All Projects → metabrainz → Listenbrainz Server

metabrainz / Listenbrainz Server

Licence: gpl-2.0
Server for the ListenBrainz project

Programming Languages

python
139335 projects - #7 most used programming language
typescript
32286 projects

Projects that are alternatives of or similar to Listenbrainz Server

Spark With Python
Fundamentals of Spark with Python (using PySpark), code examples
Stars: ✭ 150 (-64.29%)
Mutual labels:  spark, big-data, database
Zeppelin
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Stars: ✭ 5,513 (+1212.62%)
Mutual labels:  spark, big-data, database
Succinct
Enabling queries on compressed data.
Stars: ✭ 257 (-38.81%)
Mutual labels:  spark, big-data
Trino
Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
Stars: ✭ 4,581 (+990.71%)
Mutual labels:  big-data, database
Delta
An open-source storage layer that brings scalable, ACID transactions to Apache Spark™ and big data workloads.
Stars: ✭ 3,903 (+829.29%)
Mutual labels:  spark, big-data
leaflet heatmap
简单的可视化湖州通话数据 假设数据量很大,没法用浏览器直接绘制热力图,把绘制热力图这一步骤放到线下计算分析。使用Apache Spark并行计算数据之后,再使用Apache Spark绘制热力图,然后用leafletjs加载OpenStreetMap图层和热力图图层,以达到良好的交互效果。现在使用Apache Spark实现绘制,可能是Apache Spark不擅长这方面的计算或者是我没有设计好算法,并行计算的速度比不上单机计算。Apache Spark绘制热力图和计算代码在这 https://github.com/yuanzhaokang/ParallelizeHeatmap.git .
Stars: ✭ 13 (-96.9%)
Mutual labels:  big-data, spark
aut
The Archives Unleashed Toolkit is an open-source toolkit for analyzing web archives.
Stars: ✭ 111 (-73.57%)
Mutual labels:  big-data, spark
Couchdb Fauxton
Apache CouchDB
Stars: ✭ 295 (-29.76%)
Mutual labels:  big-data, database
Data Accelerator
Data Accelerator for Apache Spark simplifies onboarding to Streaming of Big Data. It offers a rich, easy to use experience to help with creation, editing and management of Spark jobs on Azure HDInsights or Databricks while enabling the full power of the Spark engine.
Stars: ✭ 247 (-41.19%)
Mutual labels:  spark, big-data
Metorikku
A simplified, lightweight ETL Framework based on Apache Spark
Stars: ✭ 361 (-14.05%)
Mutual labels:  spark, big-data
Sparkler
Spark-Crawler: Apache Nutch-like crawler that runs on Apache Spark.
Stars: ✭ 362 (-13.81%)
Mutual labels:  spark, big-data
Hive
Apache Hive
Stars: ✭ 4,031 (+859.76%)
Mutual labels:  big-data, database
spark-acid
ACID Data Source for Apache Spark based on Hive ACID
Stars: ✭ 91 (-78.33%)
Mutual labels:  big-data, spark
awesome-AI-kubernetes
❄️ 🐳 Awesome tools and libs for AI, Deep Learning, Machine Learning, Computer Vision, Data Science, Data Analytics and Cognitive Computing that are baked in the oven to be Native on Kubernetes and Docker with Python, R, Scala, Java, C#, Go, Julia, C++ etc
Stars: ✭ 95 (-77.38%)
Mutual labels:  big-data, spark
bigdata-fun
A complete (distributed) BigData stack, running in containers
Stars: ✭ 14 (-96.67%)
Mutual labels:  big-data, spark
Koalas
Koalas: pandas API on Apache Spark
Stars: ✭ 3,044 (+624.76%)
Mutual labels:  spark, big-data
Crate
CrateDB is a distributed SQL database that makes it simple to store and analyze massive amounts of data in real-time.
Stars: ✭ 3,254 (+674.76%)
Mutual labels:  big-data, database
Ignite
Apache Ignite
Stars: ✭ 4,027 (+858.81%)
Mutual labels:  big-data, database
Gimel
Big Data Processing Framework - Unified Data API or SQL on Any Storage
Stars: ✭ 216 (-48.57%)
Mutual labels:  spark, big-data
Hyperspace
An open source indexing subsystem that brings index-based query acceleration to Apache Spark™ and big data workloads.
Stars: ✭ 246 (-41.43%)
Mutual labels:  spark, big-data

listenbrainz-server

Server for the ListenBrainz project

Website | Documentation | Bug tracker

About

ListenBrainz keeps tracks of what music you listen to and provides you with insights into your listening habits. We're completely open-source and publish our data as open data.

You can use ListenBrainz to track your music listening habits and share your taste with others using our visualizations. We also have an API if you want to do more with our data.

ListenBrainz is operated by the MetaBrainz Foundation which has a long-standing history of curating, protecting and making music data available to the public.

For more information about this project and its goals, look at our website, specifically the goals page.

Changes and other important announcements about the ListenBrainz services will be announced on our blog. If you start using our services in any production system, we urge you to follow the blog!

Commercial use

All of our data is available for commercial use. You can find out more about our commercial use support tiers on the MetaBrainz site.

Contributing

If you are interested in helping out, consider donating to the MetaBrainz Foundation.

If you are interesting in contributing code or documentation, please have a look at the issue tracker or come visit us in the #metabrainz IRC channel on irc.freenode.net.

Development environment

These instructions help you get started with the development process. Installation in a production environment may be different.

Read the development environment documentation

In order to work with Spark, you'll have to setup the Spark development environment. Read the documentation.

Documentation

Full documentation for the ListenBrainz API is available at listenbrainz.readthedocs.org. You can also build the documentation locally:

cd listenbrainz-server/docs
pip install -r requirements.txt
make clean html

License Notice

listenbrainz-server - Server for the ListenBrainz project

Copyright (C) 2017 MetaBrainz Foundation Inc.

This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].