[B! facebook] uokadaã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

uokada id:uokada

facebookã«é–¢ã™ã‚‹uokadaã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (47)

${{author_name}}$

{{{comment_expanded}}}

{{label}}

{{#is_bookmark}}ãƒªã‚¹ãƒˆ{{/is_bookmark}}{{^is_bookmark}}ãƒªãƒ³ã‚¯{{/is_bookmark}}

${{author_name}}$
{{author_name}}{{created}}
{{ #comment }}{{ comment }}{{ /comment }}
- {{ label }}

${{author_name}}$

{{{comment_expanded}}}

{{label}}

{{#is_bookmark}}ãƒªã‚¹ãƒˆ{{/is_bookmark}}{{^is_bookmark}}ãƒªãƒ³ã‚¯{{/is_bookmark}}

OGPã‚’è¨å®šã—ã‚ˆã†ï¼SNSã§ã‚·ã‚§ã‚¢ã•ã‚Œã‚„ã™ã„è¨å®šæ–¹æ³•ã¨ã¯ï¼Ÿ
SEOæ‹…å½“ã®èµ¤ï¨‘ã§ã™ã€‚ WEBã‚µã‚¤ãƒˆã‚’é‹å–¶ã—ã¦ã„ã‚‹ã¨ã€æµå…¥æ•°ãŒä¼¸ã³ãªã„ã€ã„ã‚ã‚“ãªäººã«è¦‹ã¦ã‚‚ã‚‰ã„ãŸã„ã®ã«ãªã‹ãªã‹çŸ¥ååº¦ãŒä¸ŠãŒã‚‰ãªã„ãªã©ã€æ‚©ã‚“ã§ã„ã‚‹æ–¹ã‚‚å¤šã„ã¨æ€ã„ã¾ã™ã€‚ä»Šå›žã¯ã€SNSã§å¤šãã®æ–¹ã«ç›®ã«ã—ã¦ã‚‚ã‚‰ã†ã€çŸ¥ã£ã¦ã‚‚ã‚‰ã†ãŸã‚ã«å¤§åˆ‡ãªOGPè¨å®šã«ã¤ã„ã¦ã”èª¬æ˜Žã—ã¾ã™ã€‚ OGPã®ãƒ¡ãƒªãƒƒãƒˆã‚„è¨å®šæ–¹æ³•ã«ã¤ã„ã¦ã€ã“ã¡ã‚‰ã®å‹•ç”»ã§ã‚‚ã‚ã‹ã‚Šã‚„ã™ãè§£èª¬ã—ã¦ã„ã¾ã™ã€‚ è¨˜äº‹ã¨ã‚ã‚ã›ã¦ãœã²ã”è¦§ãã ã•ã„ã€‚ OGPã£ã¦ãªã‚“ã®ã“ã¨ï¼Ÿ OGPã¨ã¯ã€ã€ŒOpen Graph Protcolã€ã®ç•¥ã§Facebookã‚„Twitterãªã©ã®SNSã§ã‚·ã‚§ã‚¢ã—ãŸéš›ã«ã€è¨å®šã—ãŸWEBãƒšãƒ¼ã‚¸ã®ã‚¿ã‚¤ãƒˆãƒ«ã‚„ã‚¤ãƒ¡ãƒ¼ã‚¸ç”»åƒã€è©³ç´°ãªã©ã‚’æ£ã—ãä¼ãˆã‚‹ãŸã‚ã®HTMLè¦ç´ ã§ã™ã€‚ SNSä¸Šã§URLãŒå…±æœ‰ã•ã‚ŒãŸéš›ã«è¨å®šã—ã¦ãŠã„ãŸã‚¿ã‚¤ãƒˆãƒ«ã‚„ç”»åƒã€èª¬æ˜Žæ–‡ãªã©ãŒè¡¨ç¤ºã•ã‚Œã‚‹ã‚ˆã†ã«ãªã‚Šã€ãƒ¦ãƒ¼ã‚¶ãƒ¼ã«å¯¾ã—ã¦WEBãƒšãƒ¼ã‚¸ã®å†…å®¹ã‚’è©³ã—ãä¼ãˆã‚‹ã“ã¨ãŒã§ãã¾ã™ã€‚ ä¾‹ãˆã°ã€å¼Šç¤¾ã®ãƒ–ãƒã‚°
uokada 2021/10/01
"TOPãƒšãƒ¼ã‚¸ã®å ´åˆã¯ã€Œwebsiteã€ã€WEBã‚µã‚¤ãƒˆä¸Šã®è¨˜äº‹ãƒšãƒ¼ã‚¸ãªã©ã€TOPãƒšãƒ¼ã‚¸ä»¥å¤–ã«ã¯ã€Œarticleã€ã‚’æŒ‡å®šã—ã¾ã™ã€‚"

