Apache Parquet
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Apache Parquet | Airflow | |
---|---|---|
4 | 169 | |
2,407 | 34,485 | |
2.9% | 2.1% | |
9.2 | 10.0 | |
2 days ago | about 15 hours ago | |
Java | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Apache Parquet
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How-to-Guide: Contributing to Open Source
Apache Parquet
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parquet-tools
This go implementation, other than common advantages from go itself (small single executable, support multiple platforms, speed, etc.), has some neat features compare with Java parquet tool and Python one like:
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Writing Apache Parquet Files
Hi, I've been trying to write parquet files on android for the past couple of days, and have really been struggling to find a solution. My original hypothesis was to just use the java parquet implementation (https://github.com/apache/parquet-mr), but I've since realized that not all java libraries play well with Android. I've gone through essentially dependency hell trying to franken-fit the library into my project, and imported as much as i could before hitting walls such as this one (https://github.com/mockito/mockito/issues/841).
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pqrs: A parquet-tools replacement in Rust using Apache Arrow
Like many of you probably do, I tend to work with Parquet files a lot. parquet-tools has been my tool of choice for inspecting parquet files, but that has been deprecated recently. So, I created a replacement for it using Rust and Apache Arrow.
Airflow
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Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions
Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.
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Navigating Week Two: Insights and Experiences from My Tublian Internship Journey
In week Two, I contributed to the Apache Airflow repository.
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Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Best ETL Tools And Why To Choose
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
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Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring.
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Share Your favorite python related software!
AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic!
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Ask HN: What is the correct way to deal with pipelines?
I agree there are many options in this space. Two others to consider:
- https://airflow.apache.org/
- https://github.com/spotify/luigi
There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file showing up in a directory…
- "Você veio protestar para ter acesso ao código fonte da urnas. O que é o código fonte?" "Não sei" 🤡
- Cómo construir tu propia data platform. From zero to hero.
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Is it impossible to contribute to open source as a data engineer?
You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte
What are some alternatives?
Protobuf - Protocol Buffers - Google's data interchange format
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Apache Thrift - Apache Thrift
dagster - An orchestration platform for the development, production, and observation of data assets.
Apache Avro - Apache Avro is a data serialization system.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
Apache Orc - Apache ORC - the smallest, fastest columnar storage for Hadoop workloads
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Big Queue - A big, fast and persistent queue based on memory mapped file.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Wire - gRPC and protocol buffers for Android, Kotlin, Swift and Java.
Dask - Parallel computing with task scheduling