Non-relational Parallel Database Machines

While open research issues remain in the area of parallel database machines for relational
database systems, building a highly parallel database machine for an object-oriented database
system presents a number of new challenges. One of the first issues to resolve is how declustering
should be handled. For example, should one decluster all sets (such as set-valued attributes of a
complex object) or just top-level sets? Another question is how should inter-object references be
handled. In a relational database machine, such references are handled by doing a join between the
two relations of interest, but in an object-oriented DBMS references are generally handled via
pointers. In particular, a tension exists between declustering a set in order to parallelize scan
operations on that set and clustering an object and the objects it references in order to reduce the
number of disk accesses necessary to access the components of a complex object. Since clustering
in a standard object-oriented database system remains an open research issue, mixing in
declustering makes the problem even more challenging.

Another open area is parallel query processing in an OODBMS. Most OODBMS provide a
relational-like query language based on an extension to relational algebra. While it is possible to
parallelize these operators, how should class-specific methods be handled? If the method operates
on a single object it is certainly not worthwhile parallelizing it However, if the method operates on
a set of values or objects that are declustered, then it almost must be parallelized if one is going to
avoid moving all the data referenced to a single processor for execution. Since it is, at this point in
time, impossible to parallelize arbitrary method code, one possible solution might be to insist that
if a method is to be parallelized that it be constructed using the primitives from the underlying
algebra, perhaps embedded in a normal programming language.


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