logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

Modular Data Analytics

delete2024-09-01
delete0
PRE
AI
D
Diomidis Spinellis *
DOI：10.1109/MS.2024.3409988delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Relational online analytical processing (ROLAP) often involves complex queries with many intermediate steps, which can be expensive to run on large datasets. Modularizing SQL queries improves readability, testability, and incremental execution. While SQL common table expressions (CTEs) and views help in modularization, they have availability, performance, or development limitations. To address these, simple-rolap, an open-source framework, automates dependency analysis and orchestrates the execution of modular queries using GNU make. It uses a main database containing the infrequently modified base data and a secondary database for caching intermediate results. Simple-rolap ensures efficient, maintainable ROLAP queries by splitting complex queries into simple ones that create intermediate tables or report results, which can be unit-tested. It uses the make tool to manage dependencies and execution order, enhancing workflow control, testing, visualization, and troubleshooting.

Journal

IEEE Software cover
IEEE Software
IF:
3
Papers:
3.1K
Citations:
3.6K

Organization

No organization information available