twitter

OGP

facebook

protocol

SNS
ãƒªãƒ³ã‚¯
Open Graph protocol
Introduction The Open Graph protocol enables any web page to become a rich object in a social graph. For instance, this is used on Facebook to allow any web page to have the same functionality as any other object on Facebook. While many different techno logies and schemas exist and could be combined together, there isn't a single techno logy which provides enough information to richly represent any
uokada 2021/10/01
facebook

protocol

ogp

SNS
ãƒªãƒ³ã‚¯
Nemo: Data discovery at Facebook
Large-scale companies serve millions or even billions of people who depend on the services these companies provide for their everyday needs. To keep these services running and delivering meaningful experiences, the teams behind them need to find the most relevant and accurate information quickly so that they can make informed decisions and take action. Finding the right information can be hard for
uokada 2020/10/10
data

engineering

facebook

architecture
ãƒªãƒ³ã‚¯
LogDevice Â· Distributed storage for sequential data
Distributed storage for sequential dataLogDevice is a scala ble distributed log storage system that offers durability, high availability, and total order of records under failures. It is designed for a variety of workloads including event streaming, replication pipelines, transaction logs, and deferred work journals.
uokada 2019/10/23
storage

facebook

logging

ã‚ã¨ã§èªã‚€
ãƒªãƒ³ã‚¯
Instagramã¯ã„ã‹ã«ã—ã¦ã‚¹ãƒ†ãƒ¼ãƒˆãƒ•ãƒ«ã‚µãƒ¼ãƒ“ã‚¹ã‚’åˆ†å‰²ã—ãŸã‹
Spring Bootã«ã‚ˆã‚‹APIãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰æ§‹ç¯‰å®Ÿè·µã‚¬ã‚¤ãƒ‰ ç¬¬2ç‰ˆ ä½•åƒäººã‚‚ã®é–‹ç™ºè€…ãŒã€InfoQã®ãƒŸãƒ‹ãƒ–ãƒƒã‚¯ã€ŒPractical Guide to Building an API Back End with Spring Bootã€ã‹ã‚‰ã€Spring Bootã‚’ä½¿ã£ãŸREST APIæ§‹ç¯‰ã®åŸºç¤Žã‚’å¦ã‚“ã ã€‚ã“ã®æœ¬ã§ã¯ã€å‡ºç‰ˆæ™‚ã«æ–°ã—ããƒªãƒªãƒ¼ã‚¹ã•ã‚ŒãŸãƒãƒ¼ã‚¸ãƒ§ãƒ³ã§ã‚ã‚‹ Spring Boot 2 ã‚’ä½¿ç”¨ã—ã¦ã„ã‚‹ã€‚ã—ã‹ã—ã€Spring Boot3ãŒæœ€è¿‘ãƒªãƒªãƒ¼ã‚¹ã•ã‚Œã€é‡è¦ãªå¤‰...
uokada 2019/01/20
Instagram

facebook

cassandra
ãƒªãƒ³ã‚¯
Managing data store locality at scale with Akkio - Facebook Code
In the past eight years, weâ€™ve broken ground on 15 data centers around the world. During this time, the number of people using Facebook every month topped 2.2 billion. Those people are all sharing memories through posts, images, and videos. Initially, we were able to ensure low-latency, continuous access for everyone by storing replicas of the entire data set in each data center region. But as we
uokada 2019/01/20
facebook

