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Research on Teaching Reform of “Spark Language Programming” Course
Creative Education Studies, 2023 With the rapid development of computer science and technology, programming ...
茜茵 吴
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Towards Verified Scalable Parallel Computing with Coq and Spark
FTfJP@ECOOP, 2023SyDPaCC (Systematic Development of programs for Parallel and Cloud Computing) is a framework for the Coq interactive theorem prover. It allows to systematically develop correct parallel programs from specifications via verified and automated program ...
F. Loulergue, Jolan Philippe
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ACM SIGAda Ada Letters, 2021
An effective approach to learning a new programming language is to implement data structures common to computer programming. The approach is effective because the problem to be solved is well understood, allowing one to focus on the language details ...
P. Rogers
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An effective approach to learning a new programming language is to implement data structures common to computer programming. The approach is effective because the problem to be solved is well understood, allowing one to focus on the language details ...
P. Rogers
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Spark SQL: Relational Data Processing in Spark
SIGMOD Conference, 2015Spark SQL is a new module in Apache Spark that integrates relational processing with Spark's functional programming API. Built on our experience with Shark, Spark SQL lets Spark programmers leverage the benefits of relational processing (e.g. declarative
Michael Armbrust +10 more
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A Study of Big Data Analytics using Apache Spark with Python and Scala
International Conferences on Information Science and System, 2020Data is generated by humans every day via various sources such as Instagram, Facebook, Twitter, Google, etc at a rate of 2.5 quintillion bytes with high volume, high speed and high variety.
Y. Gupta, Surbhi Kumari
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Translation of Array-Based Loops to Spark SQL
2020 IEEE International Conference on Big Data (Big Data), 2020Many programs written to analyze data are expressed in terms of array operations in an imperative programming language with loops. However, for data analysts who need to analyze vast volumes of data, large-scale data-intensive processing is becoming a ...
Md Hasanuzzaman Noor, L. Fegaras
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International Conference on Information Integration and Web-based Applications & Services, 2020
There have been numerous studies that have examined the performance of distribution frameworks. Most of these studies deal with the processing of large amounts of data.
Alexander Döschl +2 more
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There have been numerous studies that have examined the performance of distribution frameworks. Most of these studies deal with the processing of large amounts of data.
Alexander Döschl +2 more
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Comparison of MPI and Spark for Data Science Applications
IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum, 2020Data Science applications represent a growing fraction of the scientific computing workload, many of them written in Python. The goal of this paper is to compare two popular parallel programming models, namely MPI and Apache Spark for Python based Data ...
Manvi Saxena +5 more
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Accelerating Apache Spark with FPGAs
Concurrency and Computation, 2019Apache Spark has become one of the most popular engines for big data processing. Spark provides a platform‐independent, high‐abstraction programming paradigm for large‐scale data processing by leveraging the Java framework.
Ehsan Ghasemi, P. Chow
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