Examining extended and scientific metadata for scalable index designs
Proceedings of the 6th International Systems and Storage Conference
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With the amount of data increasing at an alarming rate, domain-specific user-level metadata management systems have emerged in several application areas to compensate for the shortcomings of file systems. Such systems provide domain-specific storage formats for performance-optimized metadata storage, search-based access interfaces for enabling declarative queries, and type-specific indexing structures for performing scalable search over metadata. In this paper, we highlight several issues that plague these user-level systems. We then show how integrating metadata management into the Loris stack solves all these problems by design. In doing so, we show how the Loris stack provides a modular framework for implementing domain-specific solutions by presenting the design of our own Loris-based metadata management system that provides 1) LSM-tree-based metadata storage, 2) an indexing infrastructure that uses LSM-trees for maintaining real-time attribute indices, and 3) scalable metadata querying using an attribute-based query language.