c32f13a909
1800: Analytics r=irevoire a=irevoire
Closes #1784
Implements [this spec](https://github.com/meilisearch/specifications/blob/update-analytics-specs/text/0034-telemetry-policies.md)
# Anonymous Analytics Policy
## 1. Functional Specification
### I. Summary
This specification describes an exhaustive list of anonymous metrics collected by the MeiliSearch binary. It also describes the tools we use for this collection and how we identify a Meilisearch instance.
### II. Motivation
At MeiliSearch, our vision is to provide an easy-to-use search solution that meets the essential needs of our users. At all times, we strive to understand our users better and meet their expectations in the best possible way.
Although we can gather needs and understand our users through several channels such as Github, Slack, surveys, interviews or roadmap votes, we realize that this is not enough to have a complete view of MeiliSearch usage and features adoption. By cross-referencing our product discovery phases with aggregated quantitative data, we want to make the product much better than what it is today. Our decision-making will be taken a step further to make a product that users love.
### III. Explanation
#### General Data Protection Regulation (GDPR)
The metrics collected are non-sensitive, non-personal and do not identify an individual or a group of individuals using MeiliSearch. The data collected is secured and anonymized. We do not collect any data from the values stored in the documents.
We, the MeiliSearch team, provide an email address so that users can request the removal of their data: privacy@meilisearch.com.<br>
Thanks to the unique identifier generated for their MeiliSearch installation (`Instance uuid` when launching MeiliSearch), we can remove the corresponding data from all the tools we describe below. Any questions regarding the management of the data collected can be sent to the email address as well.
#### Tools
##### Segment
The collected data is sent to [Segment](https://segment.com/). Segment is a platform for data collection and provides data management tools.
##### Amplitude
[Amplitude](https://amplitude.com/) is a tool for graphing and highlighting collected data. Segment feeds Amplitude so that we can build visualizations according to our needs.
-----------
# The `identify` call we send every hour:
## System Configuration `system`
This property allows us to gather essential information to better understand on which type of machine MeiliSearch is used. This allows us to better advise users on the machines to choose according to their data volume and their use-cases.
- [x] `system` => Never changes but still sent every hours
- [x] distribution | On which distribution MeiliSearch is launched, eg: Arch Linux
- [x] kernel_version | On which kernel version MeiliSearch is launched, eg: 5.14.10-arch1-1
- [x] cores | How many cores does the machine have, eg: 24
- [x] ram_size | Total capacity of the machine's ram. Expressed in `Kb`, eg: 33604210
- [x] disk_size | Total capacity of the biggest disk. Expressed in `Kb`, eg: 336042103
- [x] server_provider | Users can tell us on which provider MeiliSearch is hosted by filling the `MEILI_SERVER_PROVIDER` env var. This is also filled by our providers deploy scripts. e.g. GCP [cloud-config.yaml](
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.github | ||
assets | ||
meilisearch-error | ||
meilisearch-http | ||
meilisearch-lib | ||
.dockerignore | ||
.gitignore | ||
bors.toml | ||
Cargo.lock | ||
Cargo.toml | ||
CODE_OF_CONDUCT.md | ||
CONTRIBUTING.md | ||
Cross.toml | ||
Dockerfile | ||
download-latest.sh | ||
LICENSE | ||
README.md | ||
SECURITY.md |
MeiliSearch
Website | Roadmap | Blog | LinkedIn | Twitter | Documentation | FAQ
⚡ Lightning Fast, Ultra Relevant, and Typo-Tolerant Search Engine 🔍
MeiliSearch is a powerful, fast, open-source, easy to use and deploy search engine. Both searching and indexing are highly customizable. Features such as typo-tolerance, filters, and synonyms are provided out-of-the-box. For more information about features go to our documentation.
✨ Features
- Search-as-you-type experience (answers < 50 milliseconds)
- Full-text search
- Typo tolerant (understands typos and misspelling)
- Faceted search and filters
- Supports hanzi (Chinese characters)
- Supports synonyms
- Easy to install, deploy, and maintain
- Whole documents are returned
- Highly customizable
- RESTful API
Getting started
Deploy the Server
Homebrew (Mac OS)
brew update && brew install meilisearch
meilisearch
Docker
docker run -p 7700:7700 -v "$(pwd)/data.ms:/data.ms" getmeili/meilisearch
Announcing a cloud-hosted MeiliSearch
Join the closed beta by filling out this form.
