Nested objects look similar to plain objects but they differ in mapping and the way they are stored internally in Elasticsearch.
We will work with the same Twitter data but this time we will index it in a nested structure. We will have a user as our root object and every user can have multiple tweets as nested documents. Indexing this kind of data without using nested mapping will lead to problems, as shown in the following example:
PUT /twitter/tweet/1
{
"user": {
"screen_name": "d_bharvi",
"followers_count": "2000",
"created_at": "2012-06-05"
},
"tweets": [
{
"id": "121223221",
"text": "understanding nested relationships",
"created_at": "2015-09-05"
},
{
"id": "121223222",
"text": "NoSQL databases are awesome",
"created_at": "2015-06-05"
}
]
}
PUT /twitter/tweet/2
{
"user": {
"screen_name": "d_bharvi",
"followers_count": "2000",
"created_at": "2012-06-05"
},
"tweets": [...