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Eden Chmielewski

Publications and source records attributed to Eden Chmielewski.

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The Role of Semirings in Incremental View Maintenance

We study the problem of incremental view maintenance (IVM) under inserts to semiring-annotated databases. The key observation put forward in this paper is that the complexity of the IVM problem depends fundamentally on the underlying semiring. We introduce a class of conjunctive queries called p-hierarchical. For a zero-sum free and zero-divisor free commutative semiring $K$, we show that for any p-hierarchical query with fractional hypertree width fhtw and any insert-only update sequence of length N to an initially empty K-database, we can construct a data structure that can be updated in O(N^{fhtw-1}) amortized time and supports the enumeration of the query result with constant delay. In particular, the amortized update time for any p-hierarchical alpha-acyclic query is constant. For a class of semirings used to model a wide range of computational problems, we give conditional lower bounds showing that any conjunctive query without self-joins that is not p-hierarchical cannot be maintained with constant amortized update time and constant enumeration delay under inserts. This class includes the natural semiring and its generalizations to the provenance and covariance semirings, as well as idempotent and strictly ordered semirings such as the tropical semiring. When put together, our upper and lower bounds imply a dichotomy for the insert-only maintenance of conjunctive queries without self-joins over every semiring in our class: such a query can be maintained with constant amortized update time and constant enumeration delay if and only if it is p-hierarchical alpha-acyclic.

cs.DB

Maintaining Queries under Updates Using Heavy-Light Partitioning of the Input Relations

We study the classical incremental view maintenance problem: Given a query and a database, maintain the query output under single-tuple updates (inserts or deletes) to the database such that the tuples in the query output can be enumerated with constant delay after any update. We introduce a maintenance approach whose update time matches or improves the best update time reported in prior work. Whereas prior approaches are manually tailored to each of a handful of queries, our approach generalizes to arbitrary join queries. It combines three techniques: delta queries, trees of materialized views, and heavy-light data partitioning. The overall update time incurred by our approach for a given join query is characterized by the maintenance width, a new measure that is parameterized by the heavy-light threshold for data partitioning. We show how to find the threshold that minimizes the maintenance width.

cs.DB