Hi, I understand that by default, the number of partitions = number of workers ^ 2. So, if we have N workers, each worker will process N partitions. I have a number of questions:
1- By default, does Giraph process the N partitions within a single worker sequentially? If yes, when setting the parameter giraph.numComputeThreads, will partitions within each thread be computed sequentially? 2- By default, does Giraph keep all partitions in memory? 3- If the answers to 1 and 2 are yes and yes, is there any advantage from using multiple partitions versus a single partition in the case of single threading per worker? 3- How does the out-of-core partitions affect out-of-core messages? Are they completely independent? For example, if the number of partitions to be kept in memory is set to a number less than N, and at the same time all messages are set to be kept in memory, will ALL messages be kept in memory, even those from out-of-core partitions? If the situation is reversed, where all partitions are kept in memory, and out-of-core messaging is set, will messages from memory-based partitions be saved on disk? 4- Is there a class like a PartitionContext, where you can access preSuperstep and postSuperstep *per partition*, along the lines of WorkerContext?
