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Briefly, this error occurs when OpenSearch attempts to update the settings for an index after an upgrade, but the upgrade of some primary shards has failed. This could be due to issues like insufficient resources, network problems, or data corruption. To resolve this, you could try reindexing the data, increasing system resources, or checking the network connectivity. If data corruption is suspected, restore the data from a backup. Also, ensure that the OpenSearch version is compatible with the data nodes and shards.
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This guide will help you check for common problems that cause the log ” Not updating settings for the index [{}] because upgraded of some primary shards failed – ” to appear. To understand the issues related to this log, read the explanation below about the following OpenSearch concepts: shards, settings, index, upgrade, indices, admin.
Overview
Data in an OpenSearch index can grow to massive proportions. In order to keep it manageable, it is split into a number of shards. Each OpenSearch shard is an Apache Lucene index, with each individual Lucene index containing a subset of the documents in the OpenSearch index. Splitting indices in this way keeps resource usage under control. An Apache Lucene index has a limit of 2,147,483,519 documents.
Examples
The number of shards is set when an index is created, and this number cannot be changed later without reindexing the data. When creating an index, you can set the number of shards and replicas as properties of the index using:
PUT /sensor
{
"settings" : {
"index" : {
"number_of_shards" : 6,
"number_of_replicas" : 2
}
}
}The ideal number of shards should be determined based on the amount of data in an index. Generally, an optimal shard should hold 30-50GB of data. For example, if you expect to accumulate around 300GB of application logs in a day, having around 10 shards in that index would be reasonable.
During their lifetime, shards can go through a number of states, including:
- Initializing: An initial state before the shard can be used.
- Started: A state in which the shard is active and can receive requests.
- Relocating: A state that occurs when shards are in the process of being moved to a different node. This may be necessary under certain conditions, such as when the node they are on is running out of disk space.
- Unassigned: The state of a shard that has failed to be assigned. A reason is provided when this happens. For example, if the node hosting the shard is no longer in the cluster (NODE_LEFT) or due to restoring into a closed index (EXISTING_INDEX_RESTORED).
In order to view all shards, their states, and other metadata, use the following request:
GET _cat/shards
To view shards for a specific index, append the name of the index to the URL, for example:
sensor: GET _cat/shards/sensor
This command produces output, such as in the following example. By default, the columns shown include the name of the index, the name (i.e. number) of the shard, whether it is a primary shard or a replica, its state, the number of documents, the size on disk, the IP address, and the node ID.
sensor 5 p STARTED 0 283b 127.0.0.1 ziap sensor 5 r UNASSIGNED sensor 2 p STARTED 1 3.7kb 127.0.0.1 ziap sensor 2 r UNASSIGNED sensor 3 p STARTED 3 7.2kb 127.0.0.1 ziap sensor 3 r UNASSIGNED sensor 1 p STARTED 1 3.7kb 127.0.0.1 ziap sensor 1 r UNASSIGNED sensor 4 p STARTED 2 3.8kb 127.0.0.1 ziap sensor 4 r UNASSIGNED sensor 0 p STARTED 0 283b 127.0.0.1 ziap sensor 0 r UNASSIGNED
Notes and good things to know
- Having shards that are too large is simply inefficient. Moving huge indices across machines is both a time- and labor-intensive process. First, the Lucene merges would take longer to complete and would require greater resources. Moreover, moving the shards across the nodes for rebalancing would also take longer and recovery time would be extended. Thus by splitting the data and spreading it across a number of machines, it can be kept in manageable chunks and minimize risks.
- Having the right number of shards is important for performance. It is thus wise to plan in advance. When queries are run across different shards in parallel, they execute faster than an index composed of a single shard, but only if each shard is located on a different node and there are sufficient nodes in the cluster. At the same time, however, shards consume memory and disk space, both in terms of indexed data and cluster metadata. Having too many shards can slow down queries, indexing requests, and management operations, and so maintaining the right balance is critical.
How to reduce your OpenSearch costs by optimizing your shards
Watch the video below to learn how to save money on your deployment by optimizing your shards.
