Hi, I have recently tried to upgrade Flink from 1.2.0 to the newest version and noticed that starting from the version 1.5 the performance is much worse when processing fixed graphs in a standalone JVM environment (Java 8).
This affects all the use-cases when a Gelly graph (pre-built from a fixed collection of nodes/edges) gets processed by any of our custom algorithms (VertexCentric, ScatterGather or GSA), especially when using parallel processing for a local ExecutionEnvironment. The processing times (compared to the versions <= 1.4.2) double/triple, while CPU and memory consumption increase significantly. Are there any fine-tuning steps/tricks for the job processing engine behind Flink 1.5+ that would improve the performance in the scenarios described above? Best, Jakub
