{"id":36843,"date":"2019-10-31T22:14:11","date_gmt":"2019-10-31T19:14:11","guid":{"rendered":"https:\/\/prohoster.info\/blog\/otkryt-kod-sql-dvizhka-blazingsql-ispolzuyushhego-gpu-dlya-uskoreniya\/"},"modified":"2019-10-31T22:14:11","modified_gmt":"2019-10-31T19:14:11","slug":"otkryt-kod-sql-dvizhka-blazingsql-ispolzuyushhego-gpu-dlya-uskoreniya","status":"publish","type":"post","link":"https:\/\/prohoster.info\/pl\/blog\/news\/otkryt-kod-sql-dvizhka-blazingsql-ispolzuyushhego-gpu-dlya-uskoreniya","title":{"rendered":"Otworzono kod SQL-silnika BlazingSQL, wykorzystuj\u0105cego GPU do przyspieszenia","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Og\u0142oszono<\/a><\/noindex> o otwarciu kod\u00f3w \u017ar\u00f3d\u0142owych silnika SQL BlazingSQL<\/a><\/noindex>, wykorzystuj\u0105cego GPU do przyspieszania przetwarzania danych. BlazingSQL nie jest pe\u0142noprawn\u0105 baz\u0105 danych, lecz jest pozycjonowany jako silnik do analizy i przetwarzania du\u017cych zbior\u00f3w danych, por\u00f3wnywalny w swoich zadaniach z Apache Spark<\/a><\/noindex>. Kod jest napisany w j\u0119zyku Python i otwarty<\/a><\/noindex> na licencji Apache 2.0. <\/p>\n

BlazingSQL nadaje si\u0119 do wykonywania pojedynczych zapyta\u0144 analitycznych na du\u017cych zbiorach danych (dziesi\u0105tki gigabajt\u00f3w), przechowywanych w formatach tabelarycznych (np. logi, statystyki NetFlow itd.). BlazingSQL mo\u017ce wykonywa\u0107 zapytania z plik\u00f3w raw w formatach CSV i Apache Parquet, umieszczonych w sieciowych i chmurowych systemach plik\u00f3w, takich jak HDSF i AWS S3, bezpo\u015brednio przesy\u0142aj\u0105c wyniki do pami\u0119ci GPU. Dzi\u0119ki r\u00f3wnoleg\u0142emu wykonywaniu operacji na GPU oraz u\u017cywaniu szybszej pami\u0119ci wideo, zapytania w BlazingSQL s\u0105 realizowane nawet do 20 razy<\/a><\/noindex> szybciej ni\u017c w Apache Spark.<\/p>\n

\"Otworzono<\/a><\/noindex><\/center><\/p>\n

Do pracy z GPU wykorzystywany jest rozwijany przy wsp\u00f3\u0142pracy z firm\u0105 NVIDIA zbi\u00f3r otwartych<\/a><\/noindex> bibliotek RAPIDS<\/a><\/noindex>, kt\u00f3ry umo\u017cliwia tworzenie aplikacji do przetwarzania danych i analityki, wykonywanych ca\u0142kowicie po stronie GPU (zapewniany jest interfejs Pythona<\/a><\/noindex> do korzystania z niskopoziomowych prymityw\u00f3w CUDA oraz r\u00f3wnoleg\u0142ego przetwarzania oblicze\u0144). <\/p>\n

BlazingSQL udost\u0119pnia mo\u017cliwo\u015b\u0107 korzystania z SQL zamiast API przetwarzania danych cuUDF<\/a><\/noindex> (opartego na Apache Arrow<\/a><\/noindex>), stosowanego w RAPIDS. BlazingSQL jest dodatkow\u0105 warstw\u0105, dzia\u0142aj\u0105c\u0105 na powierzchni cuDF i wykorzystuj\u0105c\u0105 bibliotek\u0119 cuIO do odczytu danych z dysku. Zapytania SQL s\u0105 transliterowane do wywo\u0142a\u0144 funkcji cuUDF, co pozwala na za\u0142adowanie danych do GPU oraz wykonywanie operacji \u0142\u0105czenia, agregacji i filtrowania. Wspierane jest tworzenie rozproszonych konfiguracji, obejmuj\u0105cych tysi\u0105ce GPU. <\/p>\n

BlazingSQL znacznie upraszcza prac\u0119 z danymi \u2014 zamiast setek wywo\u0142a\u0144 funkcji cuDF mo\u017cna ograniczy\u0107 si\u0119 do jednego zapytania SQL. Zastosowanie SQL umo\u017cliwia integracj\u0119 RAPIDS z istniej\u0105cymi systemami analitycznymi, bez konieczno\u015bci pisania specyficznych uchwyt\u00f3w i bez potrzeby po\u015bredniego za\u0142adunku danych do dodatkowej bazy danych, ale
\nprzy zachowaniu pe\u0142nej kompatybilno\u015bci ze wszystkimi elementami RAPIDS, transliteruj\u0105c istniej\u0105c\u0105 funkcjonalno\u015b\u0107 do SQL i zapewniaj\u0105c wydajno\u015b\u0107 na poziomie cuDF. W tym zapewniona jest integracja z bibliotekami XGBoost<\/a><\/noindex> i cuML<\/a><\/noindex> do rozwi\u0105zywania problem\u00f3w analitycznych i uczenia maszynowego. <\/p>\n

<\/a><\/noindex><\/p>\n

\u0179r\u00f3d\u0142o: opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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BlazingSQL \u043d\u0435 \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043f\u043e\u043b\u043d\u043e\u0446\u0435\u043d\u043d\u043e\u0439 \u0421\u0423\u0411\u0414, \u0430 \u043f\u043e\u0437\u0438\u0446\u0438\u043e\u043d\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u043a\u0430\u043a \u0434\u0432\u0438\u0436\u043e\u043a \u0434\u043b\u044f \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u0438 \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u043d\u0430\u0431\u043e\u0440\u043e\u0432 \u0434\u0430\u043d\u043d\u044b\u0445, \u0441\u0440\u0430\u0432\u043d\u0438\u043c\u044b\u0439 \u043f\u043e \u0441\u0432\u043e\u0438\u043c \u0437\u0430\u0434\u0430\u0447\u0430\u043c \u0441 Apache Spark. \u041a\u043e\u0434 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Python \u0438 \u043e\u0442\u043a\u0440\u044b\u0442 \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u0435\u0439 Apache 2.0. BlazingSQL \u043f\u043e\u0434\u0445\u043e\u0434\u0438\u0442 \u0434\u043b\u044f \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u0435\u0434\u0438\u043d\u0438\u0447\u043d\u044b\u0445 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u043d\u0430\u0434 […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":27603,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-36843","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Otwarty kod SQL silnika BlazingSQL, kt\u00f3ry wykorzystuje GPU 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