Falling back to allocating job by job counts because a memory requirement refresh could not be scheduled – 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 ” Falling back to allocating job by job counts because a memory requirement refresh could not be scheduled ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: memory, plugin and refresh.

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 “Falling back to allocating job [{}] by job counts because a memory requirement refresh could not be scheduled” classname is TransportOpenJobAction.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :

 
        // Try to allocate jobs according to memory usage; but if that's not possible (maybe due to a mixed version cluster or maybe
        // because of some weird OS problem) then fall back to the old mechanism of only considering numbers of assigned jobs
        boolean allocateByMemory = isMemoryTrackerRecentlyRefreshed;
        if (isMemoryTrackerRecentlyRefreshed == false) {
            logger.warn("Falling back to allocating job [{}] by job counts because a memory requirement refresh could not be scheduled";
                jobId);
        }

        List reasons = new LinkedList();
        long maxAvailableCount = Long.MIN_VALUE;




 

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