lakeFS
spark-operator
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| lakeFS | spark-operator | |
|---|---|---|
| 48 | 8 | |
| 4,066 | 2,609 | |
| 2.5% | 2.4% | |
| 9.8 | 8.2 | |
| 2 days ago | 2 days ago | |
| Go | Go | |
| 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.
lakeFS
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A Step-by-Step Guide to Implementing Data Version Control
# Download the LakeFS binary wget https://github.com/treeverse/lakeFS/releases/latest/download/lakefs # Make the binary executable chmod +x lakefs # Initialize LakeFS with S3 as the storage backend ./lakefs init --backend s3 --s3-gateway-endpoint --s3-region --s3-force-path-style --s3-access-key --s3-secret-key
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Jujutsu: A Git-compatible DVCS that is both simple and powerful
Might want to look at purpose built tools for that such as lakeFS (https://github.com/treeverse/lakeFS/)
* Disclaimer: I'm one of the creators/maintainers of the project.
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Data diffs: Algorithms for explaining what changed in a dataset (2022)
Might want to checkout lakeFS: https://github.com/treeverse/lakeFS
(full disclosure: I'm one of the creators)
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Transactions in Spark / Delta lake?
Take a look at https://github.com/treeverse/lakeFS -
- LakeFS – Version Control for Big Data
- DuckDB <3 LakeFS
- We built an open-source project (3.1K stars on GitHub) for data version control
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How are you incrementally testing your data pipelines as you develop them?
I mean if you're ready to adopt a new framework into your ecosystem this is one of the major usecases for LakeFS.
- Git-for-Data
- LakeFS: Git-like versioning for object stores
spark-operator
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Dependency issue with Pyspark running on Kubernetes using spark-on-k8s-operator
I have spent days now trying to figure out a dependency issue I'm experiencing with (Py)Spark running on Kubernetes. I'm using the spark-on-k8s-operator and Spark's Google Cloud connector.
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Experience setting up Spark and Hudi on Kubernetes
We're using https://github.com/bitnami/charts/tree/main/bitnami/spark, but I have heard good things about https://github.com/GoogleCloudPlatform/spark-on-k8s-operator as well. Hudi should not need any long running deployments as per the docs https://hudi.apache.org/docs/0.5.1/deployment/#deploying
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[Spark-k8s] — Getting started # Part 1
The SparkOperator must be installed before we can use Spark on Kubernetes. Google created this operator, which is available on Github. In a nutshell, the operator is in charge of monitoring the cluster for specific events related to the spark job, as known as kind: SparkApplication
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So many sparks on K8s... Could anyone give me a few explanations please ?
Spark-Operator (as I understand, Spark-Operator integrates well with K8s while vanilla Spark integration with K8s seems extremely complex to maintain)
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"Running Apache Spark on EKS Fargate"
Spark on K8s Operator is a project from Google that allows submitting spark applications on Kubernetes cluster using CustomResource Definition SparkApplication. It uses mutating admission webhook to modify the pod spec and add the features not officially supported by spark-submit.
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My Journey With Spark On Kubernetes... In Python (1/3)
In this section, you use Helm to deploy the Kubernetes Operator for Apache Spark from the incubator Chart repository. Helm is a package manager you can use to configure and deploy Kubernetes apps.
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My Journey With Spark On Kubernetes... In Python (2/3)
Additional details of how SparkApplications are run can be found in the design documentation.
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Gopher Gold #14 - Wed Oct 07 2020
GoogleCloudPlatform/spark-on-k8s-operator (Go): Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
What are some alternatives?
dvc - 🦉 ML Experiments and Data Management with Git
volcano - A Cloud Native Batch System (Project under CNCF)
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
trojan-go - Go实现的Trojan代理，支持多路复用/路由功能/CDN中转/Shadowsocks混淆插件，多平台，无依赖。A Trojan proxy written in Go. An unidentifiable mechanism that helps you bypass GFW. https://p4gefau1t.github.io/trojan-go/
git-lfs - Git extension for versioning large files
helm-operator - Successor: https://github.com/fluxcd/helm-controller — The Flux Helm Operator, once upon a time a solution for declarative Helming.
Ory Kratos - Next-gen identity server replacing your Auth0, Okta, Firebase with hardened security and PassKeys, SMS, OIDC, Social Sign In, MFA, FIDO, TOTP and OTP, WebAuthn, passwordless and much more. Golang, headless, API-first. Available as a worry-free SaaS with the fairest pricing on the market!
enhancements - Enhancements tracking repo for Kubernetes
MLflow - Open source platform for the machine learning lifecycle
kubebuilder - Kubebuilder - SDK for building Kubernetes APIs using CRDs
duf - Disk Usage/Free Utility - a better 'df' alternative
helm - The Kubernetes Package Manager [Moved to: https://github.com/helm/helm]