Try MeiliSearch in our Sandbox
Create a MeiliSearch instance in MeiliSearch Sandbox. This instance is free, and will be active for 48 hours.
Run on Digital Ocean
Deploy on Platform.sh
APT (Debian & Ubuntu)
echo "deb [trusted=yes] https://apt.fury.io/meilisearch/ /" > /etc/apt/sources.list.d/fury.list
apt update && apt install meilisearch-http
meilisearch
Download the binary (Linux & Mac OS)
curl -L https://install.meilisearch.com | sh
./meilisearch
Compile and run it from sources
If you have the latest stable Rust toolchain installed on your local system, clone the repository and change it to your working directory.
git clone https://github.com/meilisearch/MeiliSearch.git
cd MeiliSearch
cargo run --release
Create an Index and Upload Some Documents
Let's create an index! If you need a sample dataset, use this movie database. You can also find it in the datasets/
directory.
curl -L 'https://bit.ly/2PAcw9l' -o movies.json
Now, you're ready to index some data.
curl -i -X POST 'http://127.0.0.1:7700/indexes/movies/documents' \
--header 'content-type: application/json' \
--data-binary @movies.json
Search for Documents
In command line
The search engine is now aware of your documents and can serve those via an HTTP server.
The jq
command-line tool can greatly help you read the server responses.
curl 'http://127.0.0.1:7700/indexes/movies/search?q=botman+robin&limit=2' | jq
{
"hits": [
{
"id": "415",
"title": "Batman & Robin",
"poster": "https://image.tmdb.org/t/p/w1280/79AYCcxw3kSKbhGpx1LiqaCAbwo.jpg",
"overview": "Along with crime-fighting partner Robin and new recruit Batgirl, Batman battles the dual threat of frosty genius Mr. Freeze and homicidal horticulturalist Poison Ivy. Freeze plans to put Gotham City on ice, while Ivy tries to drive a wedge between the dynamic duo.",
"release_date": 866768400
},
{
"id": "411736",
"title": "Batman: Return of the Caped Crusaders",
"poster": "https://image.tmdb.org/t/p/w1280/GW3IyMW5Xgl0cgCN8wu96IlNpD.jpg",
"overview": "Adam West and Burt Ward returns to their iconic roles of Batman and Robin. Featuring the voices of Adam West, Burt Ward, and Julie Newmar, the film sees the superheroes going up against classic villains like The Joker, The Riddler, The Penguin and Catwoman, both in Gotham City… and in space.",
"release_date": 1475888400
}
],
"nbHits": 8,
"exhaustiveNbHits": false,
"query": "botman robin",
"limit": 2,
"offset": 0,
"processingTimeMs": 2
}
Use the Web Interface
We also deliver an out-of-the-box web interface in which you can test MeiliSearch interactively.
You can access the web interface in your web browser at the root of the server. The default URL is http://127.0.0.1:7700. All you need to do is open your web browser and enter MeiliSearch’s address to visit it. This will lead you to a web page with a search bar that will allow you to search in the selected index.
Documentation
Now that your MeiliSearch server is up and running, you can learn more about how to tune your search engine in the documentation.
Contributing
Hey! We're glad you're thinking about contributing to MeiliSearch! Feel free to pick an issue labeled as good first issue
, and to ask any question you need. Some points might not be clear and we are available to help you!
Also, we recommend following the CONTRIBUTING to create your PR.
Core engine and tokenizer
The code in this repository is only concerned with managing multiple indexes, handling the update store, and exposing an HTTP API.
Search and indexation are the domain of our core engine, milli
, while tokenization is handled by our tokenizer
library.
Telemetry
MeiliSearch collects anonymous data regarding general usage. This helps us better understand developers' usage of MeiliSearch features.
To find out more on what information we're retrieving, please see our documentation on Telemetry.
This program is optional, you can disable these analytics by using the MEILI_NO_ANALYTICS
env variable.
Feature request
The feature requests are not managed in this repository. Please visit our dedicated repository to see our work about the MeiliSearch product.
If you have a feature request or any feedback about an existing feature, please open a discussion. Also, feel free to participate in the current discussions, we are looking forward to reading your comments.
💌 Contact
Please visit this page.
MeiliSearch is developed by Meili, a young company. To know more about us, you can read our blog. Any suggestion or feedback is highly appreciated. Thank you for your support!