This paper evaluates the suitability of Apache Arrow, Parquet, and ORC as formats for
subsumption in an analytical DBMS. We systematically identify and explore the high-level …

Performance variability has been acknowledged as a problem for over a decade by cloud
practitioners and performance engineers. Yet, our survey of top systems conferences …

Columnar storage is a core component of a modern data analytics system. Although many
database management systems (DBMSs) have proprietary storage formats, most provide …

In-network processing, where data is processed by special-purpose devices as it passes
over the network, is showing great promise at improving application performance, in …

Columnar file formats provide an efficient way to store data to be queried by SQL‐on‐
Hadoop engines. Related works consider the performance of processing engine and file …

Edge computing is an emerging computing paradigm where data is generated and
processed in the field using distributed computing devices. Many applications such as real …

Efficiently exchanging temporary data between tasks is critical to the end-to-end
performance of many data processing frameworks and applications. Unfortunately, the …

The schemalessness, one of the major advantages of JSON representation format, comes
with high penalties in querying and operations by denying various critical functions such as …

The scale of computer clusters has grown significantly in recent years. Today, a cluster may
have 100 thousand machines and execute billions of tasks, especially short tasks, each day …

With the ever-increasing dataset sizes, several file formats such as Parquet, ORC, and Avro
have been developed to store data efficiently, save the network, and interconnect bandwidth …