I found the potential reason. In local mode, all tasks in one stage runs concurrently, while tasks in yarn mode runs in sequence.
For example, in one stage, each task costs 3 mins. If in local mode, they will run together, and cost 3 min in total. In yarn mode, only two executor are assigned to process the task, since one executor can process one task only, they need 6 min in total. Regard, Junfeng Chen On Mon, Apr 9, 2018 at 2:12 PM, Jörn Franke <jornfra...@gmail.com> wrote: > Probably network / shuffling cost? Or broadcast variables? Can you provide > more details what you do and some timings? > > > On 9. Apr 2018, at 07:07, Junfeng Chen <darou...@gmail.com> wrote: > > > > I have wrote an spark streaming application reading kafka data and > convert the json data to parquet and save to hdfs. > > What make me puzzled is, the processing time of app in yarn mode cost > 20% to 50% more time than in local mode. My cluster have three nodes with > three node managers, and all three hosts have same hardware, 40cores and > 256GB memory. . > > > > Why? How to solve it? > > > > Regard, > > Junfeng Chen >
