Briefly, this error occurs when Elasticsearch encounters an issue while trying to create a snapshot, which could be due to insufficient disk space, network connectivity issues, or incorrect snapshot repository configuration. To resolve this, ensure there’s enough disk space and stable network connection. Also, check the snapshot repository configuration for any errors. If the snapshot task is stuck, you may need to manually delete the task from the task management API. Lastly, check Elasticsearch logs for more specific error details.
This guide will help you check for common problems that cause the log ” snapshot task [%s] unexpectedly failed ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: task, blobstore, repositories, snapshot.
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
An Elasticsearch snapshot provides a backup mechanism that takes the current state and data in the cluster and saves it to a repository (read snapshot for more information). The backup process requires a repository to be created first. The repository needs to be registered using the _snapshot endpoint, and multiple repositories can be created per cluster. The following repository types are supported:
Repository types
| Repository type | Configuration type |
|---|---|
| Shared file system | Type: “fs” |
| S3 | Type : “s3” |
| HDFS | Type :“hdfs” |
| Azure | Type: “azure” |
| Google Cloud Storage | Type : “gcs” |
Examples
To register an “fs” repository:
PUT _snapshot/my_repo_01
{
"type": "fs",
"settings": {
"location": "/mnt/my_repo_dir"
}
}Notes and good things to know
- S3, HDFS, Azure and Google Cloud require a relevant plugin to be installed before it can be used for a snapshot.
- The setting, path.repo: /mnt/my_repo_dir needs to be added to elasticsearch.yml on all the nodes if you are planning to use the repo type of file system. Otherwise, it will fail.
- When using remote repositories, the network bandwidth and repository storage throughput should be high enough to complete the snapshot operations normally, otherwise you will end up with partial snapshots.
Log Context
Log “snapshot task [%s] unexpectedly failed” classname is ShardSnapshotTaskRunner.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
}
@Override
public void onFailure(Exception e) {
assert false : e;
logger.error(Strings.format("snapshot task [%s] unexpectedly failed"; this); e);
}
}
class ShardSnapshotTask extends SnapshotTask {
ShardSnapshotTask(SnapshotShardContext context) {
