Introduction
Elasticsearch, a popular search and analytics engine, provides robust support for handling arrays in documents. Arrays are a common data structure used to store multiple values in a single field. In this article, we will discuss advanced techniques and best practices for working with arrays in Elasticsearch. If you want to learn about term query does not support array of values – how to solve this Elasticsearch error, check out this guide.
Advanced techniques and best practices
1. Mapping Arrays
Elasticsearch automatically detects arrays and does not require a specific mapping for them. When you index a document containing an array field, Elasticsearch will automatically create a mapping for that field. However, it is recommended to define the mapping explicitly to avoid any unexpected behavior.
To define a mapping for an array field, there’s nothing special to do, you can just define a normal field as in the following example:
PUT /my_index
{
"mappings": {
"properties": {
"tags": {
"type": "keyword"
}
}
}
}In this example, we define a mapping for the `tags` field, which can either hold a single keyword or an array of keywords.
2. Indexing Arrays
When indexing a document with an array field, you can simply provide the array as the value for that field. For example:
PUT /my_index/_doc/1
{
"tags": ["elasticsearch", "search", "analytics"]
}In this example, we index a document with an array of tags.
3. Querying Arrays
Elasticsearch treats arrays as if each value were indexed separately. This means that you can use standard query types to search for values within an array. For example, you can use a `terms` query to search for documents with specific tags:
GET /my_index/_search
{
"query": {
"terms": {
"tags": ["elasticsearch", "search"]
}
}
}This query will return documents that have either “elasticsearch” or “search” in their `tags` array.
4. Nested Arrays
Elasticsearch supports nested arrays, which are arrays of objects. To work with nested arrays, you need to define a nested mapping for the field containing the array. For example:
PUT /my_index
{
"mappings": {
"properties": {
"comments": {
"type": "nested",
"properties": {
"author": {
"type": "keyword"
},
"text": {
"type": "text"
}
}
}
}
}
}In this example, we define a nested mapping for the `comments` field, which is an array of objects with `author` and `text` properties.
5. Querying Nested Arrays
To query nested arrays, you need to use the `nested` query type. This allows you to search for documents based on the properties of objects within the nested array. For example:
GET /my_index/_search
{
"query": {
"nested": {
"path": "comments",
"query": {
"bool": {
"must": [
{
"match": {
"comments.author": "John Doe"
}
},
{
"match": {
"comments.text": "elasticsearch"
}
}
]
}
}
}
}
}This query will return documents where the `comments` array contains an object with an `author` of “John Doe” and a `text` containing the word “elasticsearch”.
6. Updating Arrays
To update an array field in a document, you can use the `update` API with a script. For example, to add a new tag to the `tags` array, you can use the following script:
POST /my_index/_update/1
{
"script": {
"source": "ctx._source.tags.add(params.tag)",
"params": {
"tag": "new_tag"
}
}
}This script will add the “new_tag” value to the `tags` array in the document with ID 1.
Conclusion
In conclusion, Elasticsearch provides powerful support for handling arrays in documents. By understanding how to define mappings, index, query, and update arrays, you can effectively work with this versatile data structure in your Elasticsearch applications. Remember to define your mappings explicitly and use the appropriate query types for nested arrays to ensure accurate and efficient search results.
