La soci\u00e9t\u00e9 Google a pr\u00e9sent\u00e9 un nouveau langage d\u00e9claratif de programmation logique, Logica, con\u00e7u pour manipuler des donn\u00e9es et traduisant des programmes en SQL. Ce nouveau langage s'adresse \u00e0 ceux qui souhaitent utiliser la syntaxe de la programmation logique lors de l'\u00e9criture de requ\u00eates \u00e0 une base de donn\u00e9es. Actuellement, le code SQL g\u00e9n\u00e9r\u00e9 peut \u00eatre ex\u00e9cut\u00e9 dans l'entrep\u00f4t Google BigQuery ou dans les bases de donn\u00e9es PostgreSQL et SQLite, dont le support est encore exp\u00e9rimental. \u00c0 l'avenir, il est pr\u00e9vu d'\u00e9largir le nombre de dialectes SQL pris en charge. Le code du projet est \u00e9crit en Python et publi\u00e9 sous la licence Apache 2.0. <\/p>\n
Logica continue le d\u00e9veloppement d'un autre langage de traitement de donn\u00e9es d\u00e9velopp\u00e9 par Google, Yedalog, et offre un niveau d'abstraction qui n'est pas disponible dans SQL standard. Les requ\u00eates dans Logica sont programm\u00e9es sous la forme d'un ensemble d'assertions logiques. Des modules, des op\u00e9rations d'importation et la possibilit\u00e9 d'utiliser Logica depuis l'interface interactive Jupyter Notebook sont support\u00e9s. Par exemple, pour g\u00e9n\u00e9rer un r\u00e9sum\u00e9 des personnes le plus souvent mentionn\u00e9es dans les nouvelles de l'ann\u00e9e 2020, on peut utiliser le programme suivant \u00e9crit en Logica pour interroger la base de donn\u00e9es GDELT : @OrderBy(Mentions, \u00abmentions desc\u00bb); @Limit(Mentions, 10); Mentions(person:, mentions? += 1) distinct :- gdelt-bq.gdeltv2.gkg(persons:, date:), Substr(ToString(date), 0, 4) == \u00ab2020\u00bb, the_persons == Split(persons, \u00ab;\u00bb), person in the_persons; $ logica mentions.l run Mentions +------+-+-+ | person | mentions_count | +------+-+ | donald trump | 3077130 | | los angeles | 1078412 | | joe biden | 1054827 | | george floyd | 872919 | | boris johnson | 674786 | | barack obama | 438181 | | vladimir putin | 410587 | | bernie sanders | 387383 | | andrew cuomo | 345462 | | las vegas | 325487 | +------+-+-+ <\/p>\n
L'\u00e9criture de requ\u00eates SQL complexes conduit \u00e0 la n\u00e9cessit\u00e9 d'\u00e9crire des cha\u00eenes multiline encombrantes, peu \u00e9videntes \u00e0 percevoir, qui nuisent \u00e0 la r\u00e9utilisation des parties de la requ\u00eate et compliquent la maintenance. Pour des calculs r\u00e9p\u00e9t\u00e9s typiques en SQL, on peut utiliser des vues et des fonctions, mais ils ne prennent pas en charge les op\u00e9rations d'importation et ne fournissent pas la flexibilit\u00e9 caract\u00e9ristique des langages de haut niveau (par exemple, il est impossible de passer une fonction \u00e0 une autre). Logica permet de composer des programmes \u00e0 partir de petits blocs logiques, compr\u00e9hensibles et accessibles \u00e0 la r\u00e9utilisation, qui peuvent \u00eatre test\u00e9s, li\u00e9s \u00e0 des noms sp\u00e9cifiques et regroup\u00e9s en paquets disponibles pour une utilisation dans d'autres projets. \u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Google \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b\u0430 \u043d\u043e\u0432\u044b\u0439 \u0434\u0435\u043a\u043b\u0430\u0440\u0430\u0442\u0438\u0432\u043d\u044b\u0439 \u044f\u0437\u044b\u043a \u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f Logica, \u043f\u0440\u0435\u0434\u043d\u0430\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044b\u0439 \u0434\u043b\u044f \u043c\u0430\u043d\u0438\u043f\u0443\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0434\u0430\u043d\u043d\u044b\u043c\u0438 \u0438 \u0442\u0440\u0430\u043d\u0441\u043b\u0438\u0440\u0443\u044e\u0449\u0438\u0439 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u044b \u0432 \u044f\u0437\u044b\u043a SQL. \u041d\u043e\u0432\u044b\u0439 \u044f\u0437\u044b\u043a \u043e\u0440\u0438\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d \u043d\u0430 \u0442\u0435\u0445, \u043a\u0442\u043e \u0445\u043e\u0447\u0435\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043f\u0440\u0438 \u043d\u0430\u043f\u0438\u0441\u0430\u043d\u0438\u0438 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u043a \u0411\u0414. \u0412 \u043d\u0430\u0441\u0442\u043e\u044f\u0449\u0435\u0435 \u0432\u0440\u0435\u043c\u044f \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0438\u0440\u0443\u044e\u0449\u0438\u0439 SQL-\u043a\u043e\u0434 \u043c\u043e\u0436\u0435\u0442 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c\u0441\u044f \u0432 \u0445\u0440\u0430\u043d\u0438\u043b\u0438\u0449\u0435 Google BigQuery \u0438\u043b\u0438 \u0432 \u0421\u0423\u0411\u0414 PostgreSQL \u0438 SQLite, \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u043a\u0430 \u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u043f\u043e\u043a\u0430 […]<\/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-99711","post","type-post","status-publish","format-standard","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\udd47Google a publi\u00e9 le langage 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Source : opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"