The Watson API runs queries in the background using Celery.
Those wishing to add queries to the API simply need to add a SQL file (file
extension .sql) to the queries directory (anywhere they choose inside that
directory). Once the file is included, an endpoint will be generated of the form
[hostname]/api/<api_version>/query/<subdirectories_if_any>/<query_file_name> like
[hostname]/api/v1/query/sherlock/sample_query or [hostname]/api/v1/query/sample_query.
After a successful POST request to these endpoints, you will see the resource
where the results for that query can be retrieved with a GET request (when they are ready).
Most use-cases will require the input of parameters into the queries. This can be
achieved by including the parameters in the SQL files as {<parameter_name>}
where replacing them with the value would yield a valid SQL query. Then to run
your query, simply add all your query parameters as a query string to your request.
For example, if the query needs start_date and end_date include something like
date BETWEEN {start_date} AND {end_date} in your query and make your POST request like
curl -i -X POST [hostname]/api/v1/query/sherlock/sample_query?start_date=2015-09-28&end_date=2018-06-08.
Your query will then be properly parameterized!
Note that should you forget the query parameters or misspell them, you will receive a response with the query showing its parameters and the parameters you need to provide instead of the resource to retrieve your result.
Query results will be automatically removed 24 hours after their creation.
Note that this has been built for small queries. Issues may arise with queries that have large outputs.
Python 3, Flask, Celery, RabbitMQ, MongoDB, SQLAlchemy, PyMongo, Docker
- MongoDB:
FROM mongo:3.6.3-jessie - RabbitMQ:
FROM rabbitmq:3.7.4-management-alpine
Stefanie Molin
