Re: [DISCUSS] Spark cannot identify the problem executor

In spark 2.3 with blacklist enabled this is a common problem when executor A has some problem, for instance let’s say there’s some connection issue. Tasks on executor B, executor C will fail saying cannot read from executor

Re: [DISCUSS] Spark cannot identify the problem executor

The FetchFailed error of Task B will be forwarded to DAGScheduler too. The FetchFailed already means the output missing of the stage. So DAGScheduler will reschedule the upstream stage, which would reschedule the upstream task of Task B at the end. On Mon, Sep 14, 2020 at 10:39 AM 陈晓宇 wrote: >

Re: [DISCUSS] Spark cannot identify the problem executor

What do you mean by "read from executor A"? I can think of several paths for an executor to read something from another remote executor: 1. shuffle data If the executor fails to fetch the shuffle data, I think it will result in the FetchFiled for the task. For this case, blacklist can identify

Re: [DISCUSS] Spark cannot identify the problem executor

-dev, +user Executors do not communicate directly, so I don't think that's quite what you are seeing. You'd have to clarify. On Fri, Sep 11, 2020 at 12:08 AM 陈晓宇 wrote: > > Hello all, > > We've been using spark 2.3 with blacklist enabled and often meet the problem > that when executor A has