Takes datasets and extracts the facets from the files/filepath. The scanner works to map a file path to the specific handler for that collection of files. For example, ESA CCI datasets are scanned by the cci handler. This is because each collection of datasets will have different characteristics and will need to be treated in a different way.
facet_scanner (path_to_scan) [--conf <path_to_config.ini>]
Required:
Argument | Description |
---|---|
path_to_scan | File path in the archive to use as the basis of the scan. The scanner will take this path and retrieve all the files in the elasticsearch index at this point. |
Optional:
Option | No. Arguments | Description |
---|---|---|
--conf |
1 | Allows you to set a different location for the config file.This defaults to ../conf/facet_scanner.ini relative to the script. |
Adding a Handler Documentation
This repo also provides the code to read from the rabbit queue and process updates to the files index, adding facets.
Watched events:
- DEPOSIT
Exposed Queue Consumer Classes:
rabbit_facet_indexer.queue_consumers.FacetScannerQueueConsumer
Configuration is handled using a YAML file. The full configuration options are described in the rabbit_indexer repo
This process also requires an environment variable JSON_TAGGER_ROOT
. This should be set to
the json
directory which contains the tagging json.
The required sections for the facet indexer are:
- rabbit_server
- indexer
- logging
- moles
- elasticsearch
- files_index
An example YAML file (secrets noted by ***** ):
---
rabbit_server:
name: "*****"
user: "*****"
password: "*****"
vhost: "*****"
source_exchange:
name: deposit_logs
type: fanout
dest_exchange:
name: fbi_fanout
type: fanout
queues:
- name: elasticsearch_update_queue_opensearch_tags_test
kwargs:
auto_delete: false
- name: elasticsearch_update_queue_opensearch_tags_test
bind_kwargs:
routing_key: opensearch.tagger.cci
indexer:
queue_consumer_class: rabbit_facet_indexer.queue_consumers.FacetScannerQueueConsumer
path_filter:
paths:
- /neodc/esacci
filter_policy: 2
logging:
log_level: info
moles:
moles_obs_map_url: http://api.catalogue.ceda.ac.uk/api/v2/observations.json/?publicationState__in=citable,published,preview,removed&fields=publicationState,result_field,title,uuid
elasticsearch:
es_api_key: "*****"
files_index:
name: ceda-fbi
calculate_md5: false
scan_level: 2
The indexer can be run using the helper script provided by rabbit_indexer repo. This uses an entry script and parses the config file to run your selected queue_consumer_class:
rabbit_event_indexer --conf <path_to_configuration_file>