ruby-spark

Exposes Spark operations using Ruby idioms like lambdas and method symbols, as shown in examples with `map(:+)` and `reduce_by_key`, lowering the barrier for Ruby developers.

Implements core RDD transformations and actions from Spark, including `flat_map`, `aggregate`, and `histogram`, detailed in the README's operation lists.

Provides access to Spark's machine learning library for tasks like linear regression and K-Means, with Ruby examples for model training and prediction.

Supports configurable serializers like Marshal and Oj with batch sizing, allowing optimization for data types and performance, as noted in configuration settings.

Includes a Pry-based interactive shell for exploratory data analysis, enabling real-time testing of Spark jobs without full application deployment.