Knob tuning plays an important role in database optimization, which tunes knob settings to
optimize the database performance or improve resource utilization. However, there are …

Indexes are vital to enhance the lookup on single or multiple columns, and building proper
indexes can significantly improve the database performance. Existing works focus on adding …

When there is a need to make an ultimate decision about the unique features of big data
platforms, one should note that they have configurable parameters. Apache Spark is an …

Data processing engines increasingly leverage distributed file systems for scalable, cost-
effective storage. While the Apache Parquet columnar format has become a popular choice …

Hyperparameter tuning is an essential task in automatic machine learning and big data
management. To accelerate tuning, many recent studies focus on augmenting BO, the …

Abstract Big Data Cyber Security Analytics (BDCA) systems leverage big data technologies
to collect, store, and analyze a large volume of security event data for detecting cyber …

To support different application scenarios, big data frameworks usually provide a large
number of performance-related configuration parameters. Online auto-tuning these …

Faced with the challenges of big data, modern cloud database management systems are
designed to efficiently store, organize, and retrieve data, supporting optimal performance …

SyDPaCC (Systematic Development of programs for Parallel and Cloud Computing) is a
framework for the Coq interactive theorem prover. It allows to systematically develop correct …

Big data processing frameworks such as Spark usually provide a large number of
performance-related configuration parameters, how to auto-tune these parameters for a …