Skip to main content

udata search service

Project description

udata-search-service

A search service for udata. The idea is to have search service separated from the udata MongoDB. The indexation update is made using real-time HTTP messages.

See the following architecture schema: Udata Search Service architecture schema

Getting started

You can follow this recommended architecture for your code:

$WORKSPACE
├── fs
├── udata
│   ├── ...
│   └── setup.py
│		└── udata.cfg
├── udata-front
│   ├── ...
│   └── setup.py
└── udata-search-service
    ├── ...
    └── pyproject.toml

Clone the repository:

cd $WORKSPACE
git clone git@github.com:opendatateam/udata-search-service.git

Start the different services using docker-compose:

cd udata-search-service
docker-compose up

This will start:

  • an elasticsearch
  • a search app

Initialize the elasticsearch indices on setup.

# Locally
udata-search-service init-es

# In the docker context
docker-compose run --entrypoint /bin/bash web -c 'udata-search-service init-es'

This will create the following indices:

  • {UDATA_INSTANCE_NAME}-dataset-{yyyy}-{mm}-{dd}-{HH}-{MM}
  • {UDATA_INSTANCE_NAME}-reuse-{yyyy}-{mm}-{dd}-{HH}-{MM}
  • {UDATA_INSTANCE_NAME}-organization-{yyyy}-{mm}-{dd}-{HH}-{MM}

Configure your udata to use the search service, by updating the following variables in your udata.cfg. Ex in local:

    SEARCH_SERVICE_API_URL = 'http://127.0.0.1:5000/api/1/'

Using udata, when you modify objects, indexation messages will be sent to the search app and will be consumed by the API. If you want to reindex your local mongo base in udata, you can run:

cd $WORKSPACE/udata/
source ./venv/bin/activate
udata search index

Make sure to have the corresponding UDATA_INSTANCE_NAME specified in your udata settings.

After a reindexation, you'll need to change the alias by using the following command:

# Locally
udata-search-service set-alias <index-suffix>

# In the docker context
docker-compose run --entrypoint /bin/bash web -c 'udata-search-service set-alias <index-suffix>'

You can query the search service with the search service api, ex: http://localhost:5000/api/1/datasets/?q=toilettes%20à%20rennes

Development

You can create a virtualenv, activate it and install the requirements with the following commands.

python3 -m venv venv
source venv/bin/activate
make deps
make install

You can start the web search service with the following command:

udata-search-service run

Deployment

The project depends on ElasticSearch 7.16.

Elasticsearch requires the Analysis ICU plugin for your specific version. On Debian, you can take a look at these instructions for installation.

Troubleshooting

  • If the elasticsearch service exits with an error 137, it is killed due to out of memory error. You should read the following points.
  • If you are short on RAM, you can limit heap memory by setting ES_JAVA_OPTS=-Xms750m -Xmx750m as environment variable when starting the elasticsearch service.
  • If you are on MAC and still encounter RAM memory issues, you should increase Docker limit memory to 4GB instead of default 2GB.
  • If you are on Linux, you may need to double the vm.max_map_count. You can set it with the following command: sysctl -w vm.max_map_count=262144.
  • If you are on Linux, you may encounter permissions issues. You can either create the volume or change the user to the current user using chown.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

udata-search-service-2.0.1.dev231.tar.gz (41.7 kB view details)

Uploaded Source

Built Distribution

udata_search_service-2.0.1.dev231-py2.py3-none-any.whl (18.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file udata-search-service-2.0.1.dev231.tar.gz.

File metadata

File hashes

Hashes for udata-search-service-2.0.1.dev231.tar.gz
Algorithm Hash digest
SHA256 9b750b4c50b4c2f664f720f63420dfde049ebd65cf62f395fc2f710d877c57f6
MD5 6956b2500e80e9e06e08b58f6b82c7a0
BLAKE2b-256 2ca2a308d51285c92cd2cb71efa28e32a0a9c6ea0ca60e1f93b4a45629d12e90

See more details on using hashes here.

File details

Details for the file udata_search_service-2.0.1.dev231-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for udata_search_service-2.0.1.dev231-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 30889149f71d60e5197517ba33b50782cc2bac86944cbe878bdc77ff2121cf9c
MD5 e4ed58efd0a156800ae04cedec25a1c0
BLAKE2b-256 0e4a4f293362ec22a7f87fcb403807cb31b347e4cffa385b2a72ecd807fb8662

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page