Adds a quickstart guide (#1739)

* Beginning quickstart guide

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* Add sample docker compose yaml to assets

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* Adding verbiage about compose commands

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* More additions but saving before a lunch break

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* Remove sample compose file from the quickstart guide since it is linked externally

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* Added first common problem

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* Formatting of common issues - oh and I renamed it common issues because problems sounds too negative

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* Formatting

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* Adding more content. I love Starbucks White Chocolate Mocha creamer

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* Indentation

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* Added common issue re: docker perms

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* Changing the common issues section around a bit so the ordering makes more sense

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* Removed blank target from important settings links since we don't do that for other links

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* Updates

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* Committing changes

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* Added newline to docker compose file and started working on steps in the guide

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* Adding steps

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* Added cURL command for example query

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* Reworded intro paragraph and added more steps.

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* Added tip about using the pretty query parameter

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* Editing

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* Added dashboards content and working on next steps segue

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* Wrapping up for the day

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* Cleaning up before reviews

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* Finishing up

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* Editorial fixes

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* Final editorial changes

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* Changes relating to PM review

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* Incorporating feedback from docs review

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* Final changes

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---
layout: default
title: Quickstart guide
parent: Install OpenSearch
nav_order: 1
---
# Quickstart guide
Get started using OpenSearch and OpenSearch Dashboards by deploying your containers with [Docker](https://www.docker.com/). Before proceeding, you need to [get Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://github.com/docker/compose) installed on your local machine.
The Docker Compose commands used in this guide are written with a hyphen (for example, `docker-compose`). If you installed Docker Desktop on your machine, which automatically installs a bundled version of Docker Compose, then you should remove the hyphen. For example, change `docker-compose` to `docker compose`.
{: .note}
## Starting your cluster
You'll need a special file, called a Compose file, that Docker Compose uses to define and create the containers in your cluster. The OpenSearch Project provides a sample Compose file that you can use to get started. Learn more about working with Compose files by reviewing the official [Compose specification](https://docs.docker.com/compose/compose-file/).
1. Before running OpenSearch on your machine, you should review and apply these [important system settings]({{site.url}}{{site.baseurl}}/opensearch/install/important-settings/).
- Disable memory paging and swapping performance on the host to improve performance.
```bash
sudo swapoff -a
```
- Increase the number of memory maps available to OpenSearch.
```bash
# Edit the sysctl config file.
sudo vi /etc/sysctl.conf
# Define the max map count.
vm.max_map_count=262144
# Reload the kernel parameters.
sudo sysctl -p
```
1. Download the sample Compose file to your host. You can download the file with command line utilities like `curl` and `wget`, or you can manually copy [docker-compose.yml](https://github.com/opensearch-project/documentation-website/tree/{{site.opensearch_version}}/assets/examples/docker-compose.yml) from the OpenSearch Project documentation-website repository using a web browser.
```bash
# Using cURL:
curl -O https://github.com/opensearch-project/documentation-website/tree/{{site.opensearch_version}}/assets/examples/docker-compose.yml
# Using wget:
wget https://github.com/opensearch-project/documentation-website/tree/{{site.opensearch_version}}/assets/examples/docker-compose.yml
```
1. In your terminal application, navigate to the directory containing the `docker-compose.yml` file you just downloaded, and run the following command to create and start the cluster as a background process.
```bash
docker-compose up -d
```
1. Confirm that the containers are running with the command `docker-compose ps`. You should see an output like the following:
```bash
$ docker-compose ps
NAME COMMAND SERVICE STATUS PORTS
opensearch-dashboards "./opensearch-dashbo…" opensearch-dashboards running 0.0.0.0:5601->5601/tcp
opensearch-node1 "./opensearch-docker…" opensearch-node1 running 0.0.0.0:9200->9200/tcp, 9300/tcp, 0.0.0.0:9600->9600/tcp, 9650/tcp
opensearch-node2 "./opensearch-docker…" opensearch-node2 running 9200/tcp, 9300/tcp, 9600/tcp, 9650/tcp
```
1. Query the OpenSearch REST API to verify that the service is running. You should use `-k` (also written as `--insecure`) to disable host name checking because the default security configuration uses demo certificates. Use `-u` to pass the default username and password (`admin:admin`).
```bash
curl https://localhost:9200 -ku admin:admin
```
- Sample response:
```json
{
"name" : "opensearch-node1",
"cluster_name" : "opensearch-cluster",
"cluster_uuid" : "Cd7SL5ysRSyuau325M3h9w",
"version" : {
"distribution" : "opensearch",
"number" : "2.3.0",
"build_type" : "tar",
