astro-sdk
CoinCap-firehose-s3-DynamicPartitioning
| astro-sdk | CoinCap-firehose-s3-DynamicPartitioning | |
|---|---|---|
| 7 | 1 | |
| 317 | 0 | |
| 0.9% | - | |
| 8.5 | 10.0 | |
| 5 days ago | over 2 years ago | |
| Python | TypeScript | |
| Apache License 2.0 | - |
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astro-sdk
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Orchestration: Thoughts on Dagster, Airflow and Prefect?
Have you tried the Astro SDK? https://github.com/astronomer/astro-sdk
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Airflow as near real time scheduler
One interesting point about putting the data into s3, is that if the data is in an S3 file then OP can use the Astro SDK to pretty easily upload that data into a table or a dataframe (there's even an s3 dynamic task function in the SDK that might fit the use-case well here).
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Most ideal Airflow task structure?
I think you should take a look at the Astro SDK It’s an open source python package that removes the complexity of writing DAGs , particularly in the context of Extract, Load, Transform (ELT) use cases. Look at the doc here, especially aql.transform, aql.run_raw_sql, etc. That will definitely help you
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ELT pipeline using airflow
- Astro SDK*: Made for folks who are doing their ETL in airflow and want to simplify movement between DBs and Pandas
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After Airflow. Where next for DE?
More of a general principle but when you don't have design patterns, you get varying levels of results right? I think what Astro is doing to introduce "strong defaults" through projects like the astro-sdk or the cloud ide are interesting experiments to remove some of the busy work of common dags (load from s3, do something, push to database) will HELP reduce the cognitive load of really common, simple actions and give them a better single pattern to optimize on. I don't think those efforts reduce the optionality of true power users at all who want to custom code their s3 log sink to have some unique implementation while at the same time maybe solving some of the fragmentation to very frequently performed operations. 🤞
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Airflow - Passing large data volumes between tasks
Have you looked into the astro python SDK? My team and I built this out over the last year to do exactly this :). You can you use the `@dataframe` decorator to pull the API data into a dataframe, store it in GCS and the access it in future steps. Lemme know if you have any questions!
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What's the best tool to build pipelines from REST APIs?
I have an example here using COVID data. basically you just write a python function that reads the API and returns a dataframe (or any number of dataframes) and downstream tasks can then read the output as either a dataframe or a SQL table.
CoinCap-firehose-s3-DynamicPartitioning
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What's the best tool to build pipelines from REST APIs?
I agree with the Cron triggered Lambda approach. For inspiration I have a small project where a lambda pulls data from a public api and writes it to a firehose which buffers the data and writes it to s3. There is also a cron job on Glue which catalogues the data. https://github.com/TrygviZL/CoinCap-firehose-s3-DynamicPartitioning
What are some alternatives?
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
quadratic - Quadratic | Data Science Spreadsheet with Python & SQL
gnu-parallel - A clone of GNU Parallel (git://git.savannah.gnu.org/parallel.git)
astro - Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow. [Moved to: https://github.com/astronomer/astro-sdk]
starthinker - Reference framework for building data workflows provided by Google. Accelerates authentication, logging, scheduling, and deployment of solutions using GCP. To borrow a tagline.. "The framework for professionals with deadlines."
astronomer-cosmos - Run your dbt Core projects as Apache Airflow DAGs and Task Groups with a few lines of code
awesome-pipeline - A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin
airflow-maintenance-dags - A series of DAGs/Workflows to help maintain the operation of Airflow
getting-started - This repository is a getting started guide to Singer.
typhoon-orchestrator - Create elegant data pipelines and deploy to AWS Lambda or Airflow