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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hui Liu Shengqi Wu |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Mechanical Engineering, Shandong University, Jinan, China School of Computer Science and Technology, Shandong University, Jinan, China (Hui Liu; Shengqi Wu) |
| Abstract | SaaS has become a typical cloud computing delivery model. In sparse table, one of the most popular multi-tenant data storage schemas for SaaS, all tenants' data are stored into sparse table and mapped to tenant's logical view by metadata. During the data storage schema upgrade in SaaS, all tenants' data need to be migrated into the new data schema before it becomes effective to ensure the integrity of the tenants' data. However, the migration is complex and brings overhead workload. Worse still, it may cause the system unusable. In this paper, we propose metadata evolution technology. We can realize the mapping from the old data schema to new data schema smoothly via metadata evolution during schema upgrade. So the schema upgrade can be completed without data migration. |
| Starting Page | 3148 |
| Ending Page | 3151 |
| File Size | 316519 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457714146 |
| e-ISBN | 9781457714153 |
| DOI | 10.1109/CECNet.2012.6201658 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-04-21 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decision support systems Data migration Databases Metadata evolution Memory Schema upgrade SaaS Educational institutions Software Data models Engines |
| Content Type | Text |
| Resource Type | Article |
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