data
ãƒªãƒ³ã‚¯
Facebookã¯ãƒ¬ã‚¤ãƒ¤4ãƒãƒ¼ãƒ‰ãƒãƒ©ãƒ³ã‚µã‚’IPVS(LVS)ã‹ã‚‰XDPãƒ™ãƒ¼ã‚¹ã®ã‚‚ã®ã«ä¹—ã‚Šæ›ãˆã¤ã¤ã‚ã‚‹ - yunazuno.log
4æœˆã«é–‹å‚¬ã•ã‚ŒãŸnetdev 2.1ã§é¢ç™½ã„ã‚»ãƒƒã‚·ãƒ§ãƒ³ãŒã‚ã£ãŸã®ã§ãƒ¡ãƒ¢ã€‚ FacebookãŒä½¿ç”¨ã—ã¦ã„ã‚‹ãƒ¬ã‚¤ãƒ¤4ã®ãƒãƒ¼ãƒ‰ãƒãƒ©ãƒ³ã‚µã«é–¢ã™ã‚‹ç™ºè¡¨ã§ã€å¾“æ¥ã¯IPVS (LVS) ã‚’ä½¿ç”¨ã—ã¦ã„ãŸãŒã€XDPãƒ™ãƒ¼ã‚¹ã§è‡ªã‚‰é–‹ç™ºã—ãŸã‚‚ã®ã«ç§»è¡Œã—ã¤ã¤ã‚ã‚‹ã€ã¨ã„ã†å†…å®¹ã€‚ XDP Production Usage: DDoS Protection and L4LB (slide) www.youtube.com XDP (eXpress Data Path) ã«ã¤ã„ã¦ã¯ä»¥å‰ã®ã‚¨ãƒ³ãƒˆãƒªã§ç°¡å˜ã«ç´¹ä»‹ã—ãŸã€‚ yunazuno.hatena blog.com XDPã‚’æ”¹ã‚ã¦ç°¡å˜ã«ç´¹ä»‹ã™ã‚‹ã¨ã€Linuxã‚«ãƒ¼ãƒãƒ«ã®ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã‚¹ã‚¿ãƒƒã‚¯ã®æœ€ä¸‹éƒ¨ (NICã«ä¸€ç•ªè¿‘ã„å ´æ‰€) ã§ãƒ‘ã‚±ãƒƒãƒˆå‡¦ç†ã‚’è¡Œã†ä»•çµ„ã¿ã®ã“ã¨ã§ã€ã‚ªãƒ¼ãƒãƒ¼ãƒ˜ãƒƒãƒ‰ãŒéžå¸¸ã«å°ã•ã„é«˜é€Ÿãƒ‘ã‚±ãƒƒãƒˆå‡¦ç†ã®å®Ÿç¾ã‚’ç›®çš„ã¨ã—ã¦ã„ã‚‹ã€‚XDPã¯eBPFã‚’ç”¨ã„ã¦ãŠã‚Šã€eBPFãŒæä¾›ã™ã‚‹map
uokada 2018/12/23
ã‚ã¨ã§èªã‚€

LB

facebook

network
ãƒªãƒ³ã‚¯
Page not found | Starburst
These cookies are essential in order to enable you to move around the website and use its features, such as accessing secure areas of the website. These are analytics cookies that allow us to collect information about how visitors use a website, for instance which pages visitors go to most often, and if they get error messages from web pages. This helps us to improve the way the website works and
uokada 2018/08/02
presto

facebook

event
ãƒªãƒ³ã‚¯
Migrating Messenger storage to optimize performance
More than a billion people now use Facebook Messenger to instantly share text, photos, video, and more. As we have evolved the product and added new functionality, the underlying techno logies that power Messenger have changed substantially. When Messenger was originally designed, it was primarily intended to be a direct messaging product similar to em ail, with messages waiting in your inbox the ne
uokada 2018/06/27
storage

performance

facebook

database
ãƒªãƒ³ã‚¯
OSSã§å§‹ã‚ã‚‹ã‚»ã‚ãƒ¥ãƒªãƒ†ã‚£ãƒã‚°åŽé›†/oss-securitylog-builderscon2017
osqueryã®ç´¹ä»‹ https://builderscon.io/tokyo/2017/session/ce1bf3ee-33bd-4899-897d-ba3c4364c1c5
uokada 2017/08/05
osquery

