Related
I am facing issues with elasticsearch aggregation grouping inside top_hits. or i need unique students count in the tophits
Elastic search mapping:
{
"board" : {
"properties" : {
"notApplied" : {
"type" : "date"
}
}
}
}
Query :
{
"size": 0,
"query": {},
"aggs": {
"notApplied": {
"filter": {
"exists": {
"field": "board.notApplied"
}
},
"aggs": {
"top_student_hits": {
"top_hits": {
"sort": [
{
"board.notApplied": {
"order": "desc"
}
}
],
"script_fields": {
"dues": {
"script": {
"source": "if (doc.containsKey('board.notApplied') && doc['board.notApplied'].size() != 0) { (doc['board.notApplied'].value.toInstant().toEpochMilli()-params.date)/86400000 } else { 0; }",
"params": {
"date": 1669939199059 // --> < 1 day
}
}
}
},
"_source": {
"includes": [
"id",
"studentName",
"usercode",
"board.notApplied",
"userId"
]
},
"size": 5
}
}
}
}
}
}
Output for the above query :
{
"took" : 11,
...
"aggregations" : {
"notApplied" : {
"doc_count" : 42,
"top_student_hits" : {
"hits" : {
"total" : {
"value" : 42,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "applications",
"_type" : "_doc",
"_id" : "4b85533822f91e9b99392f16dedaae1f",
"_score" : null,
"_source" : {
"board" : {
"notApplied" : "2022-10-25T00:00:00.000Z"
},
"studentName" : "Joe",
"id" : "4b85533822f91e9b99392f16dedaae1f",
"userId" : "45a47d1314041ab287a277679ff19922"
},
"fields" : {
"dues" : [
-37
]
},
"sort" : [
1666656000000
]
},
{
"_index" : "applications",
"_type" : "_doc",
"_id" : "1897f32d2d7f691e42c3fe6ebe631c7d",
"_score" : null,
"_source" : {
"board" : {
"notApplied" : "2022-10-25T00:00:00.000Z"
},
"studentName" : "Joe",
"id" : "1897f32d2d7f691e42c3fe6ebe631c7d",
"userId" : "45a47d1314041ab287a277679ff19922"
},
"fields" : {
"dues" : [
-37
]
},
"sort" : [
1666656000000
]
},
{
"_index" : "applications",
"_type" : "_doc",
"_id" : "f0b25dc9a911782ace5af36db7bfbc1f",
"_score" : null,
"_source" : {
"board" : {
"notApplied" : "2022-10-25T00:00:00.000Z"
},
"studentName" : "Sam",
"id" : "f0b25dc9a911782ace5af36db7bfbc1f",
"userId" : "d84f9e5231daa902c37921de9126cad7"
},
"fields" : {
"dues" : [
-37
]
},
"sort" : [
1666656000000
]
},
{
"_index" : "applications",
"_type" : "_doc",
"_id" : "e7f84fa978a553e77716ab479d3d6ce5",
"_score" : null,
"_source" : {
"board" : {
"notApplied" : "2022-10-13T00:00:00.000Z"
},
"id" : "e7f84fa978a553e77716ab479d3d6ce5",
"studentName" : "Sam",
"userId" : "d84f9e5231daa902c37921de9126cad7"
},
"fields" : {
"dues" : [
-49
]
},
"sort" : [
1665619200000
]
},
{
"_index" : "applications",
"_type" : "_doc",
"_id" : "9cba9f6b0d7a28ef739b321291d00170",
"_score" : null,
"_source" : {
"board" : {
"notApplied" : "2022-09-20T00:00:00.000Z"
},
"studentName" : "Ctest17 ",
"id" : "9cba9f6b0d7a28ef739b321291d00170",
"userId" : "ddaf6d6162c8317fd90fec0b870132ce"
},
"fields" : {
"dues" : [
-72
]
},
"sort" : [
1663632000000
]
}
]
}
}
}
}
}
I am getting the exact results but it has been duplicated by userId.
i need a result in top_hits without duplicates or the buckets should be grouped by userId. also the result should be sort desc by (dues or notApplied) field.
can any one help me to resolve this?
