Beyond the Data Grid: Coherence, Normalisation, Joins and Linear Scalability (QCon)

Normalisation is, in many ways, the antithesis of typical cache design. We tend to denormalise for speed. Building a data store (rather than a cache) is a little different: Manageability, versioning, bi-temporal reconstitution become more important factors. Normalisation helps solve these problems but normalisation in distributed architectures suffers from problems of distributed joins, requiring iterative network calls.

We’ve developed a mechanism for managing normalisation based on a variant of the Star Schema model used in data warehousing. In our implementation Facts are held distributed (partitioned) in the data nodes and Dimensions are replicated throughout the query-processing nodes. To save space we track ‘used’, or as we term them ‘connected’ data, to ensure only useful objects are replicated.

This model was presented at the QCon 2011 and at the Coherence SIG.

You can find the slides here (Powerpoint – 7MB).

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