Unexpected IndexOrAlias for – How to solve related issues

Quick links:

• Overview – Data Stream Aliases and Index Aliases
• Creating and removing aliases
• Alias use cases
  • Filter-based aliases to limit access to data
  • Combining routing with aliases
  • Transitioning to new indices
  • Creating sliding windows into distinct indices
  • Aliases and ILM for updating or deleting documents
  • Querying data from a frozen index
• Notes and common problems

Overview

In Elasticsearch, an alias is a secondary name given that refers to a group of data streams or indices. Aliases can be created and removed dynamically using _aliases REST endpoint.

There are two types of aliases:

• Data Stream Aliases: An alias for a data stream refers to one or more data streams. The names of data streams will be referred to by data stream aliases. In the cluster state, data stream aliases are kept distinct from data streams.
• Index Aliases: An index alias points to one or more indices.

The master node manages the cluster state, which includes aliases.

Creating and removing aliases

Creating an alias on a single index:

POST /_aliases?pretty
{
  "actions": [
    {
      "add": {
        "index": "index_1",
        "alias": "alias_1"
      }
    }
  ]
}

Creating an alias that is tied to more than one index:

POST /_aliases?pretty
{
  "actions": [
    {
      "add": {
        "index": "index_1",
        "alias": "alias_1"
      }
    },
    {
      "add": {
        "index": "index_2",
        "alias": "alias_1"
      }
    }
  ]
}

Listing out all of the available aliases in an Elasticsearch cluster:

GET _cat/aliases

Removing an alias:

POST /_aliases?pretty
{
  "actions": [
    {
      "remove": {
        "index": "index_2",
        "alias": "alias_1"
      }
    }
  ]
}

Alias use cases

Aliases are used for multiple purposes such as to search across more than one index with a single name, perform the reindexing process with zero downtime and query data based on predefined filters. Below are 6 different use cases for aliases.

1. Filter-based aliases to limit access to data

One use case is making a filter-based alias, which is quite useful when you need to limit access to data. When a query is executed, an alias can apply a filter automatically.

For example, consider an index named `opster-idx`, having an alias that points to the groups that contain the `opster` company, so you can create an alias that handles this filtering automatically as shown in the steps below.

Index documents:

PUT /opster-idx/_doc/1
{
    "title": "Taking Care of Your Entire Search Operation",
    "company": "Opster"
}

PUT /opster-idx/_doc/2
{
    "title": "Streaming service",
    "company": "XYZ"
}

Add the query to the actions in the `filter` param to create a filter alias. The query here is used to limit the documents that the alias can access.

POST /_aliases?pretty
{
 "actions": [
   {
     "add": {
       "index": "opster-idx",
       "alias": "opster-alias",
       "filter": {
         "term": {
           "company": "opster"
         }
       }
     }
   }
 ]
}

While you perform a match-all query on `opster-alias`, only the documents that match the term query (which was added when building filter alias, i.e. documents with company name equal to `opster`) will appear in the search results.

Search query:

GET opster-alias/_search
{
    "query":{
        "match_all":{}
    }
}

Search response:

 "hits": {
        "total": {
            "value": 1,
            "relation": "eq"
        },
        "max_score": 1.0,
        "hits": [
            {
                "_index": "opster-idx",
                "_id": "1",
                "_score": 1.0,
                "_source": {
                    "title": "Taking Care of Your Entire Search Operation",
                    "company": "Opster"
                }
            }
        ]
    }

Now if you try to query those documents that have the company name, “XYZ”, as follows:

GET opster-alias/_search
{
    "query": {
        "match": {
            "company": "XYZ"
        }
    }
}

The search response will be:

"hits": {
        "total": {
            "value": 0,
            "relation": "eq"
        },
        "max_score": null,
        "hits": []
    }

2. Combining routing with aliases

When searching and indexing, the following example will filter out the company `opster` and add `1` to the route to limit where searches are done.

Routing is a string value that is used to route indexing and search operations to a specific shard.

POST /_aliases?pretty
{
   "actions": [
       {
           "add": {
               "index": "index_1",
               "alias": "alias_2",
               "filter": {
                   "term": {
                       "company": "opster"
                   }
               },
               "routing": "1"
           }
       }
   ]
}

3. Transitioning to new indices

You can use aliases when your application needs to seamlessly transition from an old index to a new index with no downtime.

4. Creating sliding windows into distinct indices

For example, if you construct daily indices for your data, you might wish to establish an alias named `last-7-days` to produce a sliding window of the data from the previous seven days. Then, each day, when you create a new daily index, you may add it to the alias and delete the 8-day old index at the same time.

5. Aliases and ILM for updating or deleting documents

You can use an index alias and index template with ILM to manage and roll over the alias’s indices if you need to update or delete existing documents across numerous indices frequently.

6. Querying data from a frozen index

When using ILM, If you still need to query data from a frozen index, you can use the alias to do so. Instead of searching for data directly through that index, you may run a search query on the alias, which will increase performance and allow you to get a response with fewer resources.

Notes

• An Alias cannot be used for the indexing process if it points to more than one index. If attempted, Elasticsearch will throw an exception.
• Deleting an alias does not delete the actual index.

Common problems

When you try to index a document into an alias that points to more than one index, Elasticsearch returns an error because it doesn’t know which concrete index the document should be indexed to.

You will get the following error message:

{
  "error" : {
    "root_cause" : [
      {
        "type" : "illegal_argument_exception",
        "reason" : "no write index is defined for alias [my-alias]. The write index may be explicitly disabled using is_write_index=false or the alias points to multiple indices without one being designated as a write index"
      }
    ],
    "type" : "illegal_argument_exception",
    "reason" : "no write index is defined for alias [my-alias]. The write index may be explicitly disabled using is_write_index=false or the alias points to multiple indices without one being designated as a write index"
  },
  "status" : 400
}

For a full troubleshooting guide on how to resolve this error, see here.

Index and indexing in Elasticsearch - 3 min

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

DELETE /*

action.destructive_requires_name: true

Overview

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 of the instructions for the plugin:

sudo bin/elasticsearch-plugin -h

Installing the S3 plugin 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’s path:

sudo bin/elasticsearch-plugin install file:///path/to/plugin.zip

Notes and good things to know

• Plugins are installed and removed using the elasticsearch-plugin script, which ships as a part of the 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 issues

• Managing permission issues during and after plugin installation is the most common problem. If Elasticsearch was installed using the DEB or RPM packages then the plugin has to be installed using the root user. Otherwise you can install the plugin as the user that owns all of the Elasticsearch files.
• In the case of DEB or RPM package installation, it is important to check the permissions of the plugins directory after you install it. You can 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 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.