facebook
ãƒªãƒ³ã‚¯
facebookã®13å„„ãƒ¦ãƒ¼ã‚¶ãƒ¼ã‚’æ”¯ãˆã‚‹ãƒãƒ¼ãƒ‰ãƒãƒ©ãƒ³ã‚µãƒ¼ã®è©± - stanaka's blog
æœ€è¿‘ã€SREãŒè©±é¡Œã§ã™ãã€‚ tech.mercari.com www.wantedly.com ã¨ã„ã†ã“ã¨ã§SREã«ã¤ã„ã¦èª¿ã¹ã¦ãŸã‚‰ã€SREconãªã‚“ã¦ã‚‚ã®ãŒé–‹å‚¬ã•ã‚Œã¦ã„ãŸã®ã§ä¸ã‚’è¦‹ã¦ãŸã‚‰ã€ã€ŒBuilding a Billion User Load Balancerã€ã¨ã„ã†ã‚¿ã‚¤ãƒˆãƒ«ã§Facebookã®DNSã€œLBã¾ã§ã®è©±ãŒã‚ã£ãŸã®ã§ã€ãã®ãƒ¡ãƒ¢ã§ã™ã€‚ Building a Billion User Load Balancer | USENIX tl;dr tinydns + IPVS ã§ Facebookè¦æ¨¡ã¯ã„ã‘ã‚‹ httpsã®æŽ¥ç¶šç¢ºç«‹ã¯ã‹ãªã‚Šé‡ã„(RTTã®4å€ = RTT 150msã¨ã™ã‚‹ã¨GETã¾ã§600ms)ã®ã§ã€å¤ªå¹³æ´‹è¶Šãˆã¨ã‹ã¯åŽ³ã—ã„ httpsã‚’çµ‚ç«¯ã•ã›ã‚‹CDNã¨ã‹ã¯æ´»ç”¨ã®å¯èƒ½æ€§ã‚ã‚Šãã† (å›½å†…ã ã‘ã‚’è€ƒæ…®ã™ã‚‹ãªã‚‰å½±éŸ¿ã¯è»½å¾®ã‹ã‚‚) ãƒ¡ãƒ¢ L4 LB shiv (IPVS + pyt
uokada 2015/12/16
facebookã‚‚å‡„ã„ã‘ã©Google analyticsãŒ1ç•ªã‚„ã°ãã†

facebook

dns

loadbalancer
ãƒªãƒ³ã‚¯
Scaling the Facebook data warehouse to 300 PB
At Facebook, we have unique storage scalability challenges when it comes to our data warehouse. Our warehouse stores upwards of 300 PB of Hive data, with an incoming daily rate of about 600 TB. In the last year, the warehouse has seen a 3x growth in the amount of data stored. Given this growth trajectory, storage efficiency is and will continue to be a focus for our warehouse infrastructure. There
uokada 2015/05/02
hive

development

facebook

hadoop
ãƒªãƒ³ã‚¯
ã€ŽPrestoã¨ã¯ä½•ã‹ï¼ŒPrestoã§ä½•ãŒã§ãã‚‹ã‹ã€ - ãƒˆãƒ¬ã‚¸ãƒ£ãƒ¼ãƒ‡ãƒ¼ã‚¿ï¼ˆTreasure Dataï¼‰ãƒ–ãƒã‚°
ãƒˆãƒ¬ã‚¸ãƒ£ãƒ¼ãƒ‡ãƒ¼ã‚¿ã¯ã‚¯ãƒ©ã‚¦ãƒ‰ã§ãƒ‡ãƒ¼ã‚¿ãƒžãƒãƒ¼ã‚¸ãƒ¡ãƒ³ãƒˆã‚µãƒ¼ãƒ“ã‚¹ã‚’æä¾›ã—ã¦ã„ã¾ã™ã€‚ Hadoop Conference Japan 2014 ä»¥å‰ã«å‘ŠçŸ¥ã—ãŸHadoop Conference Japan 2014ã§ï¼Œå¼Šç¤¾Software Architectã®å¤æ©‹ãŒç™ºè¡¨ã—ã¾ã—ãŸã€‚ ãƒ†ãƒ¼ãƒžã¯ï¼ŒFacebookãŒå…¬é–‹ã—ãŸæ–°ã—ã„åˆ†æ•£å‡¦ç†åŸºç›¤ï¼ŒPrestoã€‚å®Ÿã¯FacebookãŒå½¼ã‚‰ã®è¶…å¤§è¦æ¨¡ãªãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆã«å¯¾ã—ã¦ã‚¤ãƒ³ã‚¿ãƒ©ã‚¯ãƒ†ã‚£ãƒ–ã«çµæžœã‚’è¿”ã›ã‚‹ã‚ˆã†ã«ã¨é–‹ç™ºã•ã‚ŒãŸã‚‚ã®ã§ã™ã€‚é–‹ç™ºãŒå§‹ã¾ã£ã¦ã¾ã 2å¹´ã‚‚çµŒã£ã¦ãŠã‚Šã¾ã›ã‚“ãŒï¼Œä»Šã§ã¯ãƒˆãƒ¬ã‚¸ãƒ£ãƒ¼ãƒ‡ãƒ¼ã‚¿ã‚’åˆã‚ã¨ã—ã¦å¤šãã®ãƒãƒƒã‚«ãƒ¼é”ãŒã‚³ãƒŸãƒƒã‚¿ãƒ¼ã¨ã—ã¦å‚åŠ ã™ã‚‹æ´»ç™ºçš„ãªãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã«æˆé•·ã—ã¦ã„ã¾ã™ã€‚ Prestoã¯Hiveã‚„Impalaã¨åŒã˜ã€ŒSQL Query Engineã€ã§ã‚ã‚Šï¼Œç‰¹ã«æ•°ç™¾GBã‚’è¶…ãˆã‚‹å¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿ã«å¯¾ã—ã¦ã‚‚ã‚¤ãƒ³ã‚¿ãƒ©ã‚¯ãƒ†ã‚£ãƒ–ãªãƒ¬ã‚¹ãƒãƒ³ã‚¹ã‚’ï¼ˆã‚³ãƒ³ãƒž0ç§’ä»¥ä¸‹ï¼Œé…ãã¦
uokada 2015/03/22
facebook

presto

bigdata
ãƒªãƒ³ã‚¯
Facebookã®æ•°åƒå°è¦æ¨¡ã®memcachedé‹ç”¨ã«ã¤ã„ã¦ - ã‚†ã†ã†ããƒ–ãƒã‚°
Linuxã®ãƒ–ãƒãƒƒã‚¯ãƒ‡ãƒã‚¤ã‚¹ãƒ¬ãƒ™ãƒ«ã§å®Ÿç¾ã™ã‚‹rsyncã‚ˆã‚Šé«˜é€Ÿãªå·®åˆ†ãƒãƒƒã‚¯ã‚¢ãƒƒãƒ—ã«ã¤ã„ã¦ - ã‚†ã†ã†ããƒ–ãƒã‚°ã®ç¶šãã¨ã—ã¦ã€Facebook ã® memcached é‹ç”¨ã«é–¢ã™ã‚‹è«–æ–‡ã‚’èªã‚“ã ã€‚ ã‚¿ã‚¤ãƒˆãƒ«ãªã©ã¯ä»¥ä¸‹ã®é€šã‚Šã€‚ NSDI ã¯ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã‚·ã‚¹ãƒ†ãƒ ã«é–¢ã™ã‚‹ãƒˆãƒƒãƒ—ãƒ¬ãƒ™ãƒ«ã®ã‚«ãƒ³ãƒ•ã‚¡ãƒ¬ãƒ³ã‚¹ã€‚ Scaling Memcache at Facebook Rajesh Nishtala, Hans Fugal, Steven Grimm, Marc Kwiatkowski, Herman Lee, Harry C. Li, Ryan McElroy, Mike Paleczny, Daniel Peek, Paul Saab, David Stafford, Tony Tung, Venkateshwaran Venkataramani NSDI'13 In Proceedings of the
uokada 2014/07/09
memcachedæ•°åƒå°ã£ã¦ã“ã¨ã¯ã‚¢ãƒ—ãƒªã‚±ãƒ¼ã‚·ãƒ§ãƒ³ã‚µãƒ¼ãƒãƒ¼ã¯ä¸€ä½“ã©ã‚Œãã‚‰ã„ã‚ã‚‹ã‚“ã ï¼Ÿ

