Multiple reshuffles are ignored in some cases on Flink batch runner.

Multiple reshuffles are ignored in some cases on Flink batch runner. This may lead to huge performace penalty in IO connectors (when reshuffling splits).

In flink optimizer, when we `.rebalance()` dataset, is output channel is marked as `FORCED_REBALANCED`. When we chain this with another `.rebalance()`, the latter is ignored because it's source is already `FORCED_REBALANCED`, thus requested property is met. This is correct beaviour because rebalance is idempotent.

When we include `flatMap` in between rebalances -> `.rebalance().flatMap(...).rebalance()`, we need to reshuffle again, because dataset distribution may have changed (eg. you can possibli emit unbouded stream from a single element). Unfortunatelly `flatMap` output is still incorrectly marked as `FORCED_REBALANCED` and the second reshuffle gets ignored.

This especially affects IO connectors -> `FileIO.match()` returns reshuffled list of matched files -> we split each file into ranges -> *reshuffle* -> read. Ignoring the second reshuffle leads to huge perf. degradation (5m -> 2h in one of our production pipelines)