Finding a good join order is crucial for query performance. In this paper, we introduce the
Join Order Benchmark (JOB) and experimentally revisit the main components in the classic …

Cost and cardinality estimation is vital to query optimizer, which can guide the plan
selection. However traditional empirical cost and cardinality estimation techniques cannot …

Query optimizer is at the heart of the database systems. Cost-based optimizer studied in this
paper is adopted in almost all current database systems. A cost-based optimizer introduces …

Finding a good join order is crucial for query performance. In this paper, we introduce the
Join Order Benchmark that works on real-life data riddled with correlations and introduces …

Query performance prediction is vital to many database tasks (eg, database monitoring and
query scheduling). Existing methods focus on predicting the performance for a single query …

The physical data layout significantly impacts performance when database systems access
cold data. In addition to the traditional row store and column store designs, recent research …

Reusing intermediates in databases to speed-up analytical query processing was studied in
prior work. Existing solutions require intermediate results of individual operators to be …

Selecting appropriate distributed join methods for logical join operations in a query plan is
crucial for the performance of data-intensive scalable computing (DISC). Different network …

Database architectures typically process queries one at a time, executing concurrent queries
in independent execution contexts. Often, such a design leads to unpredictable performance …

In-memory join is an essential operator in any database engine. It has been extensively
investigated in the database literature. In this paper, we study whether exploiting the CDF …