"build_hash" : "6f6e84ebc54af31a976f53af36a5c69d474a5140",
"build_date" : "2022-09-09T00:07:12.137133581Z",
"build_snapshot" : false,
"lucene_version" : "9.3.0",
"minimum_wire_compatibility_version" : "7.10.0",
"minimum_index_compatibility_version" : "7.0.0"
},
"tagline" : "The OpenSearch Project: https://opensearch.org/"
}
```
1. Explore OpenSearch Dashboards by opening `http://localhost:5601/` in a web browser on the same host that is running your OpenSearch cluster.
- The default username is `admin` and the default password is `admin`.
## Create an index and field mappings using sample data
Create an index and define field mappings using a dataset provided by the OpenSearch Project. The same fictitious e-commerce data is also used for sample visualizations in OpenSearch Dashboards. To learn more, see [Getting started with OpenSearch Dashboards]({{site.url}}{{site.baseurl}}/dashboards/index/).
1. Download [ecommerce-field_mappings.json](https://github.com/opensearch-project/documentation-website/blob/{{site.opensearch_version}}/assets/examples/ecommerce-field_mappings.json). This file defines a [mapping]({{site.url}}{{site.baseurl}}/opensearch/mappings/) for the sample data you will use.
```bash
# Using cURL:
curl -O https://github.com/opensearch-project/documentation-website/blob/{{site.opensearch_version}}/assets/examples/ecommerce-field_mappings.json
# Using wget:
wget https://github.com/opensearch-project/documentation-website/blob/{{site.opensearch_version}}/assets/examples/ecommerce-field_mappings.json
```
1. Download [ecommerce.json](https://github.com/opensearch-project/documentation-website/blob/{{site.opensearch_version}}/assets/examples/ecommerce.json). This file contains the index data formatted so that it can be ingested by the bulk API. To learn more, see [index data]({{site.url}}{{site.baseurl}}/opensearch/index-data/) and [Bulk]({{site.url}}{{site.baseurl}}/api-reference/document-apis/bulk/).
```bash
# Using cURL:
curl -O https://github.com/opensearch-project/documentation-website/blob/{{site.opensearch_version}}/assets/examples/ecommerce.json
# Using wget:
wget https://github.com/opensearch-project/documentation-website/blob/{{site.opensearch_version}}/assets/examples/ecommerce.json
```
1. Define the field mappings with the mapping file.
```bash
curl -H "Content-Type: application/x-ndjson" -X PUT "https://localhost:9200/ecommerce" -ku admin:admin --data-binary "@ecommerce-field_mappings.json"
```
1. Upload the index to the bulk API.
```bash
curl -H "Content-Type: application/x-ndjson" -X PUT "https://localhost:9200/ecommerce/_bulk" -ku admin:admin --data-binary "@ecommerce.json"
```
1. Query the data using the search API. The following command submits a query that will return documents where `customer_first_name` is `Sonya`.
```bash
curl -H 'Content-Type: application/json' -X GET "https://localhost:9200/ecommerce/_search?pretty=true" -ku admin:admin -d' {"query":{"match":{"customer_first_name":"Sonya"}}}'
```
- Add the query parameter `pretty=true` to OpenSearch API requests that return a JSON to see a more readable version of the response body. Otherwise, the response will be a flat JSON. For more information about `pretty` and other query parameters, see [Common REST parameters]({{site.url}}{{site.baseurl}}/opensearch/common-parameters/).
1. Access OpenSearch Dashboards by opening `http://localhost:5601/` in a web browser on the same host that is running your OpenSearch cluster.
- The default username is `admin` and the default password is `admin`.
1. On the top menu bar, go to **Management > Dev Tools**.
1. In the left pane of the console, enter the following:
```json
GET ecommerce/_search
{
"query": {
"match": {
"customer_first_name": "Sonya"
}
}
}
```
1. Choose the triangle icon at the top right of the request to submit the query. You can also submit the request by pressing `Ctrl+Enter` (or `Cmd+Enter` for Mac users). To learn more about using the OpenSearch Dashboards console for submitting queries, see [Running queries in the console]({{site.url}}{{site.baseurl}}/dashboards/run-queries/).
## Next steps
You successfully deployed your own OpenSearch cluster with OpenSearch Dashboards and added some sample data. Now you're ready to learn about configuration and functionality in more detail. Here are a few recommendations on where to begin:
- [About the security plugin]({{site.url}}{{site.baseurl}}/security-plugin/index/)
- [OpenSearch configuration]({{site.url}}{{site.baseurl}}/opensearch/configuration/)
- [OpenSearch plugin installation]({{site.url}}{{site.baseurl}}/opensearch/install/plugins/)
- [Getting started with OpenSearch Dashboards]({{site.url}}{{site.baseurl}}/dashboards/index/)
- [OpenSearch tools]({{site.url}}{{site.baseurl}}/tools/index/)
- [Index APIs]({{site.url}}{{site.baseurl}}/api-reference/index-apis/index/)
## Common issues
Review these common issues and suggested solutions if your containers fail to start or exit unexpectedly.
### Docker commands require elevated permissions
Eliminate the need for running your Docker commands with `sudo` by adding your user to the `docker` user group. See Docker's [Post-installation steps for Linux](https://docs.docker.com/engine/install/linux-postinstall/) for more information.
```bash
sudo usermod -aG docker $USER
```
### Error message: "-bash: docker-compose: command not found"
If you installed Docker Desktop, then Docker Compose is already installed on your machine. Try `docker compose` (without the hyphen) instead of `docker-compose`. See [Use Docker Compose](https://docs.docker.com/get-started/08_using_compose/).
### Error message: "docker: 'compose' is not a docker command."
If you installed Docker Engine, then you must install Docker Compose separately, and you will use the command `docker-compose` (with a hyphen). See [Docker Compose](https://github.com/docker/compose).
### Error message: "max virtual memory areas vm.max_map_count [65530] is too low"
OpenSearch will fail to start if your host's `vm.max_map_count` is too low. Review the [important system settings]({{site.url}}{{site.baseurl}}/opensearch/install/important-settings/) if you see the following errors in the service log, and set `vm.max_map_count` appropriately.
```bash
opensearch-node1 | ERROR: [1] bootstrap checks failed
opensearch-node1 | [1]: max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]
opensearch-node1 | ERROR: OpenSearch did not exit normally - check the logs at /usr/share/opensearch/logs/opensearch-cluster.log
```

