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HIFI's Transition from BigQuery to ClickHouse for Enhanced Music Royalty Data Management
技术
- 应用基础设施与中间件 - 数据库管理和存储
- 应用基础设施与中间件 - 中间件、SDK 和库
适用行业
- 建筑物
- 水泥
适用功能
- 采购
用例
- 库存管理
- 零售店自动化
服务
- 云规划/设计/实施服务
- 系统集成
挑战
HIFI 是一家为音乐创作者提供财务和商业见解的公司，其数据管理系统面临着挑战。该公司吸收了大量的版税数据，单个 HIFI Enterprise 帐户拥有超过 0.5 GB 的相关版税数据，代表超过 2500 万行流媒体和其他交易数据。该数据需要在客户登录后立即加载到用户界面中，并且可以有多个客户同时登录。此前，加载数据可能需要长达 30 秒的时间，有时会因超时而根本无法加载。 HIFI 使用 Google Cloud 的 BigQuery (BQ) 来存储版税数据，但 BQ 的定价结构是一个重大挑战。它阻碍了数据的使用，并与 HIFI 的数据驱动价值观相矛盾。谷歌提前购买 BQ 插槽的解决方案对于 HIFI 作为初创公司来说并不可行，因为使用模式可能每周都会发生巨大变化。
关于客户
HIFI 是一家致力于构建创新技术的公司，旨在为其会员（主要是音乐创作者）提供重要的财务和业务见解。该公司提供了一款名为 HIFI Enterprise 的产品，可为大规模处理音乐版税数据的复杂企业带来智能收入处理。这包括获得音乐版权的公司和基金以及与世界上最著名的艺术家合作的业务经理。 HIFI 吸收大量版税数据，单个 HIFI Enterprise 帐户拥有超过 0.5 GB 的相关版税数据，代表超过 2500 万行流媒体和其他交易数据。该公司得到了全球顶级风投和排行榜冠军创作者的支持。
解决方案
HIFI 决定改用 ClickHouse，这是一种快速开源的面向列的数据库管理系统，允许使用 SQL 查询实时生成分析数据报告。 ClickHouse 的性能超过了所有其他面向列的数据库管理系统，每台服务器每秒处理数十亿行和数十 GB 数据。使用 ClickHouse，即使是最大的数据集也可以在几秒钟内加载，从而显着改善用户体验。 ClickHouse 还被证明有助于计算内部指标，例如系统中的总版税和去年支付的总版税等指标。然而，ClickHouse 的速度也带来了一些意外，比如连接之类的操作没有按预期工作。为了克服这个问题，HIFI 使用 JOIN 引擎表来更有效地更新记录。 HIFI 还将 ClickHouse 连接到 PostgreSQL 数据库，以获取非版税数据，例如客户帐户数据和元数据。
运营影响
数量效益
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