458 Open source projects that are alternatives of or similar to Cc Pyspark

零基础学习spark，大数据学习

A complete (distributed) BigData stack, running in containers

Boiler plate framework to use Spark and ZIO together.

Asynchronous actions for PySpark

Type System for Data Analysis in Python

spark summit 2017 SanFrancisco

Iceberg is a table format for large, slow-moving tabular data

Library for MQL5 (MetaTrader) with Python, Java, Apache Spark, AWS

Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.

Learn and understand Docker technologies, with real DevOps practice!

Spark Shuffle Optimization with RDMA+AEP

MapReduce, Spark, Java, and Scala for Data Algorithms Book

Spark on Kubernetes infrastructure Helm charts repo

something to help you spark

Building Large-Scale AI Applications for Distributed Big Data

Apache Spark docker container image (Standalone mode)

Apache Spark - A unified analytics engine for large-scale data processing

人生苦短 我用Python

Apache Spark and Apache Kafka integration example

Visualize column-level data lineage in Spark SQL

A Time Series Library for Apache Spark

spark on kubernetes

[NOT MAINTAINED] Predicting Bit coin price using Time series analysis and sentiment analysis of tweets on bitcoin

Final Project for IoT: Big Data Processing and Analytics class. Analyzing U.S nationwide temperature from IoT sensors in real-time

Code Library for My Blog

Avro SerDe for Apache Spark structured APIs.

low-level helpers for Apache Spark libraries and tests

TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.

A tool for building feature stores.

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Waimak is an open-source framework that makes it easier to create complex data flows in Apache Spark.

WeDataSphere is a financial level one-stop open-source suitcase for big data platforms. Currently the source code of Scriptis and Linkis has already been released to the open-source community. WeDataSphere, Big Data Made Easy!

Run spark calculations from Ammonite

❄️ 🐳 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

MaRe leverages the power of Docker and Spark to run and scale your serial tools in MapReduce fashion.

Kinesis Connector for Structured Streaming

Open-source distribute workflow schedule tools, also support streaming task.

🎯 🌟[大数据面试题]分享自己在网络上收集的大数据相关的面试题以及自己的答案总结.目前包含Hadoop/Hive/Spark/Flink/Hbase/Kafka/Zookeeper框架的面试题知识总结

Resources for Spark AR

Fast Data Cluster (Apache Cassandra, Kafka, Spark, Flink, YARN and HDFS with Vagrant and VirtualBox)

Efficient variant-call data storage and retrieval library using the TileDB storage library.

Spark functions to run popular phonetic and string matching algorithms

商品大数据实时推荐系统。前端：Vue + TypeScript + ElementUI，后端 Spring + Spark

PySpark Cheat Sheet - example code to help you learn PySpark and develop apps faster

C# and F# language binding and extensions to Apache Spark

Distributed least squares approximation (dlsa) implemented with Apache Spark

A framework for writing Spark 2.x applications in a pretty way

Generate beautiful documentation for your data pipelines in markdown format

Demo of PySpark and Jupyter Notebook with the Jupyter Docker Stacks

A pandas-like deferred expression system, with first-class SQL support

The Internals of Spark Structured Streaming

🎓 Jupyter notebooks from UFC data science course

This is the development repository of SparkMeasure, a tool for performance troubleshooting of Apache Spark workloads. It simplifies the collection and analysis of Spark task metrics data.

High Performance HTTP Sidecar Load Balancer

Machine Learning Platform and Recommendation Engine built on Kubernetes

Zemberek Türkçe NLP Java Kütüphanesi üzerine REST Docker Sunucu

Kyuubi is a unified multi-tenant JDBC interface for large-scale data processing and analytics, built on top of Apache Spark

A simplified, lightweight ETL Framework based on Apache Spark

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.