There is high demand for techniques and tools to process and analyze large sets of
streaming data in both industrial and academic settings. While existing work in this area has …

Abstract As Big Data processing problems evolve, many modern applications demonstrate
special characteristics. Data exists in the form of both large historical datasets and high …

There is high demand for tools that analyze large sets of streaming data in both industrial
and academic settings. While existing work has examined a wide range of issues, we focus …

This paper addresses online query processing for large-scale, incremental data analysis on
a distributed stream processing engine (DSPE). Our goal is to convert any SQL-like query to …

Today's streaming applications demand increasingly high event throughput rates and are
often subject to strict latency constraints. To allow for more complex workloads, such as …

This paper presents RisingWave, a new cloud-native streaming database under
development. RisingWave's mission is to democratize stream processing: to make stream …

ABSTRACT The Big Data movement proposes data streaming systems to tame velocity and
to enable reactive decision making. However, approaching such systems is still too complex …

In this chapter, we will look at an example of how to create a streaming application. Apache
Spark's structured streaming API allows you to use the DataFrame API to express your …

In the Big Data context, data streaming systems have been introduced to tame velocity and
enable reactive decision making. However, approaching such systems is still too complex …

Exploratory analysis on big data requires us to rethink data management across the entire
stack--from the underlying data processing techniques to the user experience. We …