s3-sqs-connector
LearningSparkV2
| s3-sqs-connector | LearningSparkV2 | |
|---|---|---|
| 6 | 1 | |
| 16 | 1,095 | |
| - | 3.3% | |
| 0.0 | 0.0 | |
| 12 days ago | over 1 year ago | |
| Scala | Scala | |
| Apache License 2.0 | Apache License 2.0 |
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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.
LearningSparkV2
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datadelivery: Providing public datasets to explore in AWS
Learning Spark
What are some alternatives?
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Spark-The-Definitive-Guide - Spark: The Definitive Guide's Code Repository
Spark Utils - Basic framework utilities to quickly start writing production ready Apache Spark applications
delta-sharing - An open protocol for secure data sharing
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
datadelivery - A Terraform module that provides an efficient way to activate pieces and services in an AWS account in order to enable users to explore preselected public datasets.
Apache-Hive-Essentials-Second-Edition - Apache Hive Essentials, Second Edition published by Packt
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs