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2010å¹´9æœˆã«ã€ã‚ªãƒ©ã‚¯ãƒ«ç¤¾ã¯ã€Oracle Linux 5ã‚’ä½¿ç”¨ã—ãŸãƒ‡ãƒ—ãƒã‚¤ãƒ¡ãƒ³ãƒˆã«æŽ¨å¥¨ã•ã‚Œã‚‹ã‚«ãƒ¼ãƒãƒ«ã¨ã—ã¦Oracle Linuxç”¨ã®æ–°ã—ã„Unbreakable Enterprise Kernel (UEK)ã‚’å…¬é–‹ã—ã¾ã—ãŸã€‚Oracle Linux 5.5ä»¥é™ã‹ã‚‰ã€Red Hatäº’æ›ã‚«ãƒ¼ãƒãƒ«ã¾ãŸã¯UEKã®ã„ãšã‚Œã‹ã‚’ä½¿ç”¨ã§ãã‚‹ã‚ˆã†ã«ãªã‚Šã¾ã—ãŸã€‚Oracle Linux 5.6ã§ã€UEKã¯ãƒ‡ãƒ•ã‚©ãƒ«ãƒˆãƒ»ã‚«ãƒ¼ãƒãƒ«ã«ãªã‚Šã¾ã—ãŸã€‚ UEKä½œæˆã®ä¸»ãªå‹•æ©Ÿã¯ã€ExadataãŠã‚ˆã³Exalogicã«ã‚ˆã£ã¦ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ãƒªãƒ³ã‚°ã•ã‚ŒãŸã‚·ã‚¹ãƒ†ãƒ ç”¨ã®é«˜æ€§èƒ½ãªæœ€æ–°ã®Linuxã‚«ãƒ¼ãƒãƒ«ã‚’æä¾›ã™ã‚‹ã“ã¨ã§ã—ãŸã€‚ã‚«ãƒ¼ãƒãƒ«ã¯ã€CPUã®æ•°ã€ãƒ¡ãƒ¢ãƒªãƒ¼ãŠã‚ˆã³ã‚¤ãƒ³ãƒ•ã‚£ãƒ‹ãƒãƒ³ãƒ‰æŽ¥ç¶šã®å¢—åŠ ã«å¿œã˜ã¦ã‚¹ã‚±ãƒ¼ãƒªãƒ³ã‚°ã™ã‚‹å¿…è¦ãŒã‚ã‚Šã¾ã—ãŸã€‚ ã‚ªãƒ©ã‚¯ãƒ«ç¤¾ã§ã¯ã€è² è·ã®é«˜ã„Oracleãƒ¯ãƒ¼ã‚¯ãƒãƒ¼ãƒ‰ã§é›†ä¸çš„ã«UEKã‚’ãƒ†ã‚¹ãƒˆã—ã¦ãŠã‚Šã€UEKã‚’Oracleãƒ‡

yass 2013/08/18

"RSSã¯å„å—ä¿¡ã‚ãƒ¥ãƒ¼ã«CPUã‚’ãƒžãƒƒãƒ—/ãƒžãƒ«ãƒã‚ãƒ¥ãƒ¼ãƒ»ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ãƒ»ãƒ‡ãƒã‚¤ã‚¹ã‚’å«ã‚€ã‚·ã‚¹ãƒ†ãƒ ã§RPSã‚’æ§‹æˆã™ã‚‹åˆ©ç‚¹ãªã—/ãƒžãƒ«ãƒã‚ãƒ¥ãƒ¼ãƒ»ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ãƒ»ãƒ‡ãƒã‚¤ã‚¹ã‚’å«ã‚€ã‚·ã‚¹ãƒ†ãƒ ã§å„CPUãŒå„é€ä¿¡ã‚ãƒ¥ãƒ¼ã«ãƒžãƒƒãƒ—ã•ã‚Œã‚‹ã‚ˆã†XPSã‚’æ§‹æˆ"

