blog_posts: 7b789af9f3
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id | createdDate | title | link | postExcerpt | featuredImageUrl | hash | contributors | modifiedDate | displayDate |
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blog-posts#33-10607 | 2020-06-25 17:51:59 | Process data with varying data ingestion frequencies using AWS Glue job bookmarks | https://aws.amazon.com/blogs/big-data/process-data-with-varying-data-ingestion-frequencies-using-aws-glue-job-bookmarks/ | We often have data processing requirements in which we need to merge multiple datasets with varying data ingestion frequencies. Some of these datasets are ingested one time in full, received infrequently, and always used in their entirety, whereas other datasets are incremental, received at certain intervals, and joined with the full datasets to generate output. To address this requirement, this post demonstrates how to build an extract, transform, and load (ETL) pipeline using AWS Glue. | https://d2908q01vomqb2.cloudfront.net/b6692ea5df920cad691c20319a6fffd7a4a766b8/2020/06/19/GlueJobBookmarks1-300x186.png | 7b789af9f3 | Dipankar Kushari, Ashok Padmanabhan | 2024-05-23 18:53:42 | 25 Jun 2020 |
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