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Evolutionary Tree-Structured Storage : Concepts, Interfaces, and Applications

Evolutionary Tree-Structured Storage : Concepts, Interfaces, and Applications

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KRAMIS, Marc Yves Maria, 2014. Evolutionary Tree-Structured Storage : Concepts, Interfaces, and Applications [Dissertation]. Konstanz: University of Konstanz

@phdthesis{Kramis2014Evolu-27695, title={Evolutionary Tree-Structured Storage : Concepts, Interfaces, and Applications}, year={2014}, author={Kramis, Marc Yves Maria}, address={Konstanz}, school={Universität Konstanz} }

Evolutionary Tree-Structured Storage : Concepts, Interfaces, and Applications Kramis, Marc Yves Maria 2014 Life is subdued to constant evolution. So is our data, be it in research, business or personal information management. From a natural, evolutionary perspective, our data evolves through a sequence of fine-granular modifications resulting in myriads of states, each describing our data at a given point in time. From a technical, anti-evolutionary perspective, mainly driven by technological and financial limitations, we treat the modifications as transient commands and only store the latest state of our data.<br /><br /><br /><br />It is surprising that the current approach is to ignore the natural evolution and to willfully forget about the sequence of modifications and therefore the past state. Sticking to this approach causes all kinds of confusion, complexity, and performance issues. Confusion, because we still somehow want to retrieve past state but are not sure how. Complexity, because we must repeatedly work around our own obsolete approaches. Performance issues, because confusion times complexity hurts. It is not surprising, however, that intelligence agencies notoriously try to collect, store, and analyze what the broad public willfully forgets.<br /><br /><br /><br />Significantly faster and cheaper random-access storage is the key driver for a paradigm shift towards remembering the sequence of modifications. We claim that (1) faster storage allows to efficiently and cleverly handle finer-granular modifications and (2) that mandatory versioning elegantly exposes past state, radically simplifies the applications, and effectively lays a solid foundation for backing up, distributing and scaling of our data. This work shows, using the example of tree-structured XML, that the characteristics and advantages of the evolutionary approach have been recognized and consistently implemented - something, which on its own is an important achievement.<br /><br /><br /><br />We present the concepts of our evolutionary tree-structured storage TreeTank and the general-purpose SlidingSnapshot to prove that (3) formerly modification-averse tree encodings can be maintained with logarithmic update complexity, (4) linear read scalability beyond memory limitations is still guaranteed while maintaining logarithmic update characteristics, (5) secure copy-on-write semantics can be extended from the file level to the much finer-granular node level, (6) versioned node-level access is predictable and even realtime-capable, and, that (7) node-level snapshots are as or even more space efficient than page-level or file-level snapshots. In the course of our work, we inspired the Java-based iSCSI implementation jSCSI which proved that (8) high-level language block access is fast and also established the Java benchmark framework PERFIDIX as well as the block touch visualization tool VISIDEFIX.<br /><br /><br /><br />We extend REST, the cornerstone interface of the web, with the ability to access the full version and modification history of a resource and call it (9) Temporal REST. This interface will not only encourage application developers to make use of our evolutionary approach, but it will also foster interactive and collaborative applications because they are, according to our claim (10), less complex to write and performing so well that users can now interactively work with large-scale data.<br /><br /><br /><br />Finally, we provide an outlook on how evolutionary (full-text) indices, applications, and schemas can greatly leverage our contributions and how special-purpose hardware can speed-up our tree-structured storage while using far less energy. Especially our suggested approach to schema handling and evolution has the potential to radically simplify ORM-based software development. 2014-05-05T05:48:47Z terms-of-use Kramis, Marc Yves Maria 2014-05-05T05:48:47Z eng

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