{"id":102666,"date":"2021-12-19T15:37:03","date_gmt":"2021-12-19T13:37:03","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-cache-bench-0-2-0-dlya-issledovaniya-effektivnosti-keshirovaniya-fajlov"},"modified":"2021-12-19T15:37:03","modified_gmt":"2021-12-19T13:37:03","slug":"vypusk-cache-bench-0-2-0-dlya-issledovaniya-effektivnosti-keshirovaniya-fajlov","status":"publish","type":"post","link":"https:\/\/prohoster.info\/de\/blog\/news\/vypusk-cache-bench-0-2-0-dlya-issledovaniya-effektivnosti-keshirovaniya-fajlov","title":{"rendered":"Ver\u00f6ffentlichung von cache-bench 0.2.0 zur Untersuchung der Effizienz von Dateicaching.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Sieben Monate nach der vorherigen Ver\u00f6ffentlichung ist cache-bench 0.2.0 erschienen. Cache-bench \u2014 ein Python-Skript, das es erm\u00f6glicht, den Einfluss von virtuellen Speichereinstellungen (vm.swappiness, vm.watermark_scale_factor, Multigenerational LRU Framework usw.) auf die Leistung von Aufgaben zu bewerten, deren Ausf\u00fchrung von der Zwischenspeicherung von Dateioperationen zum Lesen abh\u00e4ngt, insbesondere unter Speicherknappheit. Der Code ist unter der Lizenz CC0 ver\u00f6ffentlicht.  <\/p>\n<p>  Der Code des Skripts in Version 0.2.0 wurde fast vollst\u00e4ndig neu geschrieben. Anstelle des Lesens von Dateien aus dem angegebenen Verzeichnis (in der neuen Version wurde die Option -d entfernt) wird jetzt aus einer Datei in zuf\u00e4lliger Reihenfolge in den angegebenen Gr\u00f6\u00dfenbl\u00f6cken gelesen.  <\/p>\n<p>  Neue Optionen hinzugef\u00fcgt:  <\/p>\n<ul>\n<li class=\"l\">  &#8212;file &#8212; der Pfad zur Datei, aus der gelesen werden soll.\n<li class=\"l\">  &#8212;chunk &#8212; die Gr\u00f6\u00dfe des Fragments in Kibibytes, standardm\u00e4\u00dfig 64.\n<li class=\"l\">  &#8212;mmap &#8212; aus einem memory-mapped Dateiobjekt lesen, anstatt aus einem Dateideskriptor zu lesen.\n<li class=\"l\">  &#8212;preread &#8212; vor Beginn des Tests die angegebene Datei durch sequentielles Lesen in Fragmenten von 1 MiB vorab lesen (cachen).\n<li class=\"l\">  &#8212;bloat &#8212; die gelesenen Fragmente zur Liste hinzuf\u00fcgen, um den Speicherverbrauch des Prozesses zu erh\u00f6hen und sp\u00e4ter Speicherknappheit zu erzeugen.\n<li class=\"l\">  &#8212;interval &#8212; der Intervall f\u00fcr die Ausgabe (Protokollierung) der Ergebnisse in Sekunden.    <\/ul>\n<p>Quelle: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=56376\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0421\u043f\u0443\u0441\u0442\u044f 7 \u043c\u0435\u0441\u044f\u0446\u0435\u0432 \u043f\u043e\u0441\u043b\u0435 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0435\u0433\u043e \u0440\u0435\u043b\u0438\u0437\u0430 \u0432\u044b\u0448\u0435\u043b cache-bench 0.2.0. Cache-bench &#8212; \u044d\u0442\u043e Python \u0441\u043a\u0440\u0438\u043f\u0442, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0438\u0439 \u043e\u0446\u0435\u043d\u0438\u0442\u044c \u0432\u043b\u0438\u044f\u043d\u0438\u0435 \u043d\u0430\u0441\u0442\u0440\u043e\u0435\u043a \u0432\u0438\u0440\u0442\u0443\u0430\u043b\u044c\u043d\u043e\u0439 \u043f\u0430\u043c\u044f\u0442\u0438 (vm.swappiness, vm.watermark_scale_factor, Multigenerational LRU Framework \u0438 \u043f\u0440\u043e\u0447\u0438\u0445) \u043d\u0430 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c \u0437\u0430\u0434\u0430\u0447, \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u0437\u0430\u0432\u0438\u0441\u0438\u0442 \u043e\u0442 \u043a\u044d\u0448\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0444\u0430\u0439\u043b\u043e\u0432\u044b\u0445 \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u0439 \u0447\u0442\u0435\u043d\u0438\u044f, \u043e\u0441\u043e\u0431\u0435\u043d\u043d\u043e \u0432 \u0443\u0441\u043b\u043e\u0432\u0438\u044f\u0445 \u043d\u0435\u0445\u0432\u0430\u0442\u043a\u0438 \u043f\u0430\u043c\u044f\u0442\u0438. \u041a\u043e\u0434 \u043e\u0442\u043a\u0440\u044b\u0442 \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u0435\u0439 CC0. \u041a\u043e\u0434 \u0441\u043a\u0440\u0438\u043f\u0442\u0430 \u0432 \u0432\u0435\u0440\u0441\u0438\u0438 0.2.0 \u043f\u043e\u0447\u0442\u0438 \u043f\u043e\u043b\u043d\u043e\u0441\u0442\u044c\u044e [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-102666","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One 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