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AtScale > 实例探究 > Rakuten Accelerates Query Performance and Modernizes Analytics Program with AtScale
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Rakuten Accelerates Query Performance and Modernizes Analytics Program with AtScale

技术
  • 分析与建模 - 大数据分析
  • 基础设施即服务 (IaaS) - 云计算
适用行业
  • 电子商务
  • 零售
适用功能
  • 商业运营
  • 离散制造
用例
  • 库存管理
  • 预测性维护
  • 供应链可见性(SCV)
服务
  • 云规划/设计/实施服务
  • 数据科学服务
挑战
Rakuten, a shopping rewards company, had moved from their initial SQL database in 2014 to an AtScale-powered Hadoop solution in 2018. However, this wasn’t sufficient and they soon began to experience a resource crunch based on the sheer size of their database. Rakuten's existing architecture meant that business users didn't have the computing resources necessary to work with large datasets. This led to competition between business units for hard disk access, memory, and CPU time. The internal team was frustrated with the competition for resources, and the operational overhead and associated hardware and electricity costs also meant the solution was no longer cost-efficient. That, coupled with the continuous processing demands on storage infrastructure, forced Rakuten to consider new solutions for their data needs. They knew they needed more processing capability and flexibility to continue serving their customers effectively.
关于客户
Rakuten is a shopping rewards company that leverages data on shopper behavior, pricing, and commissions to create compelling offers for their customers, who receive cash-back incentives from Rakuten. With over 13 million e-commerce customers and partnerships with 70+ businesses, Rakuten depends on sophisticated analytics and data management to maintain a differentiated offering in the highly competitive e-commerce industry. While Rakuten originally consolidated data from multiple siloed systems to a single, on-premises data lake built on Hadoop in 2016, they still faced challenges related to maintaining the environment. The sheer electrical costs of hosting their own internal server farm as well as the expensive hardware required presented obstacles for this fast-growing operation.
解决方案
AtScale helped Rakuten transition their analytics to the cloud while still retaining all the analytical capabilities they had built, enabling them to deliver consistency for their team. AtScale insulated their Tableau-based reports and dashboards from changes in underlying raw data. While location and schemas changed, the AtScale model was untouched, allowing them to preserve their investment. Once they had moved their data to Snowflake, AtScale was able to help Rakuten better optimize their costs by right-sizing cloud resource consumption based on real-time usage. AtScale also helped smooth out and mitigate user concurrency challenges without requiring additional compute resources and leveraged intelligent aggregates to accelerate query performance while keeping cloud costs down.
运营影响
  • By moving from an on-premises Hadoop data warehouse to Snowflake’s elastic, scalable resource model, Rakuten gained additional computing power. This enabled them to maintain responsiveness to queries during peak demand periods, while only paying for what they used.
  • Now Rakuten can maintain flexibility to compensate for crunches, without paying excessively for operational or server overhead.
  • Because AtScale allowed Rakuten to move from Hadoop to Snowflake seamlessly, the team can now access their data faster and with more consistency.
数量效益
  • As high-demand queries were shifted to Snowflake, there was an immediate 30% drop in load on the on-premises computing cluster.
  • Rakuten ran a test of 10 terabytes of data with and without AtScale and discovered that AtScale ran the process 14x faster and at 4x less cost.

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