This is an excerpt from the Accelerating Data Analytics on Ceph Object Storage with Alluxio whitepaper. In addition to the reference architecture in this blog, the whitepaper provides a detailed implementation guide to reproduce the environment.
As the volume of data collected by enterprises has grown, there is a continual need to find efficient storage solutions. Owing to its simplicity, scalability and cost-efficiency object storage, including Ceph, has increasingly become a popular alternative to traditional file systems. In most cases, the object storage system, on-premise or in the cloud, is decoupled from compute nodes where analytics is run. There are several benefits of this separation.
- Improved cost efficiency: Storage capacity and compute power can be provisioned independently. This simplifies capacity planning and ensures better resource utilization.
- Ease of manageability: A separation of data from compute means that a single storage platform can be shared by different compute clusters. For example, a cluster hosting long-running services emitting data into object storage may run in conjunction with a data processing cluster to derive insights.
However, a consequence of this architecture is that data is remote to the compute nodes. When running analytics directly on the object store, data is repeatedly fetched from the storage nodes leading to reduced performance. This delay may prevent critical insights from being extracted in a timely manner.
This is addressed by deploying Alluxio on compute nodes, allowing fast ad-hoc analysis of data by bringing performance up to memory speeds with intelligent storage of active archive data close to computation.
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