Elastic Search: how to see the indexed data

Absolutely the easiest way to see your indexed data is to view it in your browser. No downloads or installation needed.

I'm going to assume your elasticsearch host is http://127.0.0.1:9200.

Step 1

Navigate to http://127.0.0.1:9200/_cat/indices?v to list your indices. You'll see something like this:

enter image description here

Step 2

Try accessing the desired index: http://127.0.0.1:9200/products_development_20160517164519304

The output will look something like this:

enter image description here

Notice the aliases, meaning we can as well access the index at: http://127.0.0.1:9200/products_development

Step 3

Navigate to http://127.0.0.1:9200/products_development/_search?pretty to see your data:

enter image description here


ElasticSearch data browser

Search, charts, one-click setup....


Probably the easiest way to explore your ElasticSearch cluster is to use elasticsearch-head.

You can install it by doing:

cd elasticsearch/
./bin/plugin -install mobz/elasticsearch-head

Then (assuming ElasticSearch is already running on your local machine), open a browser window to:

http://localhost:9200/_plugin/head/

Alternatively, you can just use curl from the command line, eg:

Check the mapping for an index:

curl -XGET 'http://127.0.0.1:9200/my_index/_mapping?pretty=1' 

Get some sample docs:

curl -XGET 'http://127.0.0.1:9200/my_index/_search?pretty=1' 

See the actual terms stored in a particular field (ie how that field has been analyzed):

curl -XGET 'http://127.0.0.1:9200/my_index/_search?pretty=1'  -d '
 {
    "facets" : {
       "my_terms" : {
          "terms" : {
             "size" : 50,
             "field" : "foo"
          }
       }
    }
 }

More available here: http://www.elasticsearch.org/guide

UPDATE : Sense plugin in Marvel

By far the easiest way of writing curl-style commands for Elasticsearch is the Sense plugin in Marvel.

It comes with source highlighting, pretty indenting and autocomplete.

Note: Sense was originally a standalone chrome plugin but is now part of the Marvel project.


Aggregation Solution

Solving the problem by grouping the data - DrTech's answer used facets in managing this but, will be deprecated according to Elasticsearch 1.0 reference.

Warning

Facets are deprecated and will be removed in a future release. You are encouraged to
migrate to aggregations instead.

Facets are replaced by aggregates - Introduced in an accessible manner in the Elasticsearch Guide - which loads an example into sense..

Short Solution

The solution is the same except aggregations require aggs instead of facets and with a count of 0 which sets limit to max integer - the example code requires the Marvel Plugin

# Basic aggregation
GET /houses/occupier/_search?search_type=count
{
    "aggs" : {
        "indexed_occupier_names" : {    <= Whatever you want this to be
            "terms" : {
              "field" : "first_name",    <= Name of the field you want to aggregate
              "size" : 0
            }
        }
    }
}

Full Solution

Here is the Sense code to test it out - example of a houses index, with an occupier type, and a field first_name:

DELETE /houses

# Index example docs
POST /houses/occupier/_bulk
{ "index": {}}
{ "first_name": "john" }
{ "index": {}}
{ "first_name": "john" }
{ "index": {}}
{ "first_name": "mark" }


# Basic aggregation
GET /houses/occupier/_search?search_type=count
{
    "aggs" : {
        "indexed_occupier_names" : {
            "terms" : {
              "field" : "first_name",
              "size" : 0
            }
        }
    }
}

Response

Response showing the relevant aggregation code. With two keys in the index, John and Mark.

    ....
    "aggregations": {
      "indexed_occupier_names": {
         "buckets": [
            {
               "key": "john",     
               "doc_count": 2     <= 2 documents matching
            },                        
            {
               "key": "mark",
               "doc_count": 1     <= 1 document matching
            }
         ]
      }
   }
   ....