ceja
sparkmagic
ceja | sparkmagic | |
---|---|---|
1 | 4 | |
32 | 1,286 | |
- | 0.2% | |
2.3 | 7.6 | |
2 months ago | about 20 hours ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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ceja
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Which language is better for Spark & Why?
Some Python libraries are easily wrapped via UDFs, see ceja, but don't overestimate this benefit. Most Python libraries cannot be wrapped and run via Spark in a performant manner.
sparkmagic
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Doing ML works in AWS. Need help installing cartopy
Please file an issue at https://github.com/jupyter-incubator/sparkmagic
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Ask HN: Who's an open source maintainer/project that needs sponsorship or help?
I maintain several open source projects, most notably:
Sparkmagic (https://github.com/jupyter-incubator/sparkmagic)
Sparkmagic provides jupyter magics and kernels for working with remote Spark clusters. It's used by thousands of developers and companies like Pinterest, Amazon, more!
I've been maintaining for the past few years and would love help!
KSOPS (https://github.com/viaduct-ai/kustomize-sops)
KSOPS, or kustomize-SOPS, is a kustomize KRM exec plugin for SOPS encrypted resources. KSOPS can be used to decrypt any Kubernetes resource, but is most commonly used to decrypt encrypted Kubernetes Secrets and ConfigMaps. As a kustomize plugin, KSOPS allows you to manage, build, and apply encrypted manifests the same way you manage the rest of your Kubernetes manifests.
KSOPS is the most popular kustomize plugin and I'd love help maintaining and improving it from out GitOps fanatics.
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Spark is lit once again
Things get a bit more complicated on interactive sessions. We've created Sparkmagic compatible REST API so that Sparkmagic kernel could communicate with Lighter the same way as it does with Apache Livy. When a user creates an interactive session Lighter server submits a custom PySpark application which contains an infinite loop which constantly checks for new commands to be executed. Each Sparkmagic command is saved on Java collection, retrieved by the PySpark application through Py4J Gateway and executed.
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An SQL Solution for Jupyter
Jupyter would be even better if it supported the seamless combination of Python and SQL code cells.
My notebook code typically involves a data prep stage with querying a SQL database, then downloading into Python for more complex analysis, ML modelling, integration with external data sources, etc. So the notebook has a Python kernel with SQL usually as embedded """-quoted strings.
Does anyone have a solution to treating selected code cells as SQL - with SQL highlighting and tooltips - exposed as string variables to the Python code?
Sparkmagic [1] does part of this for Python/SQL/Spark interoperability, but as far as I recall, doesn't support SQL syntax highlighting.
[1] https://github.com/jupyter-incubator/sparkmagic
What are some alternatives?
jellyfish - 🪼 a python library for doing approximate and phonetic matching of strings.
lighter - REST API for Apache Spark on K8S or YARN
TextDistance - 📐 Compute distance between sequences. 30+ algorithms, pure python implementation, common interface, optional external libs usage.
Jupyter Scala - A Scala kernel for Jupyter
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
textdistance.rs - 🦀📏 Rust library to compare strings (or any sequences). 25+ algorithms, pure Rust, common interface, Unicode support.
nbmake - 📝 Pytest plugin for testing notebooks
nbgrader - A system for assigning and grading notebooks
xeus-sql - Jupyter kernel for SQL databases
incubator-livy - Apache Livy is an open source REST interface for interacting with Apache Spark from anywhere.
incubator-livy - Mirror of Apache livy (Incubating)