Struggling with efficient query processing in distributed databases? This paper delves into the optimization techniques used in the SDD-1 distributed database system. The study focuses on translating high-level queries into relational calculus forms and efficiently reducing the database to relevant subsets, ultimately enhancing query performance. SDD-1 optimizes queries submitted in Datalanguage by translating each query into a relational calculus form called an envelope, which is essentially an aggregate-free QUEL query. The focus is on optimizing these envelopes through a two-phase process. The first phase executes relational operations to delimit a relevant data subset, called a reduction. The second phase transmits the reduction to one designated site for local execution. The efficient construction of the reduction phase is critical. The authors discuss the semijoin operator and present an algorithm that constructs a cost-effective program of semijoins, given an envelope and a database. This helps in designing operators and algorithms for processing queries against databases.
This paper published in ACM Transactions on Database Systems, fits the journal's emphasis on database management and systems. It describes techniques used to optimize relational queries in a distributed database system. This aligns with the journal's interest in improving database efficiency.