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Author SHA1 Message Date
Liz Snyder 293743e15b Missed one 2021-09-22 12:27:39 -07:00
Liz Snyder 2d228a86ca Update client name 2021-09-22 12:26:41 -07:00
Liz Snyder 18d3891879 Specify how to turn off cert verification 2021-08-26 15:23:06 -07:00
Liz Snyder e210d7d217 Fix nav order to not conflict with Go 2021-08-26 13:36:12 -07:00
Liz Snyder 51d359ec40 Remove index refresh 2021-08-26 13:34:19 -07:00
Liz Snyder 4d39000cd3 Add command to install specific version 2021-08-26 12:51:04 -07:00
Liz Snyder cea3ba7ce9 Getting started docs for javascript 2021-08-26 12:44:58 -07:00
aetter 0376c4b6d9 Fix link. 2021-08-25 14:55:03 -07:00
Andrew Etter ff8cd66090 Merge pull request #155 from ict-one-nl/patch-1
Use same attribute name as cluster page
2021-08-25 14:52:13 -07:00
ict-one-nl f3a9bad35c Use same attribute name as cluster page
Simple fix, but because https://opensearch.org/docs/opensearch/cluster/ uses the node.attr.temp setting and this page uses the box_type setting a less experienced user like me easily makes a mistake (not comprehending the exact workings). Using the temp attribute here as well would have saved me a couple of hours and some grey hairs.
2021-08-25 13:54:54 +02:00
3 changed files with 148 additions and 5 deletions
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@@ -0,0 +1,141 @@
---
layout: default
title: Javascript client
nav_order: 90
---
# Javascript client
The OpenSearch Javascript client provides a safer and easier way to interact with your OpenSearch cluster. Rather than using OpenSearch from the browser and potentially exposing your data to the public, you can build an OpenSearch client that takes care of sending requests to your cluster.
The client contains a library of APIs that let you perform different operations on your cluster and return a standard response body. The example here demonstrates some basic operations like creating an index, adding documents, and searching your data.
## Setup
To add the client to your project, install it from npm:
```bash
npm install @opensearch-project/opensearch
```
To install a specific major version of the client, run the following command:
```bash
npm install @opensearch-project/opensearch@<version>
```
If you prefer to add the client manually or just want to examine the source code, see [opensearch-js](https://github.com/opensearch-project/opensearch-js) on GitHub.
Then require the client:
```javascript
const { Client } = require("@opensearch-project/opensearch");
```
## Sample code
```javascript
"use strict";
var host = "localhost";
var protocol = "https";
var port = 9200;
var auth = "admin:admin"; // For testing only. Don't store credentials in code.
var ca_certs_path = "/full/path/to/root-ca.pem";
// Optional client certificates if you don't want to use HTTP basic authentication.
// var client_cert_path = '/full/path/to/client.pem'
// var client_key_path = '/full/path/to/client-key.pem'
// Create a client with SSL/TLS enabled.
var { Client } = require("@opensearch-project/opensearch");
var fs = require("fs");
var client = new Client({
node: protocol + "://" + auth + "@" + host + ":" + port,
ssl: {
ca: fs.readFileSync(ca_certs_path),
// You can turn off certificate verification (rejectUnauthorized: false) if you're using self-signed certificates with a hostname mismatch.
// cert: fs.readFileSync(client_cert_path),
// key: fs.readFileSync(client_key_path)
},
});
async function search() {
// Create an index with non-default settings.
var index_name = "books";
var settings = {
settings: {
index: {
number_of_shards: 4,
number_of_replicas: 3,
},
},
};
var response = await client.indices.create({
index: index_name,
body: settings,
});
console.log("Creating index:");
console.log(response.body);
// Add a document to the index.
var document = {
title: "The Outsider",
author: "Stephen King",
year: "2018",
genre: "Crime fiction",
};
var id = "1";
var response = await client.index({
id: id,
index: index_name,
body: document,
refresh: true,
});
console.log("Adding document:");
console.log(response.body);
// Search for the document.
var query = {
query: {
match: {
title: {
query: "The Outsider",
},
},
},
};
var response = await client.search({
index: index_name,
body: query,
});
console.log("Search results:");
console.log(response.body.hits);
// Delete the document.
var response = await client.delete({
index: index_name,
id: id,
});
console.log("Deleting document:");
console.log(response.body);
// Delete the index.
var response = await client.indices.delete({
index: index_name,
});
console.log("Deleting index:");
console.log(response.body);
}
search().catch(console.log);
```
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@@ -347,7 +347,7 @@ Parameter | Description | Type | Required | Default
### allocation
Allocate the index to a node with a specific attribute.
Allocate the index to a node with a specific attribute set [like this]({{site.url}}{{site.baseurl}}/opensearch/cluster/#advanced-step-7-set-up-a-hot-warm-architecture).
For example, setting `require` to `warm` moves your data only to "warm" nodes.
The `allocation` operation has the following parameters:
@@ -363,7 +363,7 @@ Parameter | Description | Type | Required
"actions": [
{
"allocation": {
"require": { "box_type": "warm" }
"require": { "temp": "warm" }
}
}
]
+5 -3
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@@ -79,11 +79,13 @@ This formula provides a good starting point, but make sure to test with a repres
For example, for a cluster with 3 data nodes, each with 8G of JVM heap size, a maximum memory percentage of 10% (default), and the entity size of the detector as 1MB: the total number of unique entities supported is (8.096 * 10^9 * 0.1 / 1M ) * 3 = 2429.
#### Set a shingle size
#### Set a window size
Set the number of aggregation intervals from your data stream to consider in a detection window. Its best to choose this value based on your actual data to see which one leads to the best results for your use case.
Set the number of aggregation intervals from your data stream to consider in a detection window. It's best to choose this value based on your actual data to see which one leads to the best results for your use case.
The anomaly detector expects the shingle size to be in the range of 1 and 60. The default shingle size is 8. We recommend that you don't choose 1 unless you have two or more features. Smaller values might increase [recall](https://en.wikipedia.org/wiki/Precision_and_recall) but also false positives. Larger values might be useful for ignoring noise in a signal.
Based on experiments performed on a wide variety of one-dimensional data streams, we recommend using a window size between 1 and 16. The default window size is 8. If you set the category field for high cardinality, the default window size is 1.
If you expect missing values in your data or if you want to base the anomalies on the current interval, choose 1. If your data is continuously ingested and you want to base the anomalies on multiple intervals, choose a larger window size.
#### Preview sample anomalies