There is likely some inlined function, try running it with --no-turbo-inlining
Hi @mcollina
thanks for looking into it and sure would run using --no-turbo-inlining and provide an update accordingly
Hi @mcollina
sorry for delayed response ,
could you please find below performgraph with --no-turbo-inlining
21290.0x.zip
As you can see, all the time is spent in node.js core writing down your output to the sockets. There is nothing to optimize here.
Hi @mcollina
Thanks for the confirmation and also if you have some time could you please have look at below
https://github.com/matt212/Nodejs_Postgresql_VanillaJS_Fastify
and provide some feedback
thanks again!