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Join is arguably the most costly and frequently used operation in relational query processing. Join algorithms usually spend the majority of their time on scanning and attempting to join the parts of the base relations that do not satisfy the join ...

Determining the degree of parallelism (DOP) for query execution is of great importance to both performance and resource provisioning. However, recent work that applies machine learning (ML) to query optimization and query performance prediction in ...

The order in which relations are joined and the physical join operators used are two aspects of query plans which have a significant impact on the execution latency of join queries. However, the set of valid query plans grows exponentially with the ...

Cardinality estimation is a high-profile technique in database management systems with a serious impact on query performance. Thus, a lot of traditional approaches such as histograms-based or sampling-based methods have been developed over the last ...

Recent research has shown that learned models can outperform state-of-the-art index structures in size and lookup performance. While this is a very promising result, existing learned structures are often cumbersome to implement and are slow to build. In ...

Data partitioning plays a critical role in data stream processing. Current data partitioning techniques use simple, static heuristics that do not incorporate feedback about the quality of the partitioning decision (i.e., fire and forget strategy). Hence,...