YAPC::Asia Hachioji 2016 mid in Shinagawa 2016-07-03 Yusuke Wada a.k.a. yusukebe
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YAPC::Asia Hachioji 2016 mid in Shinagawa 2016-07-03 Yusuke Wada a.k.a. yusukebe
cachectldã§OSã®ãƒšãƒ¼ã‚¸ã‚ャッシュ削除を自動化 - Qiita
サーãƒã‚’é‹ç”¨ã—ã¦ã„ã‚‹ã¨æ™‚々全然メモリãŒä½™ã£ã¦ã„ã‚‹ã¯ãšãªã®ã«ã‚¹ãƒ¯ãƒƒãƒ—ãŒèµ·ãã¦ã—ã¾ã†ã“ã¨ãŒã‚ã‚Šã¾ã™ã€‚ã“ã®å ´åˆã‚ˆãã‚るケースã¯éžå¸¸ã«å¤§ããªãƒã‚°ãƒ•ã‚¡ã‚¤ãƒ«ãŒã‚ã£ã¦ãã®ãƒã‚°ãƒ•ã‚¡ã‚¤ãƒ«ã®ãŸã‚ã«å¤§é‡ã®ãƒšãƒ¼ã‚¸ã‚ャッシュãŒåˆ©ç”¨ã•ã‚Œã¦ã„ã‚‹ã“ã¨ã§ã™ã€‚ ãƒã‚°ãƒ•ã‚¡ã‚¤ãƒ«ãªã‚“ã¦æ»…多ã«èªã¾ãªã„ã®ã§ã€ãã‚“ãªã®ã«ãƒ¡ãƒ¢ãƒªä½¿ã†ãらã„ã ã£ãŸã‚‰ã‚‚ã£ã¨åˆ¥ã®ã‚¢ãƒ—リケーションã«ã¡ã‚ƒã‚“ã¨å‰²ã‚Šå½“ã¦ã¦ãれよã¨æ€ã†ã®ã§ã™ãŒã€ãªã‹ãªã‹ã†ã¾ãã„ã‹ãªã„ã‚‚ã®ã§ã™ã€‚ ãã“ã§åŠ¹æžœçš„ãªã®ãŒposix_fadivseをラップã—ã¦æŒ‡å®šã—ãŸãƒ•ã‚¡ã‚¤ãƒ«ã®ãƒšãƒ¼ã‚¸ã‚ャッシュを解放ã™ã‚‹ãƒ„ールã§ã™ã€‚ ページã‚ャッシュãŒã©ã‚“ã©ã‚“増ãˆã¦ã„る…ãã‚“ãªæ™‚ã«å½¹ç«‹ã¤ãƒ¯ãƒ³ãƒ©ã‚¤ãƒŠãƒ¼ ファイル指定ã§ã€ãƒšãƒ¼ã‚¸ã‚ャッシュã«ã®ã£ã¦ã„ã‚‹ã‹ç¢ºèªã—ãŸã‚Šè¿½ã„出ã—ãŸã‚Š ç§ã®å ´åˆã€ä»Šã¾ã§ã¯nocacheã¨ã„ã†ãƒ„ールをã¡ã‚‡ã“ã£ã¨æ”¹é€ ã—ã¦ä½¿ã£ã¦ã„ã¾ã—ãŸãŒã€æœ€è¿‘ã‚‚ã†ã¡ã‚‡ã£ã¨ä¾¿åˆ©ãªé¢¨ã«æ”¹é€ ã—ãŸã„ã¨æ€ã†ã‚ˆã†ã«ãªã£ã¦ãã¾ã—ãŸã€‚例
Chrome's 10 Caches
While defining the set of page load time metrics that we think are most important for benchmarking, Mike Belshe, James Simonsen and I went through a seemingly simple exercise: enumerate the ways in which Chrome caches data. The resulting list was interesting enough to me that I thought it worthwhile to share. When most people think of "the browser's cache" they envision a single map of HTTP reques
Transactions, Caching and AOP: understanding proxy usage in Spring | SpringSource Team Blog
In the Spring framework, many technical features rely on proxy usage. We are going to go in depth on this topic using three examples: Transactions, Caching and Java Configuration. All the code samples shown in this blog entry are available on my github account. First step: no transaction The Service class below is not transactional yet. Let’s first look at it as is and then make it become transact
How to use the cachegrind output to optimize the application
I need to improve the throughput of the system. The usual cycle of optimization has been done and we have already achieved 1.5X better throughput. I am now beginning to wonder if I can utilize the cachegrind output to improve the system's throughput. Can somebody point me to how to begin on this? What I understand is we need to ensure most frequently used data should be kept small enough so that i
Valgrind
To use this tool, specify --tool=cachegrind on the Valgrind command line. Cachegrind is a high-precision tracing profiler. It runs slowly, but collects precise and reproducible profiling data. It can merge and diff data from different runs. To expand on these characteristics: Precise. Cachegrind measures the exact number of instructions executed by your program, not an approximation. Furthermore,
GitHub - fujieda/pcache: Periodic file caching for Apache httpd
pcache.pl -- Periodic file caching for Apache httpd Copyright (c) JAIST FTP Admins <ftp-admin@jaist.ac.jp> = Overview This script realizes file caching for the Apache httpd. It is aimed at servers delivering large files. It collects requests, priodically choose files to be cached, and asynchronously caches them in SSD. It does not cause client's wait for caching files differently from mod_disk_cac
What Every Programmer Should Know About Memory (PDF)