memcached

facebook

architecture
ãƒªãƒ³ã‚¯
Facebookã«ãŠã‘ã‚‹MySQLã‚’ç”¨ã„ãŸå¤§è¦æ¨¡ã‚·ã‚¹ãƒ†ãƒ ã‚¢ãƒ¼ã‚ãƒ†ã‚¯ãƒãƒ£ã®ç¾å®Ÿï½žMySQL Connect 2013
ç±³ã‚ªãƒ©ã‚¯ãƒ«ãŒä¸»å‚¬ã™ã‚‹MySQLã®ã‚¤ãƒ™ãƒ³ãƒˆã€ŒMySQL Connectã€ãŒ9æœˆ21æ—¥ã‹ã‚‰23æ—¥ã¾ã§ã€ã‚µãƒ³ãƒ•ãƒ©ãƒ³ã‚·ã‚¹ã‚³ã§é–‹å‚¬ã•ã‚Œã¾ã—ãŸã€‚Oracle OpenWorldã€JavaOneã¨ã®åŒæ™‚é–‹å‚¬ã§ã—ãŸã€‚ åŸºèª¿è¬›æ¼”ã®1ã¤ã«ã¯ã€MySQLã®ãƒ˜ãƒ“ãƒ¼ãƒ¦ãƒ¼ã‚¶ãƒ¼ã§ã‚ã‚‹Facebookã®Harrison Fiskæ°ãŒç™»å£‡ã€‚Facebookã«ãŠã‘ã‚‹MySQLã®å½¹å‰²ã€å¤§è¦æ¨¡é‹ç”¨ã®èƒŒæ™¯ãªã©ã‚’ç´¹ä»‹ã—ã¦ã„ã¾ã™ã€‚ãã®å†…å®¹ã‚’ãƒ€ã‚¤ã‚¸ã‚§ã‚¹ãƒˆã§ç´¹ä»‹ã—ã¾ã—ã‚‡ã†ã€‚ MySQL@Facebook Lots and lots of small data Harrison Fiskæ°ã€‚ Facebookã§ãƒ‡ãƒ¼ã‚¿ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ãƒãƒ¼ãƒ ã®ãƒžãƒãƒ¼ã‚¸ãƒ£ã‚’ã—ã¦ã„ã‚‹ã€‚ç¤¾å†…ã§ã¯MySQLã¯ã‚‚ã¡ã‚ã‚“ã€HBase Hadoopãªã©ã«ã‚‚é–¢ã‚ã£ã¦ã„ã‚‹ã€‚ ã¾ãšã¯ã€ã©ã‚“ãªç¨®é¡žã®ãƒ‡ãƒ¼ã‚¿ã‚’MySQLã§æ‰±ã£ã¦ã„ã‚‹ã®ã‹ã«ã¤ã„ã¦ã€‚ Facebookã¨ã¯åŸºæœ¬çš„ã«ã‚°ãƒ©ãƒ•ã ã€‚ã‚°
uokada 2013/09/27
MySQL