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RX

02. RX. å—ä¿¡å‡¦ç† Linux ã§ã¯ï¼ˆä»–ã® OS ã‚‚ãã†ã§ã™ãŒï¼‰ã€å‰²ã‚Šè¾¼ã¿ãƒãƒ³ãƒ‰ãƒ©ã¯è»½ã„ã‚‚ã®ã«ã—ã¦ãŠãã€æ™‚é–“ã®ã‹ã‹ã‚‹å‡¦ç†ã¯å‰²ã‚Šè¾¼ã¿ãƒãƒ³ãƒ‰ãƒ©å¾©å¸°å¾Œï¼ˆå‰²ã‚Šè¾¼ã¿è¨±å¯å¾Œï¼‰ã«è¡Œã„ã¾ã™ã€‚ã“ã®é…å»¶å‡¦ç†ã¯ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢å‰²ã‚Šè¾¼ã¿ï¼ˆãƒœãƒˆãƒ ãƒãƒ¼ãƒ•ã¨ã‚‚è¨€ã†ï¼‰ã¨å‘¼ã°ã‚Œã€ã‚¿ã‚¤ãƒžãƒ¼ã€ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã®é€å—ä¿¡ã€tasklet ãªã©ãŒåˆ©ç”¨ã—ã¦ã„ã¾ã™ã€‚ ï¼ˆã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢å‰²ã‚Šè¾¼ã¿ã¨è¨€ã£ã¦ã‚‚ã€x86 ãŒã‚·ã‚¹ãƒ†ãƒ ã‚³ãƒ¼ãƒ«ã§åˆ©ç”¨ã™ã‚‹ int 0x80 ã®ã‚ˆã†ãª CPU ã®ãƒˆãƒ©ãƒƒãƒ—æ©Ÿèƒ½ã§ã¯ãªãã€å‰²ã‚Šè¾¼ã¿ã‚³ãƒ³ãƒ†ã‚ã‚¹ãƒˆä¸Šã§ã€å‰²ã‚Šè¾¼ã¿è¨±å¯å¾Œã«å®Ÿè¡Œã•ã‚Œã‚‹ã‚³ãƒ¼ãƒ«ãƒãƒƒã‚¯é–¢æ•°ç¾¤ã§ã™ï¼‰ Linux ã® LAN ãƒ‰ãƒ©ã‚¤ãƒã¯ã€å‰²ã‚Šè¾¼ã¿ãƒãƒ³ãƒ‰ãƒ©ã§ã¯ã“ã®ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢å‰²ã‚Šè¾¼ã¿ï¼ˆNET_RX_SOFTIRQï¼‰ã‚’èµ·å‹•ã™ã‚‹ã®ã¿ã«ã¨ã©ã‚ã€LAN ã‚³ãƒ³ãƒˆãƒãƒ¼ãƒ©ã‹ã‚‰ã®ãƒ‡ãƒ¼ã‚¿å—ä¿¡ã‚„å„ç¨®ãƒ—ãƒãƒˆã‚³ãƒ«å‡¦ç†ã¯ NET_RX_SOFTIRQ ä¸Šã§è¡Œã†ã‚ˆã†ã«ãªã£ã¦ã„ã¾ã™ï¼ˆNAPIï¼‰ã€‚ ä»¥

yass 2013/08/18

"RPS ã¯ãƒ‡ãƒ•ã‚©ãƒ«ãƒˆã§ç„¡åŠ¹ / forwarding ã™ã‚‹ã ã‘ã§ã‚ã‚Œã° latency ãŒå¢—ãˆã‚‹ã ã‘ãªã®ã§ã€RPS ã®ä½¿ç”¨ã¯éžæŽ¨å¥¨ / ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã®ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã‚’çœŸå‰£ã«è€ƒãˆã¦ã„ã‚‹å ´åˆã¯ã€MQ ãª NIC ã§ smp_affinity ã‚’è¨å®šã—é‹ç”¨ã™ã‚‹ã®ãŒæ£ã—ã„"

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GitHub - twitter-archive/iago: A load generator, built for engineers

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yass 2013/08/18

"Iago is a load generation tool that replays production or synthetic traffic against a given target/it differs from other load generation tools in that it attempts to hold constant the transaction rate/if you want to test your service at 100K requests per minute, Iago attempts to achieve that rate"

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tsenart/vegeta: HTTP load testing tool and library. It's over 9000!