Quick links
Settings in OpenSearch
In OpenSearch, you can configure cluster-level settings, node-level settings and index level settings. Here is a quick rundown of each level.
A. Cluster settings
These settings can either be:
- Persistent, meaning they apply across restarts, or
- Transient, meaning they won’t survive a full cluster restart.
If a transient setting is reset, the first one of these values that is defined is applied:
- The persistent setting
- The setting in the configuration file
- The default value
The order of precedence for cluster settings is:
- Transient cluster settings
- Persistent cluster settings
- Settings in the opensearch.yml configuration file
Examples
An example of persistent cluster settings update:
PUT /_cluster/settings
{
"persistent" : {
"indices.recovery.max_bytes_per_sec" : "500mb"
}
}An example of a transient update:
PUT /_cluster/settings
{
"transient" : {
"indices.recovery.max_bytes_per_sec" : "40mb"
}
}B. Index settings
These are the settings that are applied to individual indices. There is an API to update index level settings.
Examples
The following API call will set the number of replica shards to 5 for my_index index.
PUT /my_index/_settings
{
"index" : {
"number_of_replicas" : 5
}
}To revert a setting to the default value, use null.
PUT /my_index/_settings
{
"index" : {
"refresh_interval" : null
}
}C. Node settings
These settings apply to nodes. Nodes can fulfill different roles. These include the master, data, and coordination roles. Node settings are set through the opensearch.yml file for each node.
Examples
Setting a node to be a data node (in the opensearch.yml file):
node.data: true
Disabling the ingest role for the node (which is enabled by default):
node.ingest: false
For production clusters, you will need to run each type of node on a dedicated machine with two or more instances of each, for HA (minimum three for master nodes).
Notes and good things to know
- Learning more about the cluster settings and index settings is important – it can spare you a lot of trouble. For example, if you are going to ingest huge amounts of data into an index and the number of replica shards is set to say, 5, the indexing process will be super slow because the data will be replicated at the same time it is indexed. What you can do to speed up indexing is to set the replica shards to 0 by updating the settings, and set it back to the original number when indexing is done, using the settings API.
- Another useful example of using cluster-level settings is when a node has just joined the cluster and the cluster is not assigning any shards to the node. Although shard allocation is enabled by default on all nodes, someone may have disabled shard allocation at some point (for example, in order to perform a rolling restart), and forgot to re-enable it later. To enable shard allocation, you can update the Cluster Settings API:
PUT /_cluster/settings
{"transient":{"cluster.routing.allocation.enable":"all"}}- It’s better to set cluster-wide settings with Settings API instead of with the opensearch.yml file and to use the file only for local changes. This will keep the same setting on all nodes. However, if you define different settings on different nodes by accident using the opensearch.yml configuration file, it is hard to notice these discrepancies.
- See also: Recovery
Quick links
Overview
In OpenSearch, an index (plural: indices) contains a schema and can have one or more shards and replicas. An OpenSearch 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 OpenSearch 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",
"OpenSearch"
],
"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, OpenSearch 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.
- OpenSearch 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 OpenSearch.yml:
action.destructive_requires_name: true
Log Context
Log “Not updating settings for the index [{}] because upgraded of some primary shards failed -” classname is TransportUpgradeAction.java.
We extracted the following from OpenSearch source code for those seeking an in-depth context :
Integer primaryCount = successfulPrimaryShards.get(index);
int expectedPrimaryCount = metadata.index(index).getNumberOfShards();
if (primaryCount == metadata.index(index).getNumberOfShards()) {
updatedVersions.put(index; new Tuple(versionEntry.getValue().v1(); versionEntry.getValue().v2().toString()));
} else {
logger.warn("Not updating settings for the index [{}] because upgraded of some primary shards failed - " +
"expected[{}]; received[{}]"; index; expectedPrimaryCount; primaryCount == null ? 0 : primaryCount);
}
}
return new UpgradeResponse(updatedVersions; totalShards; successfulShards; failedShards; shardFailures);