facebook

database
ãƒªãƒ³ã‚¯
FacebookãŒSPDYã‚’å§‹ã‚ã¾ã—ãŸï¼ - ã¼ã¡ã¼ã¡æ—¥è¨˜
1. SPDYãŒç†±ã„ã§ã™ï¼ ã¡ã‚‡ã†ã©å…ˆé€±æœ«CROSS2013ã® æ¬¡ä¸–ä»£Webã‚»ãƒƒã‚·ãƒ§ãƒ³(ãƒ—ãƒãƒˆã‚³ãƒ«ç·¨) ã«ãƒ‘ãƒãƒ©ãƒ¼ã¨ã—ã¦å‚åŠ ã•ã›ã¦ã„ãŸã ãã¾ã—ãŸã€‚ æ¬¡ä¸–ä»£Webã®éµã¨ãªã‚‹WebSocketãƒ»SPDYãƒ»HTTP/2.0ã«ã¤ã„ã¦ç†±ã„è©±ãŒã§ãã¨ã¦ã‚‚æº€è¶³ã—ã¦ã„ã¾ã™ã€‚ä¼šå ´ã¯æº€å“¡ã§çš†ã•ã‚“ãŒã¨ã¦ã‚‚èˆˆå‘³ã‚’æŒã£ã¦èžã„ã¦ã„ãŸã ã„ã¦ã„ã‚‹ã®ã‚‚ååˆ†æ„Ÿã˜ã‚‹ã“ã¨ãŒã§ãã¾ã—ãŸã€‚ å‚åŠ ã—ã¦ã„ãŸã ã„ãŸæ–¹ã€æœ¬å½“ã«ã‚ã‚ŠãŒã¨ã†ã”ã–ã„ã¾ã—ãŸã€‚ 2. LINEãŒSPDYã‚’ä½¿ã£ã¦ã„ã‚‹ ã‚»ãƒƒã‚·ãƒ§ãƒ³ã§ã¯ã€ã¤ã„æœ€è¿‘ LINE ãŒ SPDY ã‚’ä½¿ã£ã¦ã„ã‚‹ã¨ã„ã†ç™ºè¡¨( http://tech.naver.jp/blog/?p=2381 )ã«ã¤ã„ã¦ç´¹ä»‹ã—ã€ãã®æœ‰ç”¨æ€§ã«ã¤ã„ã¦ã„ãã¤ã‹ã‚³ãƒ¡ãƒ³ãƒˆã‚’ã—ã¾ã—ãŸã€‚ SPDYã¯ã€ Google ãŒ2011å¹´ã‚ˆã‚Š2å¹´è¿‘ãã»ã¨ã‚“ã©ã®Googleã‚µãƒ¼ãƒ“ã‚¹ã§å®Ÿé‹ç”¨ã—ã¦ã„ã¾ã™ãŒã€Googleä»¥å¤–ã§ä¸–ç•Œçš„ã«ãƒ¡ã‚¸ãƒ£ãƒ¼ãªå¤§è¦æ¨¡ã®
uokada 2013/08/12
SPDY

google

facebook

SSL
ãƒªãƒ³ã‚¯
é–“é•ã£ãŸãƒ‡ã‚¸ã‚¿ãƒ«ä¸€çœ¼ãƒ¬ãƒ•ã®ä½¿ã„æ–¹ã‚’ã—ã¦ã„ã¾ã›ã‚“ã‹ï¼ŸPhotoshop Camera Raw ç¾åƒãƒ†ã‚¯ãƒ‹ãƒƒã‚¯ | DX.univ
2013å¹´ 05æœˆ 29æ—¥ é–“é•ã£ãŸãƒ‡ã‚¸ã‚¿ãƒ«ä¸€çœ¼ãƒ¬ãƒ•ã®ä½¿ã„æ–¹ã‚’ã—ã¦ã„ã¾ã›ã‚“ã‹ï¼ŸPhotoshop Camera Raw ç¾åƒãƒ†ã‚¯ãƒ‹ãƒƒã‚¯ Tomonori Kawata ã©ã†ã‚‚ã€æ–°äººã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã®å·ç”°ã§ã™ã€‚ ä»Šå›žã¯ã„ã¤ã‚‚ã®Linuxãƒã‚¿ã§ã¯ãªãã€å†™çœŸãƒã‚¿ã‚’æ›¸ã„ã¦ã¿ãŸã„ã¨æ€ã„ã¾ã™ã€‚ å†™çœŸï¼ˆç”»åƒï¼‰ã®é‡è¦æ€§ çš†ã•ã‚“ã¯ã©ã†ã‚„ã£ã¦ã“ã®è¨˜äº‹ã«ãŸã©ã‚Šç€ã„ãŸã§ã—ã‚‡ã†ã‹ï¼Ÿ ãƒˆãƒƒãƒ—ãƒšãƒ¼ã‚¸ã‚„Facebookã‹ã‚‰æ¥ãŸã¨ã„ã†æ–¹ã¯ã€è¨˜äº‹ã®ã‚¿ã‚¤ãƒˆãƒ«ã¨åŒæ™‚ã«ç¾Žå‘³ã—ãã†ãªãƒãƒ³ãƒãƒ¼ã‚°ã®å†™çœŸã‚’è¦‹ã‹ã‘ãŸã¨æ€ã„ã¾ã™ã€‚ ã‚‚ã—ã‹ã—ãŸã‚‰ã€æ™®æ®µå½“ãƒ–ãƒã‚°ã‚’é–²è¦§ã—ãªã„ã‚ˆã†ãªäººã‚‚ã€ãƒãƒ³ãƒãƒ¼ã‚°ã®ç”»åƒã«é‡£ã‚‰ã‚Œã¦è¦‹ã«æ¥ã¦ãã‚ŒãŸã‹ã‚‚ã—ã‚Œã¾ã›ã‚“ã€‚ è¨˜äº‹ã®å†…å®¹ã¯ã‚‚ã¡ã‚ã‚“å¤§åˆ‡ã§ã™ãŒã€æ–‡å—ã°ã‹ã‚Šã ã¨æ–‡å—ã‚’èªã‚€ã“ã¨ãŒè‹¦æ‰‹ãªäººãŒè¾›ã„å ´åˆã‚‚ã‚ã‚Šã¾ã™ã®ã§ã€æ™‚æŠ˜å†™çœŸã‚„ç”»åƒã‚’å…¥ã‚Œã¦ã„ãã“ã¨ãŒå¤§äº‹ã§ã™ã€‚ ã¾ãŸã€è¨˜äº‹ã®å†…å®¹ã«ã‚ã¾ã‚Šèˆˆå‘³ãŒãªã„äººã«ã‚‚ã€å†™çœŸã‚„ç”»åƒã®é…åŠ›ã«ã‚ˆã£ã¦è¨˜äº‹ã‚’
uokada 2013/05/30
iphone

photo

Instagram

facebook
ãƒªãƒ³ã‚¯
Scaling Memcache at Facebook | USENIX
by Michael Piatek Responsiveness is essential for web services. Speed drives user engagement, which drives revenue. To reduce response latency, modern web services are architected to serve as much as possible from in-memory caches. The structure is familiar: a database is split among servers with caches for scaling reads. Over time, caches tends to accumulate more responsibility in the storage sta
uokada 2013/04/16
facebook

memcached
ãƒªãƒ³ã‚¯
Exploring the Software Behind Facebook, the World's Largest Social Media Site - Pingdom
At the scale that Facebook operates, several traditional approaches to serving web content break down or simply arenâ€™t practical. The challenge for Facebookâ€™s engineers has been to keep the site up and running smoothly in spite of handling over two billion active users. This article takes a look at some of the software and techniques they use to accomplish that. Facebookâ€™s Scaling Challenge Before
uokada 2013/04/01
facebook
ãƒªãƒ³ã‚¯
æ¬¡ä¸–ä»£ã‚¢ãƒ¼ã‚ãƒ†ã‚¯ãƒãƒ£ã«ã¤ã„ã¦ã®è€ƒãˆã‚’ã¾ã¨ã‚ã¦ãŠãã€‚ã¾ãšã¯ã€Hbaseã®å‹‰å¼·ä¼šã®ãŠè©±ã€‚æŸç•Œéšˆã§ã¯å‰²ã¨è©±é¡Œã«ãªã£ãŸã®ã§ã€ç´°ã‹ã„ãƒ–ãƒã‚°ã‚„ã‚µã‚¤ãƒˆã¯çµæ§‹ã€ç´¹ä»‹ã•ã‚Œã¦ã„ã‚‹ã€‚ã®ã§ç‰¹ã«è©³ç´°ã¯çœãã€‚ä¸€å¿œtatsuyaã•ã‚“ã®Slideshareã¯Tokyo HBase Meetup - Realtime Big Data at Facebook with Hadoop and ...slideã‚’è¦‹ã¦ã„ã‚‹ã ã‘ã§ã¯ã€ã‚ˆãã‚ã‹ã‚‰ãªã„ã¨æ€ã†ãŒJonathanã¨ã®ä¼šè©±ã§ã¯ã€FBã¯ãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰ã®éƒ¨åˆ†ã‚’å«ã‚ã¦ãƒãƒƒãƒå‡¦ç†ã¯åˆ¥ã®Hadoopã‚¯
uokada 2012/11/27
hbase

facebook

hadoop

tumblr
ãƒªãƒ³ã‚¯
1 2 3 æ¬¡ã®ãƒšãƒ¼ã‚¸