Stream processing fundamentals - CS 591 K1: Data Stream Processing and Analytics Spring 2020propagation synchronized asynchronous Data historical recent and historical ETL process complex fast and light-weight ETL: Extract-Transform-Load e.g. unzipping compressed files, data cleaning and0 码力 | 45 页 | 1.22 MB | 1 年前3- Introduction to Apache Flink and Apache Kafka - CS 591 K1: Data Stream Processing and Analytics Spring 2020core • Streaming & Batch API Historic data Kafka, RabbitMQ, ... HDFS, JDBC, ... Event logs ETL, Graphs, Machine Learning Relational, … Low latency, windowing, aggregations, ... 2 Vasiliki0 码力 | 26 页 | 3.33 MB | 1 年前3
- PyFlink 1.15 Documentationdata processing pipelines, large-scale exploratory data analysis, Machine Learning (ML) pipelines and ETL processes. If you’re already familiar with Python and libraries such as Pandas, then PyFlink makes0 码力 | 36 页 | 266.77 KB | 1 年前3
- PyFlink 1.16 Documentationdata processing pipelines, large-scale exploratory data analysis, Machine Learning (ML) pipelines and ETL processes. If you’re already familiar with Python and libraries such as Pandas, then PyFlink makes0 码力 | 36 页 | 266.80 KB | 1 年前3
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