Extending RDBMSs To Support Sparse Datasets Using An Interpreted Attribute Storage Format
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
The case for a wide-table approach to manage sparse relational data sets
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Multi-tenant databases for software as a service: schema-mapping techniques
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Supporting Database Applications as a Service
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
A comparison of flexible schemas for software as a service
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
The design of the force.com multitenant internet application development platform
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Efficient B-tree based indexing for cloud data processing
Proceedings of the VLDB Endowment
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For SaaS applications which multiple tenants share sparse tables, fields of varying data types are stored in one flex column based on customization. Thus it is not practical to create native physical indices for tenants. In this paper, we put forward an indexing model for sparse table storage model based on pivot tables in multi-node environments. The core idea is copying field data to be indexed to another table and creating physical indices in that table. This model supports customization and isolation characteristics of multitenant applications, and provides load balance means in index subsystem, and controls the number of index data tables thus memory consuming reasonably.