holdenk/spark-testing-base
Base classes to use when writing tests with Spark observed · 2026-08-28
Health v2 · maintenance only
66/100
- Activity 96
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4233
- days_rel: n/a
- days_push: 26
- n_releases_24m: 0
Adoption not part of the score
1555 stars · 356 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A library providing base classes for writing tests for Apache Spark applications in Scala and Python. It handles the setup and teardown of local-mode Spark sessions so developers can focus on writing test logic.
Use cases
- write unit tests for Spark jobs
- avoid boilerplate SparkContext setup in test suites
- test Spark DataFrames and RDDs
- test Spark SQL codegen
- run Spark tests in sbt or Maven builds
When to choose
- you're building Spark applications in Scala or Python and need repeatable test infrastructure
- you want shared base classes for local-mode Spark testing across many test suites
When to avoid
- you don't use Apache Spark
- you need distributed cluster integration testing rather than local-mode tests
Facets
library · maturity active
testing testing developer-tools big-data jvm python apache-spark unit-testing local-mode-spark scala pyspark
1 source
- readme: https://github.com/holdenk/spark-testing-base · fetched 2026-08-28 · 869e250cac63
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| holdenk/spark-testing-base | main | 66 |
For agents
markdown · JSON · MCP: product_card(name="holdenk/spark-testing-base")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem