Combining lakeFS and Spark provides a new standard for scale and elasticity to distributed data pipelines. When integrating two technologies, the aim should be to expose the strengths of each as much as possible. With this philosophy in mind, we are excited to announce the beta release of the lakeFS FileSystem! This native Hadoop FileSystem …
Advancing lakeFS: Version Data At Scale With Spark Read More »
Data teams love calculating and tracking everything with metrics. We already have the infrastructure in place to do so… yet often fail to apply the same strategy for our own work. To fix that, let’s take a look at a few metrics useful for measuring our own performance. In my old office, there was a …
How to use lakeFS to keep multiple Delta tables consistent and guarantee data quality.
Today we are excited to announce the official release of the lakeFS Airflow provider! What this package does is allow you to easily integrate lakeFS functionality to your Airflow DAGs. The library is published on PyPI so it can easily be installed in your project via the command: pip install airflow-provider-lakefs Once installed, you are …
Debugging an issue is never fun, but why make it harder? In this post, we show how reproducing data is possible whether interacting with a single file, entire table, or data repository. Introducing Data Reproducibility There are two types of issues in the world — reproducible and unreproducible. A reproducible issue is one where the original conditions for …
Updated on April 5, 2022 As a user of the Go programming language, I’ve found it useful to enable the running multiple versions within a single project. If this is something you’ve tried or have considered, great! In this post I’ll present the when and the how of enabling multiple Go versions. Finally, we’ll conclude …
Let’s start with the obvious: the lakeFS project doesn’t exist in isolation. It belongs to a larger ecosystem of data engineering tools and technologies adjacent and complementary to the problems we are solving. What better way to visualize our place in this ecosystem, I thought, than by creating a cross-sectional LUMAscape to depict it. What’s …
Welcome to another episode “Concrete Graveler”, our deep-dive into the implementation of Graveler, the committed object storage for lakeFS. Graveler is our versioned object store, inspired by Git. It is designed to store orders of magnitude more objects than Git does. The last episode focused on how we store a single commit — a snapshot …
It makes perfect sense that if you type aws s3 ls s3://my-bucket to list the contents of an S3 bucket, you would expect to connect to the genuine bucket and have its contents listed. But there’s no hard rule that you have to connect to the real bucket. And in fact, there’s a simple parameter …
Introduction When building a data lake, there is perhaps no more consequential decision than the format data will be stored in. The outcome will have a direct effect on its performance, usability, and compatibility. It is inspiring that by simply changing the format data is stored in, we can unlock new functionality and improve the …
Hudi, Iceberg and Delta Lake: Data Lake Table Formats Compared Read More »
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