One of previous posts presented partitioning strategies. Among described techniques we could find hashing partitioning based on the number of servers. The drawback of this method was the lack of flexibility. With the add of new server we have to remap all data. Fortunately an alternative to this "primitive" hashing exists and it's called consistent hashing.
Every data processing pipeline can have a source of contention. One of them can be the data localization. When all entries are read from single place by dozens or hundreds of workers, the data source can respond slower. One of solutions to this problem can be the partitioning.