Self-Managed Elastic App Search Beta Released
Many of you are well familiar with Elasticsearch: the heart of the Elastic Stack, which has been downloaded over 350,000,000 times. Elasticsearch provides search within the most popular applications the world over. But you might not be familiar with Elastic App Search. Today — for the first time — you can download it and run it within your own infrastructure.
Elasticsearch Born
Elasticsearch — you know, it’s for search. Elastic App Search is also for search, and it is built atop Elasticsearch.
Elasticsearch is found at the heart of web scale searching, logging, and data storing infrastructure around the world. To allow public APIs or web browsers access to Elasticsearch data, developers often put Elasticsearch behind a proxy server, or wrap its APIs in middleware. But doing this means someone needs to be careful with what is exposed, keep it secure, manage authentication, and write insulating logic to allow clients to reach the data. It's a lot of work!
If you just want the easiest and quickest way to provide relevant, tuneable search experiences within your applications then you will love Elastic App Search. It is the intelligent, refined, search API wrapper in front of Elasticsearch that streamlines data indexing, search tuning, and search development — and much more, all matched with intuitive dashboard tools that any team member can use.
Search, Dance
We can best demonstrate Elastic App Search by experimenting with its key operations — first, there is the creation of your Engine, the conduit that represents your search indexes.
We will make an Engine called:
walk-in-the-park
While we can choose from over a dozen different languages, we will choose English, the language that matches our data set:
curl -X POST 'http://localhost:3002/api/as/v1/engines' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer private-xxxxxxxxxxxxxxxxxxxx' \
-d '{
"name": "walk-in-the-park"
}'
An Engine is nothing without documents, so we shall provide some. How about two objects that represent National Parks?
curl -X POST 'http://localhost:3002/api/as/v1/engines/walk-in-the-park/documents' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer private-xxxxxxxxxxxxxxxxxxxx' \
-d '[
{
"description": "This park and the co-managed state parks protect almost half of all remaining coastal redwoods, the tallest trees on earth. There are three large river systems in this very seismically active area, and 37 miles (60 km) of protected coastline reveal tide pools and seastacks. The prairie, estuary, coast, river, and forest ecosystems contain a wide variety of animal and plant species.",
"nps_link": "https://www.nps.gov/redw/index.htm",
"states": [
"California"
],
"title": "Redwood",
"id": "park_redwood",
"visitors": 536297,
"world_heritage_site": true,
"location": "41.3,-124",
"acres": 138999.37,
"square_km": 562.5,
"date_established": "1968-10-02T05:00:00Z"
},
{
"description": "Bisected north to south by the Continental Divide, this portion of the Rockies has ecosystems varying from over 150 riparian lakes to montane and subalpine forests to treeless alpine tundra. Wildlife including mule deer, bighorn sheep, black bears, and cougars inhabit its igneous mountains and glacial valleys. Longs Peak, a classic Colorado fourteener, and the scenic Bear Lake are popular destinations, as well as the historic Trail Ridge Road, which reaches an elevation of more than 12,000 feet (3,700 m).",
"nps_link": "https://www.nps.gov/romo/index.htm",
"states": [
"Colorado"
],
"title": "Rocky Mountain",
"id": "park_rocky-mountain",
"visitors": 4517585,
"world_heritage_site": false,
"location": "40.4,-105.58",
"acres": 265795.2,
"square_km": 1075.6,
"date_established": "1915-01-26T06:00:00Z"
}
]'
In response, a simple set of JSON objects have now become indexed, searchable documents, optimized by default for full-text search. The documents exist within your Elasticsearch cluster at the heart of App Search.
But we have more than text fields, and so we should adjust our schema. Fields can also be of type number, date, or geolocation.
