2
J'expérimente avec Kyoto Cabinet HashDB. Ma base de données atteindra la taille de 110 To. Les clés sont 20 octets et les valeurs sont 128 Ko. J'essaie d'insérer environ 500 millions de dossiers. Voici la meilleure performance que j'ai eue jusqu'à présent:Kyoto Cabinet HashDB inserts ne sont pas O (1)
Le temps est en secondes. 'n' est le nombre de 10000 entrées entrées. Par exemple 1 10000 enregistrements ont pris 1 seconde. 5e 10000 enregistrements ont pris 5 secondes et ainsi de suite. Comme vous pouvez le voir, la performance commence à se dégrader après environ 2 millions d'entrées. J'ai créé la base de données avec le nombre de seau fixé à 7 milliards, et tout le reste est par défaut. J'utilise la bibliothèque C/C++, et la définition de la capacité de la carte mémoire à 30 Go (j'ai 32 Go de RAM) en utilisant db.tune_map(30LL << 30);.
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Y a-t-il un moyen de maintenir la performance à environ 9-10 secondes par 10000 enregistrements?
Est-ce que KC garde les clés dans la mémoire? Ou est-ce qu'il les récupère du disque pour chaque écriture? Je ne vois aucune documentation mentionnant cela pour HashDB, bien qu'ils le mentionnent pour l'arbre B +. –
L'utilisation totale de la RAM du système est d'environ 1,8 Go, sur laquelle le processus KC utilise environ 1,2 Go. Donc, je suppose que l'index n'est pas conservé dans la RAM. Est-ce vrai? Comment puis-je le forcer à conserver l'index dans la RAM? –
Veuillez consulter la section "Mise en œuvre efficace de la base de données de hachage" dans le manuel. C'est une bonne idée d'ajuster la taille mmap, au moins dans tokyocabinet. – Sven