{"id":18359017,"url":"https://github.com/ev2900/emr_studio_hudi","last_synced_at":"2025-08-09T10:18:00.826Z","repository":{"id":85139176,"uuid":"417507854","full_name":"ev2900/EMR_Studio_Hudi","owner":"ev2900","description":" Apache Hudi examples designed to be run on AWS Elastic Map Reduce (EMR) via. 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EMR Studio and/or EMR Notebook(s).\n\nReference background on key [concepts](https://hudi.apache.org/docs/concepts/). If you are new to working with Hudi it is worth reading about Hudi's [timeline](https://hudi.apache.org/docs/concepts/#timeline), [file management](https://hudi.apache.org/docs/concepts/#file-management), [index](https://hudi.apache.org/docs/concepts/#index), [table types](https://hudi.apache.org/docs/concepts/#table-types), [query types](https://hudi.apache.org/docs/concepts/#query-types), [copy on write](https://hudi.apache.org/docs/concepts/#copy-on-write-table), [merge on read](https://hudi.apache.org/docs/concepts/#merge-on-read-table).\n\nIf you are not familiar with the core Hudi concepts or are new to Hudi I **highly** recommend you watch [AWS re:Invent 2019: Insert, upsert, and delete data in Amazon S3 using Amazon](https://www.youtube.com/watch?v=_ckNyL_Nr1A).\n\n## Enviorment Set Up\n\nThe samples in this repository are designed to run on EMR via. EMR Notebooks or EMR Studio. To set up your enviorment follow the AWS documentation for [EMR Notebooks](https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-managed-notebooks.html) or [EMR Studio](https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-studio.html).\n\nYou can upload the .ipynb files in this repository directly to the Jupyter enviorments provides by EMR Notebooks / Studio\n\n## Copy on Write\nThe notebooks in [copy_on_write](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/tree/main/copy_on_write) is the best place to start. It covers working with data via. Hudi specific to **copy on write** tables. The notebook(s) covers\n* Writing data to S3\n* Reading data from S3\n* Upserting data\n* Incremental querying\n* Point in Time querying\n* Deleting Data\n\nBoth a [Python](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/blob/main/copy_on_write/Python/copy_on_write_python.ipynb) and [Scala](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/blob/main/copy_on_write/Scala/copy_on_write_scala.ipynb) notebooks are available.\n\n## Merge on Read\nThe notebook in [merge_on_read](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/tree/main/merge_on_read) is the best next step once you understand the [copy_on_write](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/tree/main/copy_on_write) notebook(s). The [merge_on_read](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/tree/main/merge_on_read) notebook covers\n* Writing data to S3\n* Upserting data\n* Snapshot queries\n* Read optimized queries\n* Compaction\n\nBoth a [Python](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/tree/main/merge_on_read/Python/merge_on_read_python.ipynb) and [Scala](https://github.com/ev2900/Hudi_Elastic_Map_Reduce/tree/main/merge_on_read/Scala/merge_on_read_scala.ipynb) notebooks are available.\n\n## Future Imporvement to this Repo\n* Hudi SQL example(s)\n* Hudi time travel example(s)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fev2900%2Femr_studio_hudi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fev2900%2Femr_studio_hudi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fev2900%2Femr_studio_hudi/lists"}