Briefly, this error occurs when the Elasticsearch node has metadata indicating an older index version than the current one. This could be due to a failed upgrade or a node rejoining the cluster after a long period. To resolve this, you can try to upgrade the node again, ensuring all steps are correctly followed. Alternatively, you can remove the node from the cluster, delete its data directory, and re-add it to the cluster. However, ensure you have a backup of your data before performing these operations.
This guide will help you check for common problems that cause the log ” oldest index version recorded in NodeMetadata {} ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: metadata, index, version, node.
Overview
Metadata in Elasticsearch refers to additional information stored for each document. This is achieved using the specific metadata fields available in Elasticsearch. The default behavior of some of these metadata fields can be customized during mapping creation.
Examples
Using _meta meta-field for storing application-specific information with the mapping:
PUT /my_index?pretty
{
"mappings": {
"_meta": {
"domain": "security",
"release_information": {
"date": "18-01-2020",
"version": "7.5"
}
}
}
}Notes
- In version 2.x, Elasticsearch had a total 13 meta fields available, which are: _index, _uid, _type, _id, _source, _size, _all, _field_names, _timestamp, _ttl, _parent, _routing, _meta
- In version 5.x, _timestamp and _ttl meta fields were removed.
- In version 6.x, the _parent meta field was removed.
- In version 7.x, _uid and _all meta fields were removed.
Overview
In Elasticsearch, an index (plural: indices) contains a schema and can have one or more shards and replicas. An Elasticsearch index is divided into shards and each shard is an instance of a Lucene index.
Indices are used to store the documents in dedicated data structures corresponding to the data type of fields. For example, text fields are stored inside an inverted index whereas numeric and geo fields are stored inside BKD trees.
Examples
Create index
The following example is based on Elasticsearch version 5.x onwards. An index with two shards, each having one replica will be created with the name test_index1
PUT /test_index1?pretty
{
"settings" : {
"number_of_shards" : 2,
"number_of_replicas" : 1
},
"mappings" : {
"properties" : {
"tags" : { "type" : "keyword" },
"updated_at" : { "type" : "date" }
}
}
}List indices
All the index names and their basic information can be retrieved using the following command:
GET _cat/indices?v
Index a document
Let’s add a document in the index with the command below:
PUT test_index1/_doc/1
{
"tags": [
"opster",
"elasticsearch"
],
"date": "01-01-2020"
}Query an index
GET test_index1/_search
{
"query": {
"match_all": {}
}
}Query multiple indices
It is possible to search multiple indices with a single request. If it is a raw HTTP request, index names should be sent in comma-separated format, as shown in the example below, and in the case of a query via a programming language client such as python or Java, index names are to be sent in a list format.
GET test_index1,test_index2/_search
Delete indices
DELETE test_index1
Common problems
- It is good practice to define the settings and mapping of an Index wherever possible because if this is not done, Elasticsearch tries to automatically guess the data type of fields at the time of indexing. This automatic process may have disadvantages, such as mapping conflicts, duplicate data and incorrect data types being set in the index. If the fields are not known in advance, it’s better to use dynamic index templates.
- Elasticsearch supports wildcard patterns in Index names, which sometimes aids with querying multiple indices, but can also be very destructive too. For example, It is possible to delete all the indices in a single command using the following commands:
DELETE /*
To disable this, you can add the following lines in the elasticsearch.yml:
action.destructive_requires_name: 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 “oldest index version recorded in NodeMetadata {}” classname is NodeEnvironment.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
);
}
metadata.verifyUpgradeToCurrentVersion();
logger.info("oldest index version recorded in NodeMetadata {}"; metadata.oldestIndexVersion());
if (metadata.oldestIndexVersion().isLegacyIndexVersion()) {
throw new IllegalStateException(
"Cannot start this node because it holds metadata for indices with version ["
+ metadata.oldestIndexVersion()
