# databricks/LearningSparkV2

This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]

Repository: https://github.com/databricks/LearningSparkV2
Canonical: https://ross.abutalabs.com/products/learningsparkv2
Homepage: https://learning.oreilly.com/library/view/learning-spark-2nd/9781492050032/
Language: Scala
License: Apache-2.0
License Family: permissive
Topics: apache-spark, spark, structured-streaming, spark-sql, spark-mllib, mllib, mlflow, delta-lake
Last push: 2025-01-28T04:30:40+00:00

## Health v2 (maintenance only)
Score: 34/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 3, release rhythm 35, longevity 100
- inputs: {"age_days": 2761, "days_push": 582, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1399, forks 797 (observed 2026-08-28T04:04:36.928836+00:00)

## What it is
The official companion repository for the book 'Learning Spark: Lightning-Fast Data Analytics, 2nd Edition', containing example Spark applications and notebooks. It provides buildable Scala JARs per chapter plus Databricks-style notebooks covering Spark SQL, structured streaming, MLlib, Delta Lake, and MLflow.

## Use cases
- learn apache spark from scratch
- find spark structured streaming examples
- study spark sql code samples
- learn mllib machine learning with spark
- get working examples of delta lake and mlflow
- follow along with the learning spark book exercises

## When to choose
- you are reading Learning Spark 2nd Edition and want its runnable code
- you want curated, book-quality examples of Spark SQL, streaming, and MLlib
- you prefer learning via notebooks or standalone spark-submit applications

## When to avoid
- you need production-ready Spark tooling rather than educational examples
- you want comprehensive documentation instead of book companion code
- you need a maintained library with an API to depend on

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science, machine-learning, streaming, etl
- domain: big-data, tutorials, data-science
- platform: jvm, python, cross-platform
- tags: apache-spark, spark-sql, structured-streaming, mllib, delta-lake, mlflow, book-examples, scala, notebooks, data-engineering

## Member repositories
- databricks/LearningSparkV2 (main) score 34

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:36.928836+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 2026-08-30T04:39:10.515631+00:00, confidence not recorded.
  - readme: https://github.com/databricks/LearningSparkV2 (fetched 2026-08-28T04:04:36.928836+00:00, sha f5d49384f0e9)
- Data as of 2026-08-30T08:39:29.467469+00:00.