Pervasive DataRush 的替代方案是什么
我们正在研究促进大规模并行数据处理的解决方案。我们的处理图通常相当复杂，因此像 Pervasive DataRush 提供的完善的运算符框架非常方便。有谁知道 Pervasive 的替代解决方案吗？ DataRush 是 Java，但我想考虑可使用此类解决方案的所有平台和语言。
We are looking into the solution that facilitate massively parallel data processing. Our processing graphs are often rather complex, so well developed operator framework like one Pervasive DataRush provides comes handy. Does anyone know any alternative solutions to one from Pervasive? DataRush is Java but I would like to consider all platforms and languages for which such solutions are available.
如果你对这篇内容有疑问，欢迎到本站社区发帖提问 参与讨论，获取更多帮助，或者扫码二维码加入 Web 技术交流群。
绑定邮箱获取回复消息
由于您还没有绑定你的真实邮箱，如果其他用户或者作者回复了您的评论，将不能在第一时间通知您！
发布评论
评论（3）
不确定您是否会从 hadoop/map-reduce 之类的东西中获得有用的东西。这就是他们在营销材料上对自己的比较。当然，他们也声称他们是更好/不同的解决方案。
Not sure if you'd get usefulness out of something like hadoop/map-reduce. That's what they seem to compare themselves on their marketing collateral. Of course, they also claim that they're a better/different solution.
Pervasive DataRush 利用多核服务器和集群上的细粒度并行性。
随着 2011 年 2 月 2 日发布 V5.0，Pervasive DataRush 现在支持所有 JVM 语言 ，包括 Java、JRuby、Python 和 Scala。它还支持与 Hadoop/MapReduce 集成。它是对 Hadoop 的补充。
Pervasive DataRush exploits fine-grain parallelism on multicore servers and clusters.
With the release of V5.0 on 2 Feb 2011, Pervasive DataRush now supports all JVM languages, including Java, JRuby, Python and Scala. It also supports integration with Hadoop/MapReduce. It is complementary to Hadoop.
查看 https://github.com/rfqu/df4j - 简单但功能强大的数据流库。具有参与者和其他数据流构造。虽然它还缺乏持久性，但具有与 NIO2 异步通道的接口
Look at https://github.com/rfqu/df4j - simple but powerful dataflow library. Has Actors and other dataflow constructs. It lacks persistence yet, though, but has interface with NIO2 asyncronous channels