As an addition, some operators can only be run with a parallelism of 1. For example data sources based on collections and (un-grouped) all reduces. In some cases, the parallelism of the following operators will as well be set to 1 to avoid a network shuffle.
If you do: env.fromCollection(myCollection).map(new MyMapper()).groupBy(0).reduce(new MyReduce()).writeToFile(); the data source and mapper will be run with a parallelism of 1, the reducer and sink will be executed with the default parallelism. Best, Fabian 2015-06-30 10:25 GMT+02:00 Maximilian Michels <m...@apache.org>: > Hi Michele, > > If you don't set the parallelism, the default parallelism is used. For the > visualization in the web client, a parallelism of one is used. When you run > your example from your IDE, the default parallelism is set to the number of > (virtual) cores of your CPU. > > Moreover, Flink will currently not automatically set the parallelism in a > cluster environment. It will use the default parallelism or the user-set > parallelism. In your example, if you set the parallelism explicitly then it > will also show up in the visualization. > > Best, > Max > > On Tue, Jun 30, 2015 at 7:11 AM, Michele Bertoni < > michele1.bert...@mail.polimi.it> wrote: > >> Hi, I was trying to run my program in the flink web environment (the >> local one) >> when I run it I get the graph of the planned execution but in each node >> there is a "parallelism = 1”, instead i think it runs with par = 8 (8 core, >> i always get 8 output) >> >> what does that mean? >> is that wrong or is it really running with 1 degree of par? >> >> just a note: I never do any setParallelism() command, i leave it >> automatical >> >> thanks >> Best >> Michele > > >
