You have to define a common type, like an n-ary Either type and return that from your source / operator. The resulting DataSet can be consumed by multiple FlatmapFunctions, each extracting and forwarding one of the the result types.
Cheers, Fabian Am Di., 6. Nov. 2018 um 10:40 Uhr schrieb madan <madan.yella...@gmail.com>: > Hi Vino, > > Thank you for suggestions. In my case I am using DataSet since data is > limited, and split/select is not available on DataSet api. > I doubt even hash partition might not work for me. By doing hash > partition, I do not know which partition is having which entity data (Dept, > Emp in my example. And sometimes hasing might be same for 2 different > entities). And on that partition I need to apply some other > transformations(based on partition data) which is not possible using > MapPartitionFunction. > > Please suggest if my understanding is wrong and usecase is achievable > (little example is of great help). > > Thank you, > Madan > > On Tue, Nov 6, 2018 at 12:03 PM vino yang <yanghua1...@gmail.com> wrote: > >> Hi madan, >> >> I think you need to hash partition your records. >> Flink supports hash partitioning of data. >> The operator is keyBy. >> If the value of your tag field is enumerable, you can also use >> split/select to achieve your purpose. >> >> Thanks, vino. >> >> madan <madan.yella...@gmail.com> 于2018年11月5日周一 下午6:37写道： >> >>> Hi, >>> >>> I have a custom iterator which gives data of multitple entities. For >>> example iterator gives data of Department, Employee and Address. Record's >>> entity type is identified by a field value. And I need to apply different >>> set of operations on each dataset. Ex., Department data may have >>> aggregations, Employee and Address data are simply joined together after >>> some filteration. >>> >>> If I have different datasets for each entity type the job is easy. So I >>> am trying to split incoming data to different datasets. What is the best >>> possible way to achieve this ? >>> >>> *Iterator can be read only once. >>> >>> >>> -- >>> Thank you, >>> Madan. >>> >> > > -- > Thank you, > Madan. >