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yass 2013/08/18

" Vegeta is a versatile HTTP load testing tool built out of need to drill HTTP services with a constant request rate. It can be used both as a command line utility and a library. / -rate=50: Requests per second "

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GitHub - ledsun/cookbook-of-jmeter: Cookbook of Apache JMeter

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yass 2013/08/18

" æœ¬æ–‡æ›¸ã®ç›®çš„ / æœ¬æ–‡ç« ã¯æœªçµŒé¨“è€…ãŒ Apache JMeter ã®ä½¿ã„æ–¹ãŒã‚ã‹ã‚‹ã“ã¨ã‚’ç›®çš„ã¨ã—ã¦ã„ã¾ã™ã€‚æœ¬æ›¸ã®ã‚´ãƒ¼ãƒ«ã¯ä»¥ä¸‹ã®é€šã‚Šã§ã™ã€‚ / JMeterã®ä½¿ã„æ–¹ã‚’ç†è§£ã™ã‚‹ / JMeterã®ç”¨èªžã‚’è¦šãˆã‚‹ "

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pngquant â€” lossy PNG compressor

pngquant is a command-line utility and a library for lossy compression of PNG images. The conversion reduces file sizes significantly (often as much as 70%) and preserves full alpha transparency. Generated images are compatible with all web browsers and operating systems. Features High-quality palette generation using a combination of vector quantization algorithms. Unique adaptive dithering algor

yass 2013/08/18

" pngquant is a command-line utility and a library for converting 24/32-bit PNG images to paletted (8-bit) PNGs. The conversion reduces file sizes significantly (often as much as 70%) and preserves full alpha transparency. "

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åˆ†æ•£ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚’ä½œã‚‹ãŸã‚ã®ãƒ•ãƒ¬ãƒ¼ãƒ ãƒ¯ãƒ¼ã‚¯ Gizzardã®ã”ç´¹ä»‹[å’Œè¨³]

Introducing Gizzard a framework for creating distributed datastores.markdown åˆ†æ•£ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚’ä½œã‚‹ãŸã‚ã®ãƒ•ãƒ¬ãƒ¼ãƒ ãƒ¯ãƒ¼ã‚¯ Gizzardã®ã”ç´¹ä»‹ åŽŸæ–‡: The Twitter Engineering Blog: Introducing Gizzard, a framework for creating distributed datastores This article is translated by @ono_matope. Please contact me if any probl em. ã‚·ãƒ£ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°åºè«– å¤šãã®ãƒ¢ãƒ€ãƒ³ãªWebã‚µã‚¤ãƒˆã¯ã€ï¼‘å°ã®ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿ãƒ¼ã«ç´ã¾ã‚Šãã‚‰ãªã„ã»ã©ã®å¤§é‡ã®ãƒ‡ãƒ¼ã‚¿ã«é«˜é€Ÿã«ã‚¢ã‚¯ã‚»ã‚¹ã™ã‚‹å¿…è¦ãŒã‚ã‚Šã¾ã™ã€‚ãã®ãŸã‚ã€è¤‡æ•°ã®ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ã‚¿ãƒ¼ã«æƒ…å ±ã‚’åˆ†ã‘ã¦æ ¼ç´ã™ã‚‹ã€Œã‚·ãƒ£ãƒ¼ãƒ‰ã€ã¨ã„ã†æ‰‹æ³•ãŒä½¿

yass 2013/08/18

"Replicating, Write-Only, Read-Only, Blocked(Readã‚‚Writeã‚‚ä¸è¨±å¯)ã¨ã„ã£ãŸåºƒãä¾¿åˆ©ãªã„ãã¤ã‹ã®ã‚¹ãƒˆãƒ©ãƒ†ã‚¸ã‚’åŒæ¢±"

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Introducing Gizzard ãƒ¡ãƒ¢(3) - aaa.txt

