Briefly, this error occurs when Elasticsearch encounters an unexpected issue while trying to complete a write task after a delay. This could be due to a variety of reasons such as insufficient disk space, network issues, or a problem with the underlying storage system. To resolve this issue, you can try freeing up disk space, checking the network connectivity, or investigating the health of your storage system. Additionally, check the Elasticsearch logs for more detailed information about the error. It’s also advisable to ensure your Elasticsearch version is up-to-date as this could be a bug that’s been fixed in a newer version.
This guide will help you check for common problems that cause the log ” unexpected exception while completing write task after delay ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: task, bulk.
Overview
A task is an Elasticsearch operation, which can be any request performed on an Elasticsearch cluster, such as a delete by query request, a search request and so on. Elasticsearch provides a dedicated Task API for the task management which includes various actions, from retrieving the status of current running tasks to canceling any long running task.
Examples
Get all currently running tasks on all nodes of the cluster
Apart from other information, the response of the below request contains task IDs of all the tasks which can be used to get detailed information about the particular task in question.
GET _tasks
Get detailed information of a particular task
Where clQFAL_VRrmnlRyPsu_p8A:1132678759 is the ID of the task in below request
GET _tasks/clQFAL_VRrmnlRyPsu_p8A:1132678759
Get all the current tasks running on particular nodes
GET _tasks?nodes=nodeId1,nodeId2
Cancel a task
Where clQFAL_VRrmnlRyPsu_p8A:1132678759 is the ID of the task in the below request
POST /_tasks/clQFAL_VRrmnlRyPsu_p8A:1132678759/_cancel?pretty
Notes
- The Task API will be most useful when you want to investigate the spike of resource utilization in the cluster or want to cancel an operation.
Overview
In Elasticsearch, when using the Bulk API it is possible to perform many write operations in a single API call, which increases the indexing speed. Using the Bulk API is more efficient than sending multiple separate requests. This can be done for the following four actions:
- Index
- Update
- Create
- Delete
Examples
The bulk request below will index a document, delete another document, and update an existing document.
POST _bulk
{ "index" : { "_index" : "myindex", "_id" : "1" } }
{ "field1" : "value" }
{ "delete" : { "_index" : "myindex", "_id" : "2" } }
{ "update" : {"_id" : "1", "_index" : "myindex"} }
{ "doc" : {"field2" : "value5"} }Notes
- Bulk API is useful when you need to index data streams that can be queued up and indexed in batches of hundreds or thousands, such as logs.
- There is no correct number of actions or limits to perform on a single bulk call, but you will need to figure out the optimum number by experimentation, given the cluster size, number of nodes, hardware specs etc.
Log Context
Log “unexpected exception while completing write task after delay” classname is WriteAckDelay.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
logger.trace("completing {} writes"; tasks.size());
for (Runnable task : tasks) {
try {
task.run();
} catch (Exception e) {
logger.error("unexpected exception while completing write task after delay"; e);
}
}
}
}
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