I have 2 indexes products & shop_inventory_6(shop wise inventory)
products mapping
{
"products_staging" : {
"aliases" : { },
"mappings" : {
"product" : {
"properties" : {
"alternate_names" : {
"type" : "text"
},
"brand" : {
"properties" : {
"id" : {
"type" : "integer"
},
"image_url" : {
"type" : "text",
"index" : false
},
"name" : {
"type" : "text",
"analyzer" : "standard"
}
}
},
"brand_suggest" : {
"type" : "completion",
"analyzer" : "autocomplete",
"search_analyzer" : "whitespace_analyzer",
"preserve_separators" : true,
"preserve_position_increments" : true,
"max_input_length" : 50
},
"category" : {
"properties" : {
"id" : {
"type" : "integer"
},
"image_url" : {
"type" : "text",
"index" : false
},
"name" : {
"type" : "text",
"analyzer" : "standard"
}
}
},
"id" : {
"type" : "text"
},
"image_url" : {
"type" : "text",
"index" : false
},
"name" : {
"type" : "text",
"fields" : {
"raw" : {
"type" : "keyword"
}
},
"analyzer" : "standard"
},
"name_suggest" : {
"type" : "completion",
"analyzer" : "autocomplete",
"search_analyzer" : "whitespace_analyzer",
"preserve_separators" : true,
"preserve_position_increments" : true,
"max_input_length" : 50
},
"product_alternate_name_suggest" : {
"type" : "completion",
"analyzer" : "autocomplete",
"search_analyzer" : "whitespace_analyzer",
"preserve_separators" : true,
"preserve_position_increments" : true,
"max_input_length" : 50
},
"product_sizes" : {
"type" : "nested",
"properties" : {
"ean_code" : {
"type" : "keyword"
},
"id" : {
"type" : "integer"
},
"is_deleted" : {
"type" : "boolean"
},
"price" : {
"type" : "float"
},
"shop_category_type_ids" : {
"type" : "text"
},
"uom" : {
"type" : "keyword"
},
"weight" : {
"type" : "float"
}
}
},
"sub_category" : {
"properties" : {
"alternate_names" : {
"type" : "text"
},
"id" : {
"type" : "integer"
},
"image_url" : {
"type" : "text",
"index" : false
},
"name" : {
"type" : "text",
"analyzer" : "standard"
}
}
},
"sub_category_alternate_suggest" : {
"type" : "completion",
"analyzer" : "autocomplete",
"search_analyzer" : "whitespace_analyzer",
"preserve_separators" : true,
"preserve_position_increments" : true,
"max_input_length" : 50
},
"sub_category_suggest" : {
"type" : "completion",
"analyzer" : "autocomplete",
"search_analyzer" : "whitespace_analyzer",
"preserve_separators" : true,
"preserve_position_increments" : true,
"max_input_length" : 50
}
}
}
},
"settings" : {
"index" : {
"number_of_shards" : "3",
"provided_name" : "products_staging",
"creation_date" : "1566968865962",
"analysis" : {
"filter" : {
"autocomplete_filter" : {
"type" : "edge_ngram",
"min_gram" : "2",
"max_gram" : "20"
}
},
"analyzer" : {
"autocomplete" : {
"filter" : [
"lowercase",
"autocomplete_filter"
],
"type" : "custom",
"tokenizer" : "standard"
},
"whitespace_analyzer" : {
"filter" : [
"lowercase",
"asciifolding"
],
"type" : "custom",
"tokenizer" : "whitespace"
}
}
},
"number_of_replicas" : "1",
"uuid" : "M5GE3TK9QOKVaBMcOkCJPQ",
"version" : {
"created" : "6000199"
}
}
}
}
}
shop_inventory mapping
{
"staging_shop_inventory_17" : {
