microsoft / data-accelerator

Data Accelerator for Apache Spark simplifies onboarding to Streaming of Big Data. It offers a rich, easy to use experience to help with creation, editing and management of Spark jobs on Azure HDInsights or Databricks while enabling the full power of the Spark engine.

Summary

	SFPROJ CMD
		Main Code: 50,926 LOC (709 files) = CS (45%) + JSX (22%) + JS (13%) + SCALA (11%) + PS1 (4%) + PSM1 (1%) + YAML (<1%) + CSS (<1%) + SFPROJ (<1%) + PY (<1%) + CMD (<1%) + HTML (<1%) + YML (<1%) Secondary code: Test: 4,860 LOC (81); Generated: 694 LOC (4); Build & Deploy: 3,151 LOC (74); Other: 15,184 LOC (202);
		Duplication: 16%
		File Size: 2% long (>1000 LOC), 61% short (<= 200 LOC)
		Unit Size: 4% long (>100 LOC), 52% short (<= 10 LOC)
		Conditional Complexity: 5% complex (McCabe index > 50), 69% simple (McCabe index <= 5)
		Logical Component Decomposition: primary (23 components)
		2 years, 10 months old 100% of code older than 365 days 90% of code not updated in the past 365 days
		0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits.
		Goals: Keep the system simple and easy to change (4)
	Features of interest: TODOs 22 files

Commits Trend

Latest commit date: 2022-01-19

2 commits (30 days) 2 contributors (30 days)

Commits 2 19 9 292 Contributors 2 6 3 27 2022 2021 2020 2019

show commits trend per language

Commits	2022 2021 2020 2019 1 5 1 22 scala 5 3 27 jsx 4 2 100 cs 2 2 15 ps1 2 1 10 psm1 2 1 6 css sfproj 2 14 sfproj 1 1 43 js 9 yaml 1 py cmd 5 cmd 1 1 html 1 yml
Contributors	2022 2021 2020 2019 1 4 1 8 scala 3 1 15 cs sfproj 2 6 sfproj 1 1 7 jsx 1 2 7 ps1 1 1 6 psm1 1 1 5 css 1 1 7 js 4 yaml 1 py cmd 5 cmd 1 1 html 1 yml