How To Solve Issues Related to Log – Error loading watches index:

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Updated: Jan-20

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Troubleshooting background

To troubleshoot Elasticsearch log “Error loading watches index:” it’s important to understand common problems related to Elasticsearch concepts: indexing, plugin. See detailed explanations below complete with common problems, examples and useful tips.

Elasticsearch Indexing

What it is

Indexing is the process of adding or updating new documents to an Elasticsearch index.

Examples

In its simplest form, you can index a document like this:

POST /test/_doc
{
  "message": "Opster Rocks Elasticsearch Management"
}

This will create the index “test” (if it doesn’t already exist) and add a document with the source equal to the body of the POST call.  In this case, the ID will be created automatically. If you repeat this command, a second document will be created with an identical source but a different ID.
Alternatively, you can do this: 

PUT /test/_doc/1
{
  "message": "Opster Elasticsearch Management and Troubleshooting"
}

This is almost the same, but in this case, the call sets the ID of the document to 1.  If you repeat the command modifying the message, you will modify the original document, replacing the previous source with the latest source.

However note that this is NOT the same as an UPDATE operation, which is a different API and allows us to modify certain fields of the document while leaving others unchanged.

Notes and good things to know

You can set your own ID if necessary (especially if you later need to update the same ID) but this comes at a performance penalty.  If you don’t need to update documents, then let Elasticsearch set its own ID automatically.

If you need to index many documents at once, it is much more efficient to use the BULK API to carry out these operations with a single call.

Indexing is not an immediate Automatic process.  Documents will not be available for search until the index has refreshed. Refresh time by default is 1 second. Increasing this time reduces the burden on the cluster of indexing, increasing indexing speed. It is possible to modify the refresh time in the index settings.  

You can apply version control by setting the version parameter (?version=3) and indicating version_type=external.  By doing this Elasticsearch will reject any index requests where the version specified is less than the current version.  This can be useful when running distributed processes and you cannot guarantee that updated documents arrive in the correct order.

PUT test/_doc/1?version=20&version_type=external
{
	"message" : "using external version the document will be modified only  if version is greater than previous!"
}
The process of indexing is as follows:

The index request is sent to the primary shard. Once the primary shard is updated, then the replication process request will be relayed to the replica shards. The command will not return until the primary shard (at least) has been updated. For greater resilience, you can specify a minimum number of shard replicas to be available before proceeding with the operation by using the parameter ?wait_for_active_shards=2

You can also specify which specific shard the index operation is sent to by using the “routing” command.  There are 2 reasons that this might be done:  

  • Certain Elasticsearch functions (parent-child documents) that require that the parent and child documents be held on the same shard.  
  • Secondly, it may be possible to increase search speeds and reduce load on elasticsearch by storing similar documents together on the same shard and then specifying the routing for both indexing and searching.  Although this can be done explicitly during indexing, it is not recommended. It would be preferable to set this up using the index mapping, so that the routing is determined by an ID value on the source document.

Plugin in Elasticsearch

What it is

A plugin is used to enhance the core functionalities of Elasticsearch. Elasticsearch provides some core plugins as a part of their release installation. In addition to those core plugins, it is possible to write your own custom plugins as well. There are several community plugins available on GitHub for various use cases.

Examples:
  • Get all the instructions for the plugin usage
sudo bin/elasticsearch-plugin -h
  • Installing S3 plugin using URL for storing Elasticsearch snapshots on S3
sudo bin/elasticsearch-plugin install repository-s3
  • Removing a plugin
sudo bin/elasticsearch-plugin remove repository-s3
  • Installing a plugin using the file path
sudo bin/elasticsearch-plugin install file:///path/to/plugin.zip

Notes:
  • Plugins are installed and removed using the elasticsearch-plugin script, which ships as a part of Elasticsearch installation and can be found inside the bin/ directory of the Elasticsearch installation path.
  • A plugin has to be installed on every node of the cluster and each of the nodes has to be restarted to make the plugin visible.
  • You can also download the plugin manually and then install it using the elasticsearch-plugin install command, providing the file name/path of the plugin’s source file.
  • When a plugin is removed, you will need to restart every elasticsearch node in order to complete the removal process.

Common Problems:
  • Managing permission issues during and after plugin installation is the most common problem. If Elasticsearch was installed using the deb or rpm package then the plugin has to be installed using the root user, or else you can install the plugin as the user that owns all of the Elasticsearch files.
  • In case of deb or rpm package installation, it is important to check the permission of the plugins directory after plugin installation and update the permission if it has been modified using the following command:
chown -R elasticsearch:elasticsearch path_to_plugin_directory 
  • If your Elasticsearch nodes are running in a private subnet without internet access, you cannot install a plugin directly. In this case, you can simply download the plugins at once and copy the files inside the plugins directory of the Elasticsearch installation path on every node. The node has to be restarted in this case as well.

Index in Elasticsearch

What it is

In Elasticsearch, an index (indices in plural) can be thought of as a table inside a database that has 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 below command:

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

To help troubleshoot related issues we have gathered selected Q&A from the community and issues from Github , please review the following for further information :

1 Github Issue Number 32445  

2Errors After Updating To 6 2 4  


Log Context

Log ”Error loading watches index: [{}]” classname is WatcherIndexingListener.java
We have extracted the following from Elasticsearch source code to get an in-depth context :

                         configuration = INACTIVE;
                    } else {
                        checkWatchIndexHasChanged(metaData; event);
                    }
                } catch (IllegalStateException e) {
                    logger.error("error loading watches index: [{}]"; e.getMessage());
                    configuration = INACTIVE;
                }
            }
        } else {
            configuration = INACTIVE;






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