Couldnt schedule ML memory update node might be shutting down – How to solve related issues

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Couldnt schedule ML memory update node might be shutting down – How to solve related issues

Opster Team

Jan-20, Version: 1.7-8.0

Before you begin reading this guide, we recommend you run Elasticsearch Error Check-Up which can resolve issues that cause many errors.

This guide will help you check for common problems that cause the log ” Couldnt schedule ML memory update node might be shutting down ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: memory and plugin.

Advanced users might want to skip right to the common problems section in each concept or try running the Check-Up to analyze Elasticsearch configuration and help resolve this error.

Log Context

Log “Couldn’t schedule ML memory update – node might be shutting down” classname is MlMemoryTracker.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :

                 logger.debug("scheduling async refresh");
                threadPool.executor(executorName()).execute(
                    () -> refresh(clusterService.state().getMetaData().custom(PersistentTasksCustomMetaData.TYPE); listener));
                return true;
            } catch (EsRejectedExecutionException e) {
                logger.warn("Couldn't schedule ML memory update - node might be shutting down"; e);
            }
        }

        return false;
    }




 

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