appbase-js is a universal JavaScript client library for working with the ReactiveSearch API.
It can:
- Index new documents or update / delete existing ones.
- Work universally with Node.JS, Browser, and React Native.
It can't:
- Configure mappings, change analyzers, or capture snapshots. All these are provided by elasticsearch.js - the official Elasticsearch JS client library.
Create Cluster
You can start by creating an Elasticsearch cluster with appbase.io or bring your Elasticsearch cluster or self-host appbase.io.
- Log in toAppbase Dashboard, and create a new cluster.
- Copy the URL of your cluster for further actions
You can read see the different options for creating a cluster and their pricing over here.
Creating an Index
This gif shows how to create an index on reactivesearch.io cluster, which we will need for this quickstart guide.
For this tutorial, we will use an index called good-books-demo
. The credentials for this index are 376aa692e5ab:8472bf31-b18a-454d-bd39-257c07d02854
.
Note
reactivesearch.io uses HTTP Basic Auth, a widely used protocol for simple username/password authentication. It also support creating various API credentials with different access. You can read more about access control in docs.
Install appbase-js
We will fetch and install the appbase-js lib using npm. 4.0.0-beta
is the most current version.
npm install appbase-js
Adding it in the browser should be a one line script addition.
<script defer src="https://unpkg.com/appbase-js/dist/appbase-js.umd.min.js"></script>
Alternatively, a UMD build of the library can be used directly from jsDelivr.
To write data to appbase.io, we need to first create a reference object. We do this by passing the appbase.io API URL, app name, and credentials into the Appbase
constructor:
var appbaseRef = Appbase({
url: 'https://appbase-demo-ansible-abxiydt-arc.searchbase.io',
app: 'good-books-demo',
credentials: 'c84fb24cbe08:db2a25b5-1267-404f-b8e6-cf0754953c68',
});
OR
var appbaseRef = Appbase({
url:
'https://c84fb24cbe08:db2a25b5-1267-404f-b8e6-cf0754953c68@appbase-demo-ansible-abxiydt-arc.searchbase.io',
app: 'good-books-demo',
});
Credentials can also be directly passed as a part of the API URL.
Storing Data
Once we have the reference object (called appbaseRef
in this tutorial), we can insert any JSON object into it with the index()
method.
var jsonObject = {
department_name: 'Books',
department_name_analyzed: 'Books',
department_id: 1,
name: 'A Fake Book on Network Routing',
price: 5595,
};
appbaseRef
.index({
type: '_doc',
id: 'X1',
body: jsonObject,
})
.then(function(response) {
console.log(response);
})
.catch(function(error) {
console.log(error);
});
The index()
method (and all the other appbase
methods) return a promise.
Note
appbase.io uses the same APIs and data modeling conventions as Elasticsearch.
GET Data
Now that we are able to store data, let's try to get the data back from appbase.io with the get()
method.
appbaseRef.get({
type: "_doc",
id: "X1"
}).then(function(response) {
console.log(response)
}).catch(function(error) {
console.log(error)
})
/* get() response */
{
"_index": "good-books-demo",
"_type": "books",
"_id": "X1",
"_version": 5,
"found": true,
"_source": {
"department_name": "Books",
"department_name_analyzed": "Books",
"department_id": 1,
"name": "A Fake Book on Network Routing",
"price": 5595
}
}
Search Queries
search
method helps you query the Elasticsearch with query DSL as its body.
For example, here we are trying to run match_all
query that returns all the documents.
appbaseRef.search({
body: {
query: {
match_all: {}
}
}
}, function(response) {
console.log(response);
}, function("search() response: ", error) {
console.log("caught a error: ", error)
})
/* Response when a new data matches */
{
"_type": "books",
"_id": "X1",
"_version": 5,
"found": true,
"_source": {
"department_name": "Books",
"department_name_analyzed": "Books",
"department_id": 1,
"name": "A Fake Book on Network Routing",
"price": 6034
}
}