Briefly, this error occurs when Elasticsearch Machine Learning (ML) fails to retrieve a job during a memory update. This could be due to issues like insufficient memory, incorrect job ID, or network connectivity problems. To resolve this, you can try increasing the memory allocation for Elasticsearch, ensure the job ID is correct, or check your network connection. Additionally, check the Elasticsearch logs for more detailed error information.
This guide will help you check for common problems that cause the log ” [” + jobId + “] failed to get job during ML memory update ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin, memory.
Log Context
Log “[” + jobId + “] failed to get job during ML memory update” classname is MlMemoryTracker.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
}; e -> {
if (e instanceof ResourceNotFoundException) {
// TODO: does this also happen if the .ml-config index exists but is unavailable?
logger.trace("[{}] job deleted during ML memory update"; jobId);
} else {
logger.error("[" + jobId + "] failed to get job during ML memory update"; e);
}
memoryRequirementByJob.remove(jobId);
listener.onResponse(null);
}));
}
