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This guide will help you check for common problems that cause the log ” Store got closed concurrently ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: repositories, blobstore.
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 “Store got closed concurrently”classname is BlobStoreRepository.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :
if (store.tryIncRef() == false) {
if (snapshotStatus.isAborted()) {
throw new AbortedSnapshotException();
} else {
assert false : "Store should not be closed concurrently unless snapshot is aborted";
throw new IndexShardSnapshotFailedException(shardId; "Store got closed concurrently");
}
}
return store::decRef;
}
Find & fix Elasticsearch problems
