There are 35 repositories under spark-streaming topic.
酷玩 Spark: Spark 源代码解析、Spark 类库等
基于Spark的电影推荐系统,包含爬虫项目、web网站、后台管理系统以及spark推荐系统
Streaming System 相关的论文读物
Scala examples for learning to use Spark
Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines
Databricks framework to validate Data Quality of pySpark DataFrames
Benchmarks for data processing systems: Pathway, Spark, Flink, Kafka Streams
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.
Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
Spark, Spark Streaming and Spark SQL unit testing strategies
A complete example of a big data application using : Kubernetes (kops/aws), Apache Spark SQL/Streaming/MLib, Apache Flink, Scala, Python, Apache Kafka, Apache Hbase, Apache Parquet, Apache Avro, Apache Storm, Twitter Api, MongoDB, NodeJS, Angular, GraphQL
Self-contained examples of Apache Spark streaming integrated with Apache Kafka.
A prototype project of big data platform, the source codes of the book Big Data Platform Architecture and Prototype
StreamLine - Streaming Analytics
:star2: :sparkles: Analyze and visualize Twitter Sentiment on a world map using Spark MLlib
Kinesis Connector for Structured Streaming
Apache Spark and Apache Kafka integration example
Apache Spark 3 - Structured Streaming Course Material
电影推荐系统、电影推荐引擎、使用Spark完成的电影推荐引擎
Code examples on Apache Spark using python
This repository will help you to learn about databricks concept with the help of examples. It will include all the important topics which we need in our real life experience as a data engineer. We will be using pyspark & sparksql for the development. At the end of the course we also cover few case studies.
This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to topic where they are consumed by a spark streaming job running on IBM BigInsights (hadoop).
基于spark-ml,spark-mllib,spark-streaming的推荐算法实现
Custom state store providers for Apache Spark
spark全示例代码(java、scala) Spark most full instance code DEMO (java、scala)
A data engineering project (Twitter monitor app)