Integrating Ruby with Spark and Hadoop is practical when teams standardize around JRuby shims for Spark DataFrame operations, orchestrate batch ETL with Airflow and Ruby clients, manage Parquet/ORC file handling and schema evolution, enforce fault tolerance with speculative execution and retries, and pursue cost optimization on cloud compute/storage tiers. These five approaches let Ruby applicat..