"aliases" : { },
"mappings" : {
"shop_inventory" : {
"properties" : {
"brand" : {
"properties" : {
"created_at" : {
"type" : "date"
},
"id" : {
"type" : "integer"
},
"image" : {
"type" : "text",
"index" : false
},
"is_selected" : {
"type" : "boolean"
},
"name" : {
"type" : "text",
"analyzer" : "standard"
},
"updated_at" : {
"type" : "date"
}
}
},
"brand_suggest" : {
"type" : "text",
"analyzer" : "ngram_analyzer"
},
"category" : {
"properties" : {
"id" : {
"type" : "integer"
},
"image" : {
"type" : "text",
"index" : false
},
"name" : {
"type" : "text",
"analyzer" : "standard"
}
}
},
"deleted_at" : {
"type" : "date"
},
"id" : {
"type" : "integer"
},
"image" : {
"type" : "text",
"index" : false
},
"is_deleted" : {
"type" : "boolean"
},
"name" : {
"type" : "text",
"fields" : {
"raw" : {
"type" : "keyword"
}
},
"analyzer" : "gramAnalyzer",
"search_analyzer" : "whitespace_analyzer"
},
"name_suggest" : {
"type" : "text",
"analyzer" : "ngram_analyzer"
},
"product_deleted" : {
"type" : "keyword"
},
"product_id" : {
"type" : "integer"
},
"product_sizes" : {
"type" : "nested",
"properties" : {
"deleted_at" : {
"type" : "date"
},
"ean_code" : {
"type" : "keyword"
},
"id" : {
"type" : "integer"
},
"in_stock" : {
"type" : "boolean"
},
"is_deleted" : {
"type" : "boolean"
},
"price" : {
"type" : "float"
},
"product_update_on" : {
"type" : "date"
},
"product_update_status" : {
"type" : "integer"
},
"uom" : {
"type" : "keyword"
},
"weight" : {
"type" : "float"
}
}
},
"sub_category" : {
"properties" : {
"created_at" : {
"type" : "date"
},
"id" : {
"type" : "integer"
},
"image" : {
"type" : "text",
"index" : false
},
"is_selected" : {
"type" : "boolean"
},
"name" : {
"type" : "text",
"analyzer" : "standard"
},
"updated_at" : {
"type" : "date"
}
}
},
"sub_category_suggest" : {
"type" : "text",
"analyzer" : "gramAnalyzer",
"search_analyzer" : "whitespace_analyzer"
}
}
}
},
"settings" : {
"index" : {
"number_of_shards" : "3",
"provided_name" : "staging_shop_inventory_17",
"creation_date" : "1569230448054",
"analysis" : {
"filter" : {
"gramFilter" : {
"token_chars" : [
"letter",
"digit"
],
"min_gram" : "1",
"type" : "edge_ngram",
"max_gram" : "20"
}
},
"analyzer" : {
"whitespace_analyzer" : {
"filter" : [
"lowercase",
"asciifolding"
],
"type" : "custom",
"tokenizer" : "whitespace"
},
"ngram_analyzer" : {
"token_chars" : [
"letter",
"digit"
],
"min_gram" : "4",
"type" : "custom",
"max_gram" : "20",
"tokenizer" : "ngram"
},
"gramAnalyzer" : {
"filter" : [
"lowercase",
"asciifolding",
"gramFilter"
],
"type" : "custom",
"tokenizer" : "whitespace"
}
}
},
"number_of_replicas" : "1",
"uuid" : "q9BkwXMVQnGoga8tznNFgg",
"version" : {
"created" : "6000199"
}
}
}
}
}
I want to select products from products index which are not in shop_inventory index. without two queries
Also I want select product by sub_category_id & brand_ids where I have multiple sub_category_id & brand ids (because my brand belongs to multiple categories) without using OR condition
I have generated some points of interest with my database with SQL to geoJSON.
