Starting template upgrade to version templates will be updated and will be removed – How to solve this Elasticsearch error

If you want to learn more about Elasticsearch templates, check out this guide.

Overview

A template in Elasticsearch falls into one of the two following categories and is indexed inside Elasticsearch using its dedicated endpoint: 

1. Index templates, which are a way to define a set of rules including index settings, mappings and an index pattern. The template is applied automatically whenever a new index is created with the matching pattern. Templates are also used to dynamically apply custom mapping for the fields which are not predefined inside existing mapping.
2. Search templates, which help in defining templates for search queries using mustache scripting language. These templates act as a placeholder for variables defined inside the search queries.

Examples

Create a dynamic index template

PUT /_template/template_1?pretty
{
  "index_patterns": [
    "logs*",
    "api*"
  ],
  "settings": {
    "number_of_shards": 2
  },
  "mappings": {
    "dynamic_templates": [
      {
        "strings": {
          "match_mapping_type": "string",
          "mapping": {
            "type": "keyword"
          }
        }
      }
    ],
    "properties": {
      "host_name": {
        "type": "keyword"
      },
      "created_at": {
        "type": "date"
      }
    }
  }
}

Create a search template

POST /_scripts/search_template_1?pretty
{
    "script": {
        "lang": "mustache",
        "source": {
            "query": {
                "match": {
                    "description": "{{query_string}}"
                }
            }
        }
    }
}

Executing a search query using search template

GET /_search/template?pretty
{
    "id": "search_template_1", 
    "params": {
        "query_string": "hello world"
    }
}

The search request will be executed by default on all the indices available in the cluster and can be limited to particular indices using an index parameter.

Notes

• A dynamic index template is always useful when you do not know the field names in advance and want to control their mapping as per the business use case.

Overview

Upgrade refers to migrating your Elasticsearch version to a newer version. The process of updating distributed systems like Elasticsearch can be intricate, given the extensive data quantities, the involvement of numerous nodes, and the diverse configurations that may exist within your cluster.

An upgrade of an existing cluster can be done in two ways: through a rolling upgrade and through a full cluster restart. The benefit of a rolling upgrade is having zero downtime.

Bear in mind that any changes to your system could lead to data loss if the instructions are not adhered to accurately. Thoroughly test and strategize your upgrade, and ensure you create a backup of your data prior to executing any updates.

For guides on how to upgrade specific versions, see:

1. How to Upgrade Elasticsearch from Version 5 to Version 6
2. How to Upgrade Elasticsearch from Version 6 to Version 7
3. How to Upgrade Elasticsearch from Version 7 to Version 8

What should I check before upgrading versions?

Elasticsearch nodes cannot be downgraded after upgrading. Before starting the upgrade process you should: 

• Check the deprecation log and resolve any issues.
• Review the breaking changes to make sure you know of any functionalities which may changes or disappear. This would mainly affect node configuration, index mappings and templates, and cluster settings.
• Check the ES plugin compatibility to ensure they are compatible with the new version.
• Set up a test environment to test the upgrade process in a testing or staging environment first before upgrading your production cluster to avoid any issues.
• Take a backup and snapshots from your data, as the only way to “reverse” a failed upgrade is to create a new cluster with the old version and restore the data from snapshots.

How to perform offline upgrades – full cluster restart upgrades

A complete cluster restart upgrade involves simultaneously stopping all Elasticsearch nodes, updating them, and subsequently restarting each one. Inevitably, this upgrade approach will necessitate the downtime of your Elasticsearch cluster throughout the entire process.

Generally, offline upgrades are simpler than online ones because there’s no need to handle a cluster with varying node versions concurrently.

The steps are:

1. Disable shard allocation 
2. Stop all Elasticsearch nodes and upgrade them 
3. Upgrade any plugins
4. Start the Elasticsearch cluster
5. Re-enable shard allocation 
6. Upgrade client libraries to new version
7. Restart master eligible nodes
8. Restart non-master eligible nodes

Keep in mind that during a full cluster restart, the master nodes need to be initiated prior to the non-master nodes. This is essential for allowing the master nodes to establish the cluster so that other nodes can join, which is in contrast to a rolling upstart where non-master nodes should be upgraded before the master nodes.

How to perform online upgrades – rolling restart upgrades

A rolling restart upgrade allows for updating a cluster without incurring any downtime. In this scenario, every node is sequentially upgraded and rebooted, without ever halting the entire Elasticsearch cluster.

Rolling restart upgrades cannot be performed when there is a change in MAJOR versions, except for specific exceptions:

• Upgrading Elasticsearch version 5.6.16 to version 6.x.x
• Upgrading Elasticsearch version 6.8.23 to version 7.x.x
• Upgrading Elasticsearch version 7.17.5 to version 8.x.x

For this reason, when performing a rolling restart upgrade between major versions, it is imperative to ALWAYS utilize the most recent minor version as an intermediary step for upgrading to the subsequent major version. For instance, if you are operating Elasticsearch 5.x.x, you can first update to 5.6.16 and then proceed to 6.8.23.

How to upgrade nodes in a rolling upgrade

To disable shard allocation, run:

PUT _cluster/settings
{
  "persistent": {
    "cluster.routing.allocation.enable": "primaries"
  }
}

To re-enable shard allocation, run:

PUT _cluster/settings
{
  "persistent": {
    "cluster.routing.allocation.enable": null
  }
}

Get cluster status and see how many nodes are in the cluster using:

GET _cluster/health

Common problems and important points

• The major problem with upgrades is version incompatibility. Elasticsearch supports rolling upgrades only between minor versions. You need to make sure to go through the official documentation to see if your cluster can support a rolling upgrade, otherwise a complete reindexing is required.
• Once you upgrade an Elasticsearch node, a rollback cannot be done. You need to make sure to backup your data before an upgrade.
• Elasticsearch continuously removes or deprecates some of its features with every release, so keep an eye on the change logs of each version before planning an upgrade. 
• While doing a rolling upgrade, it is important to disable shard allocation before stopping a node and enable the shard allocation when node is upgraded and restarted. This process helps in avoiding unnecessary IO load in the cluster.

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
}