Want to generate results given proximity to geo-coordinates or a specific date? Or search through a range of numbers? If the schema is right, you can do so at query time.
curl -X POST 'http://localhost:3002/api/as/v1/engines/walk-in-the-park/schema' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer private-xxxxxxxxxxxxxxxx' \
-d '{
"description": "text",
"nps_link": "text",
"location": "geolocation",
"states": "text",
"title": "text",
"visitors": "number",
"world_heritage_site": "text",
"acres": "number",
"square_km": "number",
"date_established": "date"
}'
Ahh-ha, good good. We are now ready to search through this data, and for that we are going to use a JavaScript client. But first, how about we craft a unique key. Luckily, this unique key is disposable and can be access controlled using the API or intuitive dashboard controls…
curl -X POST 'http://localhost:3002/api/as/v1/credentials' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer admin-xxxxxxxxxxxxxxxx' \
-d '[
{
"name": "limited-javascript-search-key",
"type": "search",
"read": true,
"write": false,
"access_all_engines": false,
"engines": [
"walk-in-the-park"
]
}
]'
Key acquired: search-lpaewu2xf6uc52dr8med54v8. Along with this key, we have an Engine - which contains an index with multiple data types — and two lush documents over which we can search. And now, to search.
We will use a JavaScript client to search as promised.
We will request only a title and a description:
const client = SwiftypeAppSearch.createClient({
searchKey: 'search-soaewu2ye6uc45dr8mcd54v8',
engineName: 'walk-in-the-park'
})
const query = 'rocky mountain'
const options = {
filters: {
result_field: {
title: {
raw: {}
},
description: {
raw: {}
}
}
}
}
client
.search(query, options)
.then(function(response){ console.log(response) })
.catch(function(error){ console.log(error) })
And we return our documents. With this, we have the backbone of a quality, scaleable search experience. And it only took a few minutes.
{
"meta": {
"warnings": [],
"page": {
"current": 1,
"total_pages": 4,
"total_results": 38,
"size": 10
},
"request_id": "ce1a5d2a70113fab5d361b335a76e0ad"
},
"results": [
{
"title": {
"raw": "Rocky Mountain"
},
"description": {
"raw": "Bisected north to south by the Continental Divide, this portion of the Rockies has ecosystems"
},
"id": {
"raw": "park_rocky-mountain"
},
"_meta": {
"score": 48.68962
}
}
]
}
Stop! Query Time
At query time, one can adjust the weight of fields, giving greater precedence to specific fields. One can also provide boosts depending on the result values of those fields, receive facet counts, sort, create groups, apply tags, and more — all while collecting analytics data in realtime.
The Analytics API can be used in conjunction with search; are your top 3 search results often changing? Perhaps your front-end code can request your most popular search results and then re-configure its content or product listings in real-time. Or, perhaps you just want a tidy way to view what users are searching for, finding, and not finding.
More than just APIs, team members of all kind can add value from the Elastic App Search dashboard. You can view analytics, curate results, add synonyms, configure weights and boosts, and more, all from within an intuitive user interface.
All Packed Up, Somewhere to Go
During the beta period, you can spin Elastic App Search up on your own hardware at no charge. To do so, download App Search.
This self-managed release of Elastic App Search requires that you have Java 8 or Java 11 installed and Elasticsearch 6.4.x or 6.5.x running. Elasticsearch requires at least a Basic license. You will receive a licence for free when downloading Elasticsearch from Elastic.co.
Once the dependencies have been taken care of, enter the decompressed App Search directory and run:
bin/app-search
And now access http://localhost:3002, login with the default credentials and explore. You can now host and configure App Search however you like.
Wondering where to start? Index some documents, then see how your data looks within the Reference UI, a foundational, React based open source search experience that you can build on top of, or use from within the dashboard for search experimentation. From there, we have ample documentation that can help you fine tune search relevance and build the next great search experience.
We’d Love Your Feedback
Please let us know how you are feeling about Elastic App Search. If you run into any bugs, have any comments or questions, please reach us at: [email protected].
Elastic App Search, Managed
If this sounds intriguing, but you are more interested in Elastic App Search as a managed service, you can sign up for a free 14 day trial.