The repository has been migrated to https://github.com/SimpleElasticLanguage/server
Simple Elastic Language offer an easy way to query ElasticSearch for everybody even no-tech people and even on a big, complex and nested schema.
The project is split into two sub projects:
- SEL, which is the library
- SEL Server, unlock quick usage by connecting directly to ES.
Two first digits of SEL version match Elasticsearch version and then it's the inner SEL version, eg 7.17.1 works with ES 7.17, v1 of SEL for this version of ES
SEL doc - Containing Big queries' examples and all the query synthax
SEL Server doc
SEL was initially developed for Heuritech in 2016 and used by everybody inside the compagny tech and no-tech people since that time to explore internal data, generate reports and analysis.
SEL is using index schema to generate queries.
Be aware it will request ES schema at any query generation.
See SEL repository for library usage.
curl -X POST -H "Content-Type: application/json" -d '{"query": "category = person"}' http://localhost:9000/search/ms_coco_2017
curl -X POST -H "Content-Type: application/json" -d '{"query": {"field": "category", "value": "person"}}' http://localhost:9000/search/ms_coco_2017
ghcr.io/arnaudparant/sel_server:v7.17.1
You need to get a dataset to test the service.
This dataset has been generated from the official MS COCO 2017, without the person keypoints, using the convertor.py
wget http://simpleelasticlanguage.com/datasets/ms_coco_2017/ms_coco_2017.ndjson
wget http://simpleelasticlanguage.com/datasets/ms_coco_2017/schemas/schema_es_7.json
First install docker
docker-compose up -d
Go to: localhost:9000
First time you need to insert some data.
This one made 500Mo, but you can use only a sample to test and insert quicker
./scripts/elastic.py ms_coco_2017.ndjson schema_es_7.json ms_coco_2017 --http-auth sel:onlyfortests -v
Curl query for 1 person and 2 animals in the image, returning only image url
curl -X POST -H "Content-Type: application/json" -d '{"query": "category = person where count = 1 and supercategory = animal where supercount = 2"}' http://localhost:9000/search/ms_coco_2017 | jq -r '.results.hits.hits[]._source.url'
Don't forget to stop the server after use
docker-compose down
SEL Server is available for test purpose on simpleelasticlanguage.com:9000 with MS COCO 2017 dataset
Curl query for 1 person and 2 animals in the image, returning only image url
curl -X POST -H "Content-Type: application/json" -d '{"query": "category = person where count = 1 and supercategory = animal where supercount = 2"}' http://simpleelasticlanguage.com:9000/search/ms_coco_2017 | jq -r '.results.hits.hits[]._source.url'
- ES_HOSTS - Comma separated url of your cluster, such "http://elasticsearch:9200"
- ES_CLOUD_ID - Alternative way of connecting to your cluster such: "cluster-1:dXMa5Fx..."
- ES_AUTH - Auth to connect to your cluster, such: "user:password"
- ES_API_KEY - Alternative auth system with base64 encoded tuple, such: "aWQ6YXBpX2tleQ=="
- ES_HTTP_COMPRESS - Set "true" to activate
- ES_SSL_CONTEXT_FILEPATH - Set filepath to the ssl certificate to activate, such: "path/to/cert.pem", (requires to mount the file in a RO volume)
PS: Don't forget to use secrets to securize sensitive variables in your environments.
- docker - Build SEL Server docker
- docker-test - Build SEL Server test docker
- lint - Lint the code
- tests - Run all tests
- upshell - Up a shell into a docker, useful to run only few tests
- down-tests - Down tests, in case of failed tests
- doc - Get latest documentation json
- clean - Clean all
__pycache__
Fail to start with the following error
[1]: max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]
Execute the following command
sysctl -w vm.max_map_count=262144
Fail to start with the following error
Caused by: java.nio.file.AccessDeniedException: /usr/share/elasticsearch/data/nodes
Execute the following command
chown -R 1000:root /usr/share/elasticsearch/data