赵老师讲讲flink

http://www.mitbbs.com/article_t/Programming/31431453.html

发信人: database (《※★※§Hey§※★※》), 信区: Programming
标  题: 赵老师讲讲flink
发信站: BBS 未名空间站 (Thu Jul  9 10:10:56 2015, 美东)

Flink flips this on its head. Whereas Spark is a batch processing framework
that can approximate stream processing, Flink is primarily a stream
processing framework that can look like a batch processor. Immediately you
get the benefit of being able to use the same algorithms in both streaming
and batch modes (exactly as you do in Spark), but you no longer have to turn
to a technology like Apache Storm if you require low-latency responsiveness
. You get all you need in one framework, without the overhead of programming
and maintaining a separate cluster with a different API.


最近一直在找一种batch processor. 需要可以并行处理大量事务。我说事务而不是数
据。因为，在处理的过程中需要查询各种http microservice. spark看了半天文档和各
种例子。貌似进入rdd后就没法扩展了。

akka stream就是几个actor串起来，虽然pipeline起来了，但是并发木有啊。如果我用
n条pipeleine,这个他们做优化好像完全不对劲了。而且这个和我用fork join pool自
己写的异步程序区别不大。

貌似现在没有一个batch  ＋ pipeline的batch processor.而且不是面相单纯数据处理
而是数据和各种查询混杂的framework.

不知道flink或者storm那个更合适这种情景。