# sryza/aas

Code to accompany Advanced Analytics with Spark from O'Reilly Media

Repository: https://github.com/sryza/aas
Canonical: https://ross.abutalabs.com/products/aas
Language: Scala
License: NOASSERTION
License Family: other
Last push: 2024-09-25T14:40:05+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4316, "days_push": 707, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1525, forks 1008 (observed 2026-08-28T04:04:58.314796+00:00)

## What it is
Source code examples accompanying the O'Reilly book 'Advanced Analytics with Spark', written in Scala and built with Maven. It provides runnable chapter-by-chapter examples covering machine learning and analytics on Apache Spark with accompanying public datasets.

## Use cases
- learn spark machine learning with worked examples
- run analytics examples on apache spark
- study recommendation and clustering code in scala
- find datasets for practicing spark analytics
- follow along with the advanced analytics with spark book

## When to choose
- you are reading the book and want its companion code
- you want concrete Scala/Spark examples of common ML algorithms
- you need sample datasets paired with analytics code

## When to avoid
- you need a production-ready analytics library
- you want a maintained framework with active feature development
- you work outside the JVM/Spark ecosystem

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science, etl, developer-tools
- domain: data-science, big-data, machine-learning, tutorials
- platform: jvm, cross-platform
- tags: apache-spark, scala, book-examples, oreilly, analytics, maven

## Member repositories
- sryza/aas (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:58.314796+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:31:40.417432+00:00, confidence not recorded.
  - readme: https://github.com/sryza/aas (fetched 2026-08-28T04:04:58.314796+00:00, sha 0bab594aba1e)
- Data as of 2026-08-30T08:39:29.467469+00:00.