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From Philip Lee <philjj...@gmail.com>
Subject Hello, Pipelining Question
Date Mon, 15 Feb 2016 22:17:48 GMT

I found some interesting results from comparison with spark-sql and flink.
just for your information, spark-sql uses Hive QL on spark machine.

so as far as we know, when we run Flink job, the functions could be
overlapped on *pipelining* like this picture.

[image: Inline image 1]

likewise, spark supports *pipelining* as I read PPT of Spark. The function
could be overlapped as well. but it seems like there is some boundary.

For example, in *Flink*, functions to read multiple inputs could be run
together *with join function* like the above pic. but in *Spark*, to read
multiple inputs can be together, but join function is seemingly *sepearted*
to the reading functions. (you can see the starting time and duration,
indicating join step is seperated)

[image: Inline image 2]

This is why Spark is a Batch processing in memory, wherease Flink is a
Streaming processing in memory?


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