What Every Programmer Should Know About Memory Ulrich Drepper Red Hat, Inc. [email protected] November 21, 2007 Abstract As CPU cores become both faster and more numerous, the limiting factor for most programs is now, and will be for some time, memory access. Hardware designers have come up with ever more sophisticated memory handling and acceleration techniques–such as CPU caches–but these canno
ncache
1. NCACHE The fast web cache server base on nginx Use aio sendfile and epoll modules The self sort share mem hash index High performance and large storage Low cpu cost and low iowait Record lock instead of process lock Without http headers cache 3. STRUCTURE Be proxy hash index Init by Ngx master process when nginx is start on Ngx worker process Ngx worker process Disk Files Read / write by file s
squidã§å¤šæ®µãƒªãƒãƒ¼ã‚¹ãƒ—ãƒã‚シー - å¾è¼©ã®ãƒ¡ãƒ¢ã§ã‚ã‚‹
ã„ã‚ゆるproxyã¯ã‚„ã£ãŸã“ã¨ãŒã‚ã‚‹ã‚“ã§ã™ãŒã€reverseã¯Apacheã¨ã‹Poundã¿ãŸã„ãªãŠæ‰‹è»½ãªã‚„ã¤ã§ã—ã‹ã‚„ã£ãŸã“ã¨ãªã‹ã£ãŸã®ã§ã€squidã§reverse proxy(ã‚ャッシュサーãƒ)ã§ã™ã€‚ 構æˆã¯ proxy (carp1, carp2ã«ãƒªã‚¯ã‚¨ã‚¹ãƒˆã‚’é€ã‚‹ãƒãƒ©ãƒ³ã‚µãƒ¼ç”¨ãƒ›ã‚¹ãƒˆ) carp1 (ファイルをã‚ャッシュã™ã‚‹ãƒ›ã‚¹ãƒˆãã®1) carp2 (ファイルをã‚ャッシュã™ã‚‹ãƒ›ã‚¹ãƒˆãã®2) origin (ファイルをストアã—ã¦ã„るホスト) ã¨ãªã£ã¦ãŠã‚Šã¾ã™ã€‚ ホストåアドレス proxy192.168.0.200 carp1192.168.0.201 carp2192.168.0.202 origin192.168.0.203 proxyã¯ã‚ャッシュをã•ã›ãšã«carp1, carp2ã«ãƒªã‚¯ã‚¨ã‚¹ãƒˆã‚’ãµã‚Šã¾ã™ã€‚squidã§ã¯CARP(Cache Array Routing Protocol
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DBIx::Class::Cursor::Cached
NAME DBIx::Class::Cursor::Cached - cursor class with built-in caching support SYNOPSIS my $schema = SchemaClass->connect( $dsn, $user, $pass, { cursor_class => 'DBIx::Class::Cursor::Cached' } ); $schema->default_resultset_attributes({ cache_object => Cache::FileCache->new({ namespace => 'SchemaClass' }), }); my $rs = $schema->resultset('CD')->search(undef, { cache_for => 300 }); my @cds = $rs->all
ã¯ã¦ãªãƒ–ãƒã‚° | 無料ブãƒã‚°ã‚’作æˆã—よã†
2024å¤ä¼‘ã¿æ—…行　神戸・2日目ã€å‰ç·¨ã€‘ zfinchyan.hatenablog.com ↑１日目ã¯ã“ã¡ã‚‰ 6:50 ã‚ãŸã—ã¨å¤«ã ã‘å…ˆã«èµ·åºŠ å‰æ—¥ã«è²·ã£ã¦ãŠã„ãŸãŠèŠ‹ã®ãƒ‘ンã§æœã”ã¯ã‚“ 昨日ã®ç–²ã‚Œã‹ã‚‰ã‹ã€ãªã‹ãªã‹æ¯åãŸã¡ãŒèµ·ãã¦ã“ãªã‹ã£ãŸã®ã§ã€ã‚†ã£ãã‚Šå¯ã‹ã›ã¦ã‹ã‚‰10:00ã«ãƒ›ãƒ†ãƒ«ã®ä¸‹ã«ã‚るプレイゾーンã«è¡Œã£ã¦ã€ãƒ‘ターゴルフやãƒã‚¹â€¦
HTTP/1.1: Caching in HTTP
part of Hypertext Transfer Protocol -- HTTP/1.1 RFC 2616 Fielding, et al. 13 Caching in HTTP HTTP is typically used for distributed information systems, where performance can be improved by the use of response caches. The HTTP/1.1 protocol includes a number of elements intended to make caching work as well as possible. Because these elements are inextricable from other aspects of the protocol, and
MySQL Performance Blog � Cache Performance Comparison
Jay Pipes continues cache experiements and has compared performance of MySQL Query Cache and File Cache. Jay uses Apache Benchmark to compare full full stack, cached or not which is realistic but could draw missleading picture as contribution of different components may be different depending on your unique applications. For example for application containing a lot of clode but having only couple
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Google Code Archive - Long-term storage for Google Code Project Hosting.
https://labs.cybozu.co.jp/blog/kazuho/archives/2006/02/utilizing_cache.php
Toru Maesaka
https://labs.cybozu.co.jp/blog/kazuho/archives/2007/05/cache_adaptive.php
http://72.14.253.104/search?q=cache:LSaubABCx4kJ:tokuhirom.dnsalias.org/~tokuhirom/tokulog/2183.html+Catalyst::Plugin::Cache::Memcached&hl=ja&gl=jp&ct=clnk&cd=1&lr=lang_ja&client=firefox
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