Sql

In real-world analytics, Spark users often need to do things like count substrings, tally words in collections, or process text—tasks not always convenient with Spark’s built-in SQL functions. fantastic-spork delivers production-ready, native Catalyst expressions for these cases, ensuring top Spark performance and seamless integration. More efficient than regular Scala UDFs Convenient SQL extensions Composable for DataFrame, Dataset, and SQL APIs Project Link: https://rokorolev.gitlab.io/fantastic-spork/

sparqlin is a Spark SQL framework designed to simplify job creation and management in Databricks environments. It integrates with Spark SQL and PySpark for a streamlined development experience. The framework was specifically created to empower data analysts who may not have deep development skills. It provides a streamlined approach to adopting standard software development life cycles, enabling analysts to focus on working with data without the need to master complex programming paradigms. By leveraging familiar tools like SQL scripts and YAML files, the framework simplifies tasks such as data configuration, transformation, and testing. ...