Open Issues Need Help
View All on GitHubA no-code platform for creating DAGs, fully SQL-driven, that allows users to define workflows and execute them seamlessly on AWS EMR. Documentation: https://arcticoak2.github.io/data-phantom-docs/
AI Summary: This issue aims to establish project consistency and improve collaboration by setting up a contribution guide and defining a Java code style. It involves integrating formatting/linting tools to enforce the chosen style and subsequently refactoring the existing codebase to align with these new standards, enhancing readability and maintainability.
A no-code platform for creating DAGs, fully SQL-driven, that allows users to define workflows and execute them seamlessly on AWS EMR. Documentation: https://arcticoak2.github.io/data-phantom-docs/
AI Summary: This issue proposes adding support for running jobs on Google Cloud Dataproc, utilizing data stored in Google Cloud Storage (GCS). It involves creating a new provider module for GCP Dataproc and enabling seamless read/write operations with GCS.
A no-code platform for creating DAGs, fully SQL-driven, that allows users to define workflows and execute them seamlessly on AWS EMR. Documentation: https://arcticoak2.github.io/data-phantom-docs/
AI Summary: This issue requests the addition of Azure HDInsight as a new processing engine, allowing jobs to run on HDInsight clusters while utilizing Azure Blob Storage for data input and output. This involves developing a dedicated HDInsight provider module, implementing Blob Storage read/write capabilities, and updating the project's documentation.
A no-code platform for creating DAGs, fully SQL-driven, that allows users to define workflows and execute them seamlessly on AWS EMR. Documentation: https://arcticoak2.github.io/data-phantom-docs/