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version: '3'
services:
opensearch-node1: # This is also the hostname of the container within the Docker network (i.e. https://opensearch-node1/)
image: opensearchproject/opensearch:latest
container_name: opensearch-node1
environment:
- cluster.name=opensearch-cluster # Name the cluster
- node.name=opensearch-node1 # Name the node that will run in this container
- discovery.seed_hosts=opensearch-node1,opensearch-node2 # Nodes to look for when discovering the cluster
- cluster.initial_cluster_manager_nodes=opensearch-node1,opensearch-node2 # Nodes eligibile to serve as cluster manager
- bootstrap.memory_lock=true # Disable JVM heap memory swapping
- "OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m" # Set min and max JVM heap sizes to at least 50% of system RAM
ulimits:
memlock:
soft: -1 # Set memlock to unlimited (no soft or hard limit)
hard: -1
nofile:
soft: 65536 # Maximum number of open files for the opensearch user - set to at least 65536
hard: 65536
volumes:
- opensearch-data1:/usr/share/opensearch/data # Creates volume called opensearch-data1 and mounts it to the container
ports:
- 9200:9200 # REST API
- 9600:9600 # Performance Analyzer
networks:
- opensearch-net # All of the containers will join the same Docker bridge network
opensearch-node2:
image: opensearchproject/opensearch:latest # This should be the same image used for opensearch-node1 to avoid issues
container_name: opensearch-node2
environment:
- cluster.name=opensearch-cluster
- node.name=opensearch-node2
- discovery.seed_hosts=opensearch-node1,opensearch-node2
- cluster.initial_cluster_manager_nodes=opensearch-node1,opensearch-node2
- bootstrap.memory_lock=true
- "OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536
hard: 65536
volumes:
- opensearch-data2:/usr/share/opensearch/data
networks:
- opensearch-net
opensearch-dashboards:
image: opensearchproject/opensearch-dashboards:latest # Make sure the version of opensearch-dashboards matches the version of opensearch installed on other nodes
container_name: opensearch-dashboards
ports:
- 5601:5601 # Map host port 5601 to container port 5601
expose:
- "5601" # Expose port 5601 for web access to OpenSearch Dashboards
environment:
OPENSEARCH_HOSTS: '["https://opensearch-node1:9200","https://opensearch-node2:9200"]' # Define the OpenSearch nodes that OpenSearch Dashboards will query
networks:
- opensearch-net
volumes:
opensearch-data1:
opensearch-data2:
networks:
opensearch-net: