s3-sqs-connector
Spark Utils
| s3-sqs-connector | Spark Utils | |
|---|---|---|
| 6 | - | |
| 16 | 36 | |
| - | - | |
| 0.0 | 4.6 | |
| 13 days ago | 28 days ago | |
| Scala | Scala | |
| Apache License 2.0 | MIT License |
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s3-sqs-connector
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Upload to S3 -> AWS lambda with some Scala Spark code -> Process -> Write back to S3
Are you planning on uploading and processing many files to S3? If so I would use something like Structured Streaming with the FileSource which can detect new files uploaded to S3 and process them in on a "standard" Spark cluster. You can then build a very easy to deploy and operate cluster on EKS/Kubernetes. I would check out: https://github.com/qubole/s3-sqs-connector once the number of files you upload start to get really large. Glue could also be used to achieve roughly the same thing and without the hassle of managing the EKS/K8s clusters.
Spark Utils
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Tracking mentions began in Dec 2020.
What are some alternatives?
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
delight - A Spark UI and Spark History Server alternative with CPU and Memory metrics! Delight is free, cross-platform, and open-source.
Jupyter Scala - A Scala kernel for Jupyter
Scoobi - A Scala productivity framework for Hadoop.
deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
Scoozie - Scala DSL on top of Oozie XML
LearningSparkV2 - This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
Sparkta - Real Time Analytics and Data Pipelines based on Spark Streaming