Gizzardã¨ã„ã†ãƒŸãƒ‰ãƒ«ã‚¦ã‚§ã‚¢ã®è©±ãŒç´¹ä»‹ã‚’ãƒ¡ãƒ¢å–ã‚ŠãªãŒã‚‰èªã‚“ã§ã„ã¾ã™ã€‚å…ƒè¨˜äº‹ã¯ä»¥ä¸‹ã€ Introducing Gizzard, a framework for creating distributed datastores. å‰åŠã¨ä¸ç›¤ã®ãƒ¡ãƒ¢ï¼š Introducing Gizzard ãƒ¡ãƒ¢(1) Introducing Gizzard ãƒ¡ãƒ¢(2) ä»Šå›žã§æœ€å¾Œã¾ã§èªã¿ã¾ã—ãŸã€‚ Gizard ã¯ãƒ•ã‚©ãƒ¼ãƒ«ãƒˆãƒˆãƒ¬ãƒ©ãƒ³ãƒˆ éšœå®³è¨±å®¹æ€§ã¯åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã®æœ€å¤§ã®é–¢å¿ƒäº‹ã§ã‚ã‚‹ã€‚ãªãœãªã‚‰ãã®ã‚ˆã†ãªç³»ã§ã¯å¤šãã®è¨ˆç®—æ©Ÿã¨ é–¢ä¿‚ã—ã¦ã„ã‚‹ã®ã§ã€ã©ã‚“ãªæ™‚ã§ã‚‚ã‚ã‚‹ç¢ºçŽ‡ã§ä¸€ã¤ï¼ˆã¾ãŸã¯å¤šãï¼‰ã®æ©Ÿèƒ½ä¸å…¨ãŒ èµ·ã“ã£ã¦ã„ã‚‹ã‹ã‚‰ã§ã‚ã‚‹ã€‚Gizzardã¯å˜ä¸€éšœå®³ç‚¹ã‚’ã©ã®ã‚ˆã†ãªå½¢ã§ã‚‚é¿ã‘ã¦ã„ã‚‹ã€‚ ã‚‚ã—ã€ãƒ‘ãƒ¼ãƒ†ã‚£ã‚·ãƒ§ãƒ³ä¸ã®ã‚ã‚‹ãƒ¬ãƒ—ãƒªã‚«ãŒã‚¯ãƒ©ãƒƒã‚·ãƒ¥ã—ãŸã‚‰ã€é‡ã¿ä»˜ã‘é–¢æ•°ã«ã—ãŸãŒã£ã¦ã€ Gizzardã¯æ®‹ã‚Šã®å¥åº·ãªãƒ¬ãƒ—ãƒªã‚«ã«ãƒªã‚¯ã‚¨ã‚¹ãƒˆã‚’æ¡ˆå†…ã™ã‚‹

yass 2013/08/18

"ãƒ¬ãƒ—ãƒªã‚«ãŒå¿œç”ã—ãªãã¦ã‚‚ã€å¿œç”ã™ã‚‹ãƒ¬ãƒ—ãƒªã‚«ã«å¯èƒ½ãªé™ã‚Šæ›¸ãè¾¼ã¿ã‹ã¤å¿œç”ã—ãªã„ãƒ¬ãƒ—ãƒªã‚«ã¸ã®æ›¸ãè¾¼ã¿ã‚’ãƒãƒƒãƒ•ã‚¡ãƒªãƒ³ã‚°ã—ã€shardãŒç”Ÿãè¿”ã£ãŸã‚‰å¾Œã§æ›¸ãè¾¼ã‚€/ã€Œå¾Œã§ãƒªãƒˆãƒ©ã‚¤ã€ã™ã‚‹æˆ¦ç•¥/æ›¸ãè¾¼ã¿æ“ä½œã‚’å†ªç‰ã‹ã¤å¯æ›"

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Introducing Gizzard ãƒ¡ãƒ¢(2) - aaa.txt

