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# Treasure Data Summer Internship Final Report

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Treasure Data Summer Internship Final Report

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### Treasure Data Summer Internship Final Report

1. 1. INTERNSHIP FINAL REPORT
2. 2. Who are you? Ritta Narita (github:@naritta) The University of Tokyo, Engineering M2 Researched about Physic simulation I’ve worked in some companies. 2
3. 3. Projects for Intern hivemall: Original VM for Random Forests ! ﬂuentd: Socket Manager with ServerEngine 3
4. 4. hivemall: Original VM for Random Forests 4
5. 5. What’s Random Forest ? make many decision trees, accept a majority decision decision tree(play golf or not) to know the result of decision tree, need calculation for bound features. humidity > 30 %? whether = sunny wind speed > 10 m/s ? play golf don’t play don’t play don’t play yes yes yes 5
6. 6. generate JS code →execute using eval ! At present, to calculate decision tree if (x[0]==0){ if (x[1]>30){ return 1;} ・・・ } else { return 1; } x = [weather, humidity, wind] 0=play golf, 1=don’t play humidity > 30 %? whether = sunny wind speed > 10 m/s ? play golf don’t play don’t play don’t play yes yes yes 6
7. 7. ! ! due to using eval, can execute any code ! For example hostile JS code like inﬁnite loop →burden for TD ! It’s difﬁcult to restrict JS code →need restricted environment to calculate decision tree ! Problem for JS 7
8. 8. Then generate original op code from tree model →execute on originalVM PUT x[1] PUT 0 IFEQ 10 ! ・ ・ ・ x = [weather, humidity, wind] 0=play golf, 1=don’t play if (x[0]==0){ if (x[1]>30){ return 1;} ・・・ } else { return 1; } 8
9. 9. What’s the merit? ・can ﬁnd illegal code like inﬁnite loop easily ・only for comparator, so very restricted ・less op code, very fast 9
10. 10. My work op code featured for comparator  only PUSH, POP, GOTO, IF~ ! can ﬁnd inﬁnite loop In this code, supposed not to have loop →don’t execute same code 10
11. 11. hadoop version 2.6, Hive 1.2.0 (Tez 0.6.1) ! hadoop cluster size: c3.2xlarge 8 nodes ! ! randomforest !  number of test examples in test_rf: 18083 !  number of trees: 500 ! ! ! compile num: 500 ! eval num: 500 * 18083 ! Javascript : 1062.04 s (Nashorn) ! VM: 106.84 s   comparison with JS 10 times faster 11
12. 12. Why don’t you use Java bytecode and ASM ? 12
13. 13. Because of the number of class loading for example, if every clients make 500 models… ↓ too many class loading If using one class and 500 method, It is same. 13
14. 14. summary ・very restricted, can ﬁnd illegal code ! ・10 times faster ! ・future prospects: can make it even faster by binary code ! ・merged in development branch and will be released in v0.4 14
15. 15. ﬂuentd: Socket Manager with ServerEngine 15
16. 16. In ﬂuentd v0.14 produce ! New multiprocess model 16
17. 17. multiprocess at present use in_multiprocess plugin have to use multi sockets and assign each ports by user super visor worker worker worker port: 24224 port: 24226 port: 24225 17
18. 18. multiprocess v0.14 super visor worker worker worker port: 24224 using Socket Manager, share one listening socket →can use multicore without any assignment port: 24224 port: 24224 port: 24224 Socket Manager server Socket Manager client Socket Manager client Socket Manager client 18
19. 19. in Windows 20
20. 20. can use multicore power fully without unconsciousness setting ﬁle will get very simple 21 with SocketManagerwith in_multiprocess plugin <source> type multiprocess <process> cmdline -c /etc/td-agent/td-agent-child1.conf </process> <process> cmdline -c /etc/td-agent/td-agent-child2.conf </process> </source> ! #/etc/td-agent/td-agent-child1.conf <source> type forward port 24224 </source> ! #/etc/td-agent/td-agent-child2.conf <source> type forward port 24225 </source> <source> type forward port 24224 </source> setting when using 2 core
21. 21. To implement Socket Manager, I used ServerEngine worker worker worker super visor Server Engine live restart Heartbeat via pipe auto restart 22 ServerEngine is: a framework to implement robust multiprocess servers like Unicorn.
22. 22. Implementation (Unix) ②Unix Domain Socket (send_io ﬁle descriptor) worker worker worker Socket Manager client Socket Manager client Socket Manager client FD Spawn Socket Manager server super visor Server Engine ①DRb (request listening socket) 24
23. 23. Unix: very simple Windows: a little complex main difference 1. can’t share socket by FD   in Windows, socket descriptor ≠ ﬁle descriptor   It doesn’t make sense to share FD   (have to use Winsock2 API to share sockets) ! 2. have to lock accept in unix, don’t need consider thundering herd  but do in windows.   25
24. 24. Implementation (Windows) DRb create socket from port and bind (WSASocket) ↓ duplicate exclusive socket by pid (WSADuplicateSocket) ↓ get socket protocol (WSAProcolInfo) worker worker worker Socket Manager server Socket Manager client Socket Manager client Socket Manager client from WSAProcolInfo, make WSASocket ↓ handle into FD ↓ IO.for_fd(FD) send this IO to Cool.io super visor Server Engine 26
25. 25. accept mutex worker worker get mutex detach release mutex attach listening socket to cool.io loop accept mutex read and send data to buffer/output server socket get mutex detach release mutex attach listening socket to cool.io loop accept read and send data to buffer/output deal with post processing in this process as it is other process can listen while this process is dealing with data 27
26. 26. rotation in order by accept mutex  ①2376→②3456→③2696→④3388 →①2376→②3456→ 28
27. 27. As a result of test, Thundering herd doesn’t occur in windows. Tentatively I implemented roughly with mutex, but I want to use IOCP like livuv in the future. ! Patches are welcome from Windows specialist! 29
28. 28. benchmark result (unix) AWS ubuntu 14.04 m4.xlarge RPS IO conventional model 6798.69 /sec 1361.07 kb/s new model (4 workers) 13743.02 /sec 2751.29 kb/s in_http → out_forward 30
29. 29. benchmark result (windows) AWS Microsoft Windows Server 2012 R2 m4.xlarge RPS IO conventional model 1834.01 /sec 385.07 kb/s new model (4 workers) 3513.31 /sec 737.66 kb/s in_http → out_forward 31
30. 30. Future work ・Buffering in multiprocess ・accept mutex based IOCP…etc summary ・Implemented ﬂuentd Socket Manager with ServerEngine, and will be faster without consciousness. ! ・There is details in ServerEngine Issue,  you can test my forked branch(ﬂuentd and ServerEngine)  and I’ll send PR after this report. 32
31. 31. That’s all,Thank you! 33
32. 32. appendix
33. 33. Why don’t you use Object serialization? 35
34. 34. Because of memory problem When Random forests model is big and many customers use it, It is too much memory consumption 36
35. 35. ServerEngine is: To implement Socket Manager, I used ServerEngine a framework to implement robust multiprocess servers like Unicorn. 37
36. 36. how to use Socket Manager in ﬂuentd side ! #get socket manager socket_manager = ServerEngine::SocketManager.new_socket_manager ! #get FD from socket manager fd = socket_manager.get_tcp(bind, port) ! #create listening socket from FD lsock = TCPServer.for_fd(fd.to_i) it doesn’t need consider about socket sharing in ﬂuentd side, ServerEngine deal with it inside. 38
37. 37. Benchmark Result I’ll add multiprocess buffering function, After that I’ll do benchmark formally. ! Tentatively Show the rough result 40