Could not start dataframe allocation explanation – How to solve this Elasticsearch exception

Opster Team

August-23, Version: 7.2-7.4

Briefly, this error occurs when Elasticsearch is unable to start a data frame analytics job due to insufficient resources or improper allocation. This could be due to low disk space, insufficient memory, or incorrect node allocation. To resolve this issue, you can try increasing the disk space or memory, checking the node allocation settings, or redistributing the load across multiple nodes. Additionally, ensure that the Elasticsearch cluster is properly configured and that there are no network connectivity issues.

This guide will help you check for common problems that cause the log ” Could not start dataframe; allocation explanation [ ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin, allocation.

Log Context

Log “Could not start dataframe; allocation explanation [” class name is We extracted the following from Elasticsearch source code for those seeking an in-depth context :

 if (assignment != null &&
 assignment.equals(PersistentTasksCustomMetaData.INITIAL_ASSIGNMENT) == false &&
 assignment.isAssigned() == false) {
 // For some reason; the task is not assigned to a node; but is no longer in the `INITIAL_ASSIGNMENT` state
 // Consider this a failure.
 exception = new ElasticsearchStatusException("Could not start dataframe; allocation explanation [" +
 assignment.getExplanation() + "]"; RestStatus.TOO_MANY_REQUESTS);
 return true;
 // We just want it assigned so we can tell it to start working
 return assignment != null && assignment.isAssigned() && isNotStopped(persistentTask);


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