Before you begin reading this guide, we recommend you run Elasticsearch Error Check-Up which analyzes 2 JSON files to detect many errors.
To easily locate the root cause and resolve this issue try AutoOps for Elasticsearch & OpenSearch. It diagnoses problems by analyzing hundreds of metrics collected by a lightweight agent and offers guidance for resolving them.
This guide will help you check for common problems that cause the log ” Unexpected failure during ; current state version ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: cluster, routing and version.
Overview
In Elasticsearch, routing refers to document routing. When you index a document, Elasticsearch will determine which shard the document should be routed to for indexing.
The shard is selected based on the following formula:
shard = hash(_routing) % number_of_primary_shards
Where the default value of _routing is _id.
It is important to know which shard the document is routed to, because Elasticsearch will need to determine where to find that document later on for document retrieval requests.
Examples
In twitter index with 2 primary shards, the document with _id equal to “440” gets routed to the shard number:
shard = hash( 440 ) % 2
PUT twitter/_doc/440
{
...
}Notes and good things to know
- In order to improve search speed, you can create custom routing. For example, you can enable custom routing that will ensure that only a single shard will be queried (the shard that contains your data).
- To create custom routing in Elasticsearch, you will need to configure and define that not all routing will be completed by default settings. ( v <= 5.0)
PUT my_index/customer/_mapping
{
"order":{
"_routing":{
"required":true
}
}
}- This will ensure that every document in the “customer” type must specify a custom routing. For Elasticsearch version 6 or above you will need to update the same mapping as:
PUT my_index/_mapping
{
"order":{
"_routing":{
"required":true
}
}
}Overview
A version corresponds to the Elasticsearch built-in tracking system that tracks the changes in each document’s update. When a document is indexed for the first time, it is assigned a version 1 using _version key. When the same document gets a subsequent update, the _version is incremented by 1 with every index, update or delete API call.
What it is used for
A version is used to handle the concurrency issues in Elasticsearch which come into play during simultaneous accessing of an index by multiple users. Elasticsearch handles this issue with an optimistic locking concept using the _version parameter to avoid letting multiple users edit the same document at the same time and protects users from generating incorrect data.
Notes
You cannot see the history of the document using _version. That means Elasticsearch does not use _version to keep a track of original changes that had been performed on the document. For example, if a document has been updated 10 times, it’s _version would be marked by Elasticsearch as 11, but you cannot go back and see what version 5 of the document looked like. This has to be implemented independently.
Common problems
If optimistic locking is not implemented while making updates to a document, Elasticsearch may return a conflict error with the 409 status code, which means that multiple users are trying to update the same version of the document at the same time.
POST /ratings/123?version=50
{
"name": "Joker",
"rating": 50
}
Log Context
Log “Unexpected failure during [{}]; current state version [{}]” classname is RoutingService.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
ClusterState state = clusterService.state();
if (logger.isTraceEnabled()) {
logger.error(() -> new ParameterizedMessage("unexpected failure during [{}]; current state:\n{}";
source; state); e);
} else {
logger.error(() -> new ParameterizedMessage("unexpected failure during [{}]; current state version [{}]";
source; state.version()); e);
}
}
});
} catch (Exception e) {
Find & fix Elasticsearch problems
