CCTC 2016 Databricks连城:The Future of Real-Time in Spark

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该文档来自CCTC 2016中国云计算技术大会。Apache Spark & Apache Parquet committer,Databricks 软件工程师发表的题为“The Future of Real-Time in Spark”的主题演讲,欢迎下载!
Streaming engine Noun Takes an input stream and produces an output stream edatabricks park Unified stack SQL Streaming MAli GraphX Spark Core edatabricks park Unified stack SQL Streaming MLIb GraphX Spark Core Introduced 3 years ago in Spark 0. 7 50% users consider most important part of spark edatabricks park streaming First attempt at unifying streaming and batch State management built in Exactly-once semantics Features required for large clusters Straggler mitigation Dynamic load balancing Fast fault-recovery edatabricks Streaming computations don’ t run in isolation edatabricks Use case fraud detection ANOMALY Ad-hoc analyze historic data STREAM Machine learning model continuously updates to detect new anomalies edatabricks Continuous application Noun An end-to-end application that acts on real-time data edatabricks Challenges building continous A plication Integration with non-streaming systems often an after-thought Interactive. batch. relational databases machine learning… Streaming programming models are complex edatabricks 10

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试读 30P CCTC 2016 Databricks连城:The Future of Real-Time in Spark
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geoge0714 也只有作者才敢起这样的标题吧
2017-11-18
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这个该叫什么呢 非常有用,谢谢楼主分享
2016-11-07
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