Does the semijoin strategy reduce network traffic in distributed join processing?

Introduction / Context:Network bandwidth is a scarce resource in distributed databases. The semijoin technique is a classic optimization to reduce transferred data during joins.

Given Data / Assumptions:

• Relations to be joined reside on different sites.
• Join selectivity allows filtering large fractions of non-matching rows.
• Join keys can be exchanged at low cost compared to full rows.

Concept / Approach:A semijoin sends projected join keys first, enabling the remote site to eliminate non-matching rows, and then returns only necessary tuples, reducing bytes on the wire.

Step-by-Step Solution:Project join attribute(s) at the initiating site.Send keys to the remote site.Filter and return only matching tuples.Complete the final join locally with reduced data volume.

Verification / Alternative check:Cost-based optimizers consider semijoins when the key set is much smaller than the base relation sizes.

Why Other Options Are Wrong:Semijoins do not require replication, outer joins, or specific schemas; they address transmission cost broadly.

Common Pitfalls:Using semijoins when the key set is large can negate benefits due to extra passes.

Final Answer:Applies — semijoins are used specifically to cut data shipping