Apache Spark adoption is growing but the complexities remain
Apache Spark has moved beyond the early-adopter phase and is now mainstream. Large data-driven enterprises are looking at Spark for all data processing tasks ranging from ingest through ETL and data quality processing to advanced analytics and machine learning jobs.
However, despite its growing popularity, Spark is still evolving. Along with a steep learning curve, developers need time to develop, integrate, and test code on Spark to solve the underlying complexities.