geojson:
{
"FeatureCollection" : [
{
"geometry" : {
"coordinates" : [
-45.927083,
-12.260889
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "626.46"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.916500,
-12.255944
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "565.04"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.949417,
-12.270361
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "631.47"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.958833,
-12.277361
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "591.85"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.942944,
-12.249889
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "644.67"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.930917,
-12.243611
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "644.67"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.871917,
-12.197139
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.866861,
-12.206417
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.967389,
-12.261889
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "592.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.973500,
-12.250639
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "592.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.962944,
-12.245444
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "621.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.952667,
-12.239778
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "592.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.931639,
-12.228528
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.908694,
-12.247472
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "557.20"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.918667,
-12.239139
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "644.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.897028,
-12.246000
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "557.20"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.906417,
-12.230472
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "64.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.895750,
-12.225028
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "644.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.927111,
-12.213750
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "564.90"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.917639,
-12.208750
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "564.90"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.897833,
-12.198444
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "584.00"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.881583,
-12.202233
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.876833,
-12.235306
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.867278,
-12.230306
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.856806,
-12.224889
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.861806,
-12.215611
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.887833,
-12.192806
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "12.60"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.877639,
-12.187917
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "564.90"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.941889,
-12.234611
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "644.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.887111,
-12.239889
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "644.50"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.907944,
-12.203361
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "591.70"
},
"type" : "Feature"
},
{
"geometry" : {
"coordinates" : [
-45.892722,
-12.208028
],
"type" : "Point"
},
"properties" : {
"grower" : "foo",
"name" : "bar",
"radius" : "574.60"
},
"type" : "Feature"
}
]
}
I would like to import this geojson to my code editor on Google Earth Engine. Looking in the docs (assets manager), GEE accepts assets as raster images, shapefiles (.shp, shx, dbf, prj).
Also, I found the import to feature collection via fusion tables, but it still needs shapefiles.
I have found some geojson to shapefile conversors, though I need a way to directly import my geojson to a feature collection on GEE. Is that possible?
You can also import GeoJSON geometry objects directly into either the JavaScript or Python API using, for example, this format for a MultiPolygon:
feature_geometry = {
"type": "MultiPolygon",
'coordinates": [
[
[
[-120, 35],
[-120.001, 35],
[-120.001, 35.001],
[-120, 35.001],
[-120, 35]
]
]
]
}
Both hash maps (i.e., dictionaries) are identical to the GeoJSON specification (source):
{
"type": "MultiPolygon",
"coordinates": [
[
[
[-120, 35],
[-120.001, 35],
[-120.001, 35.001],
[-120, 35.001],
[-120, 35]
]
]
]
}
Of course, you can also read this data in from a GeoJSON file (Python example shown):
import json
data = json.loads(geojson_file)
For a simple Python wrapper, there is the pygeoj library, but JSON data is handled well natively in Python and of course in JavaScript.
You can easily use OGR to convert your data a shapefile (which you can then upload through the code editor) or to KML and upload it into FusionTables.
ogr2ogr -f KML output.kml input.json
However, your FeatureCollection isn't valid GeoJSON and you'll have to fix that first. The preamble should look like:
{
"type": "FeatureCollection",
"features": [
{
"geometry" : { ...
I am struggling with elasticsearch-rails.
I have the following mapping:
{
"listings" : {
"mappings" : {
"listing" : {
"properties" : {
"address" : {
"type" : "string"
},
"authorized" : {
"type" : "boolean"
},
"categories" : {
"properties" : {
"created_at" : {
"type" : "date",
"format" : "dateOptionalTime"
},
"id" : {
"type" : "long"
},
"name" : {
"type" : "string"
},
"parent_id" : {
"type" : "long"
},
"updated_at" : {
"type" : "date",
"format" : "dateOptionalTime"
},
"url_name" : {
"type" : "string"
}
}
},
"cid" : {
"type" : "string"
},
"city" : {
"type" : "string"
},
"country" : {
"type" : "string"
},
"created_at" : {
"type" : "date",
"format" : "dateOptionalTime"
},
"featured" : {
"type" : "boolean"
},
"geojson" : {
"type" : "string"
},
"id" : {
"type" : "long"
},
"latitude" : {
"type" : "string"
},
"longitude" : {
"type" : "string"
},
"name" : {
"type" : "string"
},
"phone" : {
"type" : "string"
},
"postal" : {
"type" : "string"
},
"province" : {
"type" : "string"
},
"thumbnail_filename" : {
"type" : "string"
},
"updated_at" : {
"type" : "date",
"format" : "dateOptionalTime"
},
"url" : {
"type" : "string"
}
}
}
}
}
}
I would like to change the type for the geojson field from string to geo_point so I can use the geo_shape query on it.
