A Modular Design for Geo-Distributed Querying
This work addresses the problem of limited querying capabilities in distributed data stores for applications with diverse needs, though it appears incremental as it builds on existing systems.
The paper tackled the challenge of enabling efficient querying on secondary attributes in distributed storage systems by proposing a modular architecture that allows dynamic adaptation to varying workloads, resulting in a flexible design that supports trade-offs for different use case requirements.
Most distributed storage systems provide limited abilities for querying data by attributes other than their primary keys. Supporting efficient search on secondary attributes is challenging as applications pose varying requirements to query processing systems, and no single system design can be suitable for all needs. In this paper, we show how to overcome these challenges in order to extend distributed data stores to support queries on secondary attributes. We propose a modular architecture that is flexible and allows query processing systems to make trade-offs according to different use case requirements. We describe adap-tive mechanisms that make use of this flexibility to enable query processing systems to dynamically adjust to query and write operation workloads.