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qdrant-scaling-data-volume

@qdrant · 收录于 1 周前 · 上游提交 昨天★ 社区精选

Guides Qdrant data volume scaling decisions. Use when someone asks 'data doesn't fit on one node', 'too much data', 'need more storage', 'vertical or horizontal scaling', 'tenant scaling', 'time window rotation', or 'data growth exceeds capacity'.

适合你,如果 Qdrant 数据量超出单节点容量,需要规划扩容方案。

/ 通过 npx 安装 校验哈希
npx oh-my-skill add qdrant/skills/qdrant-scaling-data-volume
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- qdrant/skills/qdrant-scaling-data-volume
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify qdrant/skills/qdrant-scaling-data-volume
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

技能原文 SKILL.md作者撰写 · Apache-2.0 · 5ea598d

Scaling Data Volume

This document covers data volume scaling scenarios, where the total size of the dataset exceeds the capacity of a single node.

Tenant Scaling

If the use case is multi-tenant, meaning that each user only has access to a subset of the data, and we never need to query across all the data, then we can use multi-tenancy patterns to scale.

The recommended way is to use multi-tenant workloads with payload partitioning, per-tenant indexes, and tiered multitenancy.

Learn more [Tenant Scaling](tenant-scaling/SKILL.md)

Sliding Time Window

Some use-cases are based on a sliding time window, where only the most recent data is relevant. For example an index for social media posts, where only the last 6 months of data require fast search.

Learn more [Sliding Time Window](sliding-time-window/SKILL.md)

Global Search

Most general use-cases require global search across all data. In these situations, we might need to fall back to vertical scaling, and then horizontal scaling when we reach the limits of vertical scaling.

Vertical Scaling

When data doesn't fit in a single node, the first approach is to scale the node itself — more RAM, better disk, quantization, mmap. Exhaust vertical options before going horizontal, as horizontal scaling adds permanent operational complexity.

Learn more [Vertical Scaling](vertical-scaling/SKILL.md)

Horizontal Scaling

When a single node can't hold the data even with quantization and mmap, distribute data across multiple nodes via sharding.

Learn more [Horizontal Scaling](horizontal-scaling/SKILL.md)

按 Apache-2.0 许可原样转载,未经改动 · 在 GitHub 查看 →

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