I tried this in my model:
settings index: { number_of_shards: 1 } do
mappings dynamic: 'false' do
indexes :geojson, type: 'geo_shape'
end
end
with peculiar results. When I queried the mapping with $ curl 'localhost:9200/_all/_mapping?pretty', the geojson field still shows as type: string.
Within a Rails console, if I do Listing.mappings.to_hash, it seems to show that the geojson field is of type geo_shape.
And yet when running this query:
Listing.search(query: { fuzzy_like_this: { fields: [:name], like_text: "gap" } }, query: { fuzzy_like_this_field: { city: { like_text: "San Francisco" } } }, query: { geo_shape: { geojson: { shape: { type: :envelope, coordinates: [[37, -122],[38,-123]] } } } }); response.results.total; response.results.map { |r| puts "#{r._score} | #{r.name}, #{r.city} (lat: #{r.latitude}, lon: #{r.longitude})" }
ES complains that the geojson field is not of type geo_shape.
What am I missing? How do I tell ES that I want the geojson field to be of type geo_shape and not string?
The issue was that I didn't delete and recreate the mapping.
In the rails console, I ran Model.__elasticsearch__.delete_index! and then Model.__elasticsearch__.create_index! followed by Model.import
I am unable to create a custom mapping for "hashtags," which is a subfield of "twitter_entities" in elasticsearch. I tried to do it in the following ways:
{
"mappings": {
"tweet" : {
"properties": {
"twitter_entities.hashtags" : {
"type" : "multi_field",
"fields" : {
"hashtag" : {
"type" : "string",
"analyzer" : "hashtag"
},
"autocomplete" : {
"type" : "string",
"index_analyzer" : "hashtag_autocomplete",
"search_analyzer" : "hashtag"
}
}
}
}
}
}
}
This creates another root field called "twitter_entities.hashtags"
{
"mappings": {
"tweet" : {
"properties": {
"hashtags" : {
"type" : "multi_field",
"fields" : {
"hashtag" : {
"type" : "string",
"analyzer" : "hashtag"
},
"autocomplete" : {
"type" : "string",
"index_analyzer" : "hashtag_autocomplete",
"search_analyzer" : "hashtag"
}
}
}
}
}
}
}
and
{
"mappings": {
"tweet" : {
"properties": {
"_parent" : {"type" : "twitter_entities" },
"hashtags" : {
"type" : "multi_field",
"fields" : {
"hashtag" : {
"type" : "string",
"analyzer" : "hashtag"
},
"autocomplete" : {
"type" : "string",
"index_analyzer" : "hashtag_autocomplete",
"search_analyzer" : "hashtag"
}
}
}
}
}
}
}
both just create another root field called "hashtags".
I am unable to find any documentation in the elasticsearch api or forums about doing this. Could anyone point me in the right direction?
Have a look at the documentation for mapping, especially the page about the object type.
You just have to define twitter_entitiesas an object and declare its fields under properties, same as you did for the root object (twitter_entities). You can omit the type object since any field that contains other fields under properties is detected as object anyway.
{
"mappings": {
"tweet" : {
"properties": {
"twitter_entities" : {
"type": "object",
"properties" : {
"hashtag" : {
"type" : "multi_field",
"fields" : {
"hashtag" : {
"type" : "string",
"analyzer" : "hashtag"
},
"autocomplete" : {
"type" : "string",
"index_analyzer" : "hashtag_autocomplete",
"search_analyzer" : "hashtag"
}
}
}
}
}
}
}
}
}