Zeppelin
superset
Zeppelin | superset | |
---|---|---|
8 | 137 | |
6,263 | 58,852 | |
0.2% | 1.5% | |
8.7 | 9.9 | |
7 days ago | 5 days ago | |
Java | TypeScript | |
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.
Zeppelin
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Serverless Apache Zeppelin on AWS
Now we can proceed with the definition of Apache Zeppelin. It is a web-based notebook that enables data-driven, interactive data analytics and collaborative documents with Python, Scala, SQL, Spark, and more. You can execute code and even schedule a job (via cron) to run at regular intervals.
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Visualization using Pyspark Dataframe
Have you tried Apache Zepellin I remember that you can pretty print spark dataframes directly on it with z.show(df)
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Fast CSV Processing with SIMD
I used to use Zeppelin, some kind of Jupyter Notebook for Spark (that supports Parquet). But it may be better alternatives.
https://zeppelin.apache.org/
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What libraries do you use for machine learning and data visualizing in scala?
Another more widely used notebooks for scala and spark: https://zeppelin.apache.org/
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How to use IPython in Apache Zeppelin Notebook
[1] Apache Zeppelin http://zeppelin.apache.org/ [2] Zeppelin notebooks website http://zeppelin-notebook.com/. [3] Zeppelin notebooks git repo https://github.com/zjffdu/zeppelin-notebook
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BI Application in Golang.
Apache Zeppelin
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Using InterSystems Caché and Apache Zeppelin
For all who think: What the heck is Apache Zeppelin? Here are some details what the project site says:
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Is there a way to collaborate in real-time for Jupyter Notebooks?
Check out Zeppelin. It's similar to Jupyter and allows real-time editing by multiple users. https://zeppelin.apache.org/
superset
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Apache Superset
Superset is absolutely phenomenal. I really hope Microsoft eventually releases all of their customizations they made to it internally to the OS community someday.
https://www.youtube.com/watch?v=RY0SSvSUkMA
https://github.com/apache/superset/discussions/20094
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A modern data stack for startups
I recently ran a little shootout between Superset, Metabase, and Lightdash. All have nontrivial weaknesses but I ended up picking Lightdash.
Superset the best of them at _data visualization_ but I honestly found it almost useless for self-serve _BI_ by business users. This issue on how to do joins in Superset (with stalebot making a mess XD) is everything difficult about Superset for BI in a nutshell. https://github.com/apache/superset/issues/8645
Metabase is pretty great and it's definitely the right choice for a startup looking to get low cost BI set up. It still has a very table centric view, but feels built for _BI_ rather than visualization alone.
Lightdash has significant warts (YAML, pivoting being done in the frontend, no symmetric aggregates) but the Looker inspiration is obvious and it makes it easy to present _groups of tables_ to business users ready to rock. I liked Looker before Google acquired it. My business users are comfortable with star and snowflake schemas (not that they know those words) and it was easy to drop Lightdash on top of our existing data warehouse.
- FLaNK Stack Weekly for 20 Nov 2023
- Hiding tokens retrieved via API from the html source?
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Yandex open sourced it's BI tool DataLens
Or like not being able to delete a user without running some SQL:
https://github.com/apache/superset/issues/13345
Almostl instantly run into this issue setting up a test instance of Superset. And the issue has been around for years.
- Apache Superset Is a Data Visualization and Data Exploration Platform
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Apache Superset: Installing locally is easy using the makefile
Are you interested in trying out Superset, but you're intimidated by the local setup process? Worry not! Superset needs some initial setup to install locally, but I've got a streamlined way to get started - using the makefile! This file contains a set of scripts to simplify the setup process.
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More public SQL-queryable databases?
Recently I discovered BigQuery public datasets - just over 200 datasets available for directly querying via SQL. I think this is a great thing! I can connect these direct to an analytics platform (we use Apache Superset which uses Python SQLAlchemy under the hood) for example and just start dashboarding.
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How useful is SQL for managers?
if they don't want to pay for powerbi, can try something like https://superset.apache.org/
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Real-time data analytics with Apache Superset, Redpanda, and RisingWave
In today's fast-paced data-driven world, organizations must analyze data in real-time to make timely and informed decisions. Real-time data analytics enables businesses to gain valuable insights, respond to real-time events, and stay ahead of the competition. Also, the analytics engine must be capable of running analytical queries and returning results in real-time. In this article, we will explore how you can build a real-time data analytics solution using the open-source tools Redpanda a distributed streaming platform, Apache Superset, a data visualization, and a business intelligence platform, combined with RisingWave a streaming database.
What are some alternatives?
Breeze - Breeze is a numerical processing library for Scala.
streamlit - Streamlit — A faster way to build and share data apps.
Spark Notebook - Interactive and Reactive Data Science using Scala and Spark.
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
Algebird - Abstract Algebra for Scala
Apache Hive - Apache Hive
Figaro - Figaro Programming Language and Core Libraries
lightdash - Self-serve BI to 10x your data team ⚡️
BigDL - Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, etc.
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
Smile - Statistical Machine Intelligence & Learning Engine
django-project-template - The Django project template I use, for installation with django-admin.