stac-fastapi.elasticsearch 3.1.0

Description:

stacfastapi.elasticsearch 3.1.0

stac-fastapi-elasticsearch-opensearch (sfeos)



Elasticsearch and Opensearch backends for the stac-fastapi project.
Featuring stac-fastapi.core for simplifying the creation and maintenance of custom STAC api backends.




Online Documentation: https://stac-utils.github.io/stac-fastapi-elasticsearch-opensearch
Source Code: https://github.com/stac-utils/stac-fastapi-elasticsearch-opensearch

Notes:


Our Api core library can be used to create custom backends. See stac-fastapi-mongo for a working example.


Reach out on our Gitter channel or feel free to add to our Discussions page here on github.


There is Postman documentation here for examples on how to run some of the API routes locally - after starting the elasticsearch backend via the docker-compose.yml file.


The /examples folder shows an example of running stac-fastapi-elasticsearch from PyPI in docker without needing any code from