Introducing Gizzard, a framework for creating distributed datastores. Twitter ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ãƒ–ãƒã‚°ã§Gizzardã¨ã„ã†ãƒŸãƒ‰ãƒ«ã‚¦ã‚§ã‚¢ã®è©±ãŒç´¹ä»‹ã•ã‚Œã¦ã„ã¦éžå¸¸ã«èˆˆå‘³æ·±ã‹ã£ãŸã®ã§ãƒ¡ãƒ¢å–ã‚ŠãªãŒã‚‰èªã‚“ã§ã„ã¾ã™ã€‚ç¶šãã§ã™ã€‚Gizzardã¯Consistent Hashingã§ã¯ãªã„ã®ã§ã™ãã€‚ Gizzardã¯ãƒ•ã‚©ãƒ¯ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ãƒ†ãƒ¼ãƒ–ãƒ«ã‚’é€šã—ã¦ã€ãƒ‘ãƒ¼ãƒ†ã‚£ã‚·ãƒ§ãƒ‹ãƒ³ã‚°å‡¦ç†ã™ã‚‹ã€‚ GIzzardã¯ãƒ‡ãƒ¼ã‚¿ã®ç¯„å›²ã‚’å„ã€…ã®ã‚·ãƒ£ãƒ¼ãƒ‰ã«ãƒžãƒƒãƒ”ãƒ³ã‚°ã™ã‚‹ã“ã¨ã«ã‚ˆã£ã¦ ãƒ‘ãƒ¼ãƒ†ã‚£ã‚·ãƒ§ãƒ‹ãƒ³ã‚°ã™ã‚‹(ã¤ã¾ã‚ŠæŽ’ä»–çš„ãªç¯„å›²ã§è¤‡æ•°ã®ãƒ›ã‚¹ãƒˆã«åˆ†å‰²ã•ã‚Œã‚‹)ã€‚ ã“ã®ãƒžãƒƒãƒ”ãƒ³ã‚°ã¯ä¸‹è¨˜ã®ãƒ†ãƒ¼ãƒ–ãƒ«ã®ã‚ˆã†ã«ã€æ•°å€¤ã®ãƒ¬ãƒ³ã‚¸ã®ä¸‹é™ã¨æ‰€å±žã™ã‚‹ ã‚·ãƒ£ãƒ¼ãƒ‰ã®æƒ…å ±ãŒãƒ•ã‚©ãƒ¯ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ãƒ†ãƒ¼ãƒ–ãƒ«ã«ä¿ç®¡ã•ã‚Œã‚‹ã€‚ æ£ç¢ºã«ã¯ã‚ãªãŸæ–¹ã¯Gizzardã«æ¬¡ã®ã‚ˆã†ãªã‚«ã‚¹ã‚¿ãƒ ãƒãƒƒã‚·ãƒ³ã‚°é–¢æ•°ã‚’ä¾›çµ¦ã™ã‚‹ï¼š ãƒ‡ãƒ¼ã‚¿ã«ã‚

yass 2013/08/18

"GIzzardã¯ãƒ‡ãƒ¼ã‚¿ã®ç¯„å›²ã‚’å„ã€…ã®ã‚·ãƒ£ãƒ¼ãƒ‰ã«ãƒžãƒƒãƒ”ãƒ³ã‚°ã™ã‚‹ã“ã¨ã«ã‚ˆã£ã¦ãƒ‘ãƒ¼ãƒ†ã‚£ã‚·ãƒ§ãƒ‹ãƒ³ã‚°ã™ã‚‹(ã¤ã¾ã‚ŠæŽ’ä»–çš„ãªç¯„å›²ã§è¤‡æ•°ã®ãƒ›ã‚¹ãƒˆã«åˆ†å‰²ã•ã‚Œã‚‹)/ãƒžãƒƒãƒ”ãƒ³ã‚°ã¯ã€æ•°å€¤ã®ãƒ¬ãƒ³ã‚¸ã®ä¸‹é™ã¨æ‰€å±žã™ã‚‹ã‚·ãƒ£ãƒ¼ãƒ‰ã®æƒ…å ±ãŒä¿ç®¡ã•ã‚Œã‚‹"

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New Tweets per second record, and how!

Recently, something remarkable happened on Twitter: On Saturday, August 3 in Japan, people watched an airing of Castle in the Sky, and at one moment they took to Twitter so much that we hit a one-second peak of 143,199 Tweets per second. (August 2 at 7:21:50 PDT; August 3 at 11:21:50 JST) To give you some context of how that compares to typical numbers, we normally take in more than 500 million Tw

yass 2013/08/18

"our Rails servers were only capable of serving 200-300 requests/sec/host. / JVM instead / we push on the order of 10-20K requests/sec/host. / Gizzard was fronting a series of MySQL databases â€“ every time a tweet comes into the system, Gizzard hashes it, and then chooses an appropriate database"

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http://blog.chase-dream.com/2010/04/28/961

yass 2013/08/18

" å›žå¸°åˆ†æžï¼ˆæœ€å°äºŒä¹—æ³•ï¼‰ã§æ±‚ã¾ã‚‹å‚¾ãã¯ï¼Œ x ã¨ y ã®ç›¸é–¢ä¿‚æ•°ã«ç‰ã—ããªã‚‹ï¼Žã—ãŸãŒã£ã¦ï¼Œå‚¾ããŒ1ã¨ãªã‚‹ã®ã¯ï¼Œã™ã¹ã¦ã®ãƒ‡ãƒ¼ã‚¿ãŒç¶ºéº—ã«ä¸€ç›´ç·šä¸Šã«ã®ã£ãŸã¨ãã ã‘ã ï¼Ž"

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Fluentdã¯ã€Rubyè£½ã®ãƒã‚°ã‚³ãƒ¬ã‚¯ã‚¿ã ã€‚ã‚³ãƒ¼ãƒ‰ã¯å…¬é–‹ã•ã‚Œã¦ã„ã‚‹ã€‚ æ§˜ã€…ãªãƒã‚°ã‚’æ§‹é€ åŒ–ã—ã¦ä¸€å…ƒç®¡ç†ã™ã‚‹ã“ã¨ãŒã§ãã€åŽé›†ã¨è§£æžã¸ã®ãƒãƒ¼ãƒ‰ãƒ«ã‚’å¤§ããä¸‹ã’ã¦ãã‚Œã‚‹ã€‚ ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã‚‚ãƒ—ãƒ©ã‚°ã‚¤ãƒ³é–‹ç™ºã‚‚ç°¡å˜ã€‚æ—¥æœ¬èªžã®è³‡æ–™ã‚‚å¤šã„ã€‚ ãã®è³‡æ–™ã‚‚æ§˜ã€…ã‚ã‚‹ãŒã€ãƒ—ãƒ©ã‚°ã‚¤ãƒ³ã‚’è¦‹ã‚‹ãªã‚‰ã“ã‚ŒãŒæœ€è‰¯ã ã¨æ€ã†ã€‚å¿…è¦ãªæƒ…å ±ãŒã‚ˆãã¾ã¨ã¾ã£ã¦ãŠã‚Šã€å¿…èªã¨ã„ãˆã‚‹ã€‚ Big Dataå…¥é–€ã«è¦‹ã›ã‹ã‘ãŸFluentdå…¥é–€ from Keisuke Takahashi ãƒ‡ãƒ¼ã‚¿ã®ç¢ºå®Ÿãªè»¢é€ã‚’å®Ÿç¾ã™ã‚‹ãƒãƒƒãƒ•ã‚¡æ©Ÿèƒ½ã«ã¤ã„ã¦ã¯ã€æ± ç”°å¤§è¼”ã•ã‚“ã®ãƒ–ãƒã‚°ãŒè©³ã—ã„ã€‚ã•ã¦ã€Fluentdã¯ãƒ‡ãƒ¼ã‚¿ã‚’åŽé›†ã—ã¦ãã‚Œã‚‹ãŒã€ä¿å˜ã¯ã—ã¦ãã‚Œãªã„ã€‚ æ°¸ç¶šåŒ–ã«ã¯ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ãŒå¿…è¦ã ã€‚ ãã“ã§ã€Riakã€‚ Bashoç¤¾ãŒã‚¹ãƒãƒ³ã‚µãƒ¼ãƒ‰ã™ã‚‹Erlangè£½åˆ†æ•£åž‹KVSã€‚ã“ã‚Œã‚‚OSSã ãŒã€å¥‘ç´„ã«ã‚ˆã£ã¦å•†ç”¨ã‚µãƒ¼ãƒ“ã‚¹ãŒå—ã‘ã‚‰ã‚Œã‚‹ã€‚ ã“ã‚ŒãŒã¾ãŸã‚¨ãƒƒã‚¸ç«‹ã¡ã¾ãã£ã¦ã¦

yass 2013/08/18

fluentd
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Speeding Up I/O Workloads with IntelÂ® Optaneâ„¢ Persistent Memory

yass 2013/08/18

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GitHub - twitter-archive/iago: A load generator, built for engineers

tsenart/vegeta: HTTP load testing tool and library. It's over 9000!

GitHub - ledsun/cookbook-of-jmeter: Cookbook of Apache JMeter

pngquant â€” lossy PNG compressor

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Introducing Gizzard ãƒ¡ãƒ¢(3) - aaa.txt

Introducing Gizzard ãƒ¡ãƒ¢(2) - aaa.txt

New Tweets per second record, and how!

http://blog.chase-dream.com/2010/04/28/961

Fluentdã¨Riakã®è©± - After Coding

Speeding Up I/O Workloads with IntelÂ® Optaneâ„¢ Persistent Memory

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