Unexpected error while indexing monitoring document – How to solve this Elasticsearch error

Overview

Indexing is the process of adding documents to and updating documents on 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.

Document in Elasticsearch

What is an Elasticsearch document?

While an SQL database has rows of data stored in tables, Elasticsearch stores data as multiple documents inside an index. This is where the analogy must end however, since the way that Elasticsearch treats documents and indices differs significantly from a relational database.

For example, documents could be:

• Products in an e-commerce index
• Log lines in a data logging application
• Invoice lines in an invoicing system

Document fields

Each document is essentially a JSON structure, which is ultimately considered to be a series of key:value pairs. These pairs are then indexed in a way that is determined by the document mapping. The mapping defines the field data type as text, keyword, float, time, geo point or various other data types.

Elasticsearch documents are described as schema-less because Elasticsearch does not require us to pre-define the index field structure, nor does it require all documents in an index to have the same structure. However, once a field is mapped to a given data type, then all documents in the index must maintain that same mapping type.

Each field can also be mapped in more than one way in the index. This can be useful because we may want a keyword structure for aggregations, and at the same time be able to keep an analysed data structure which enables us to carry out full text searches for individual words in the field.

For a full discussion on mapping please see here.

Document source

An Elasticsearch document _source consists of the original JSON source data before it is indexed. This data is retrieved when fetched by a search query.

Document metadata

Each document is also associated with metadata, the most important items being:

_index – The index where the document is stored

_id – The unique ID which identifies the document in the index

Documents and index architecture

Note that different applications could consider  a “document” to be a different thing.  For example, in an invoicing system, we could have an architecture which stores invoices as documents (1 document per invoice),  or we could have an index structure which stores multiple documents as “invoice lines” for each invoice. The choice would depend on how we want to store, map and query the data.

Examples:

Creating a document in the user’s index:

POST  /users/_doc 
{
    "name" : "Petey",
    "lastname" : "Cruiser",
    "email" : "petey@gmail.com"
}

In the above request, we haven’t mentioned an ID for the document so the index operation generates a unique ID for the document. Here _doc is the type of document.

POST  /users/_doc/1
{
    "name" : "Petey",
    "lastname" : "Cruiser",
    "email" : "petey@gmail.com"
}

In the above query, the document will be created with ID 1.

You can use the below ‘GET’ query to get a document from the index using ID:

GET  /users/_doc/1

Below is the result, which contains the document (in _source field) as metadata:

{
    "_index": "users",
    "_type": "_doc",
    "_id": "1",
    "_version": 1,    "_seq_no": 1,    "_primary_term": 1,
    "found": true,
    "_source": {
        "name": "Petey",
        "lastname": "Cruiser",
        "email": "petey@gmail.com"
    }
}

Notes

Starting version 7.0 types are deprecated, so for backward compatibility on version 7.x all docs are under type ‘_doc’, starting 8.x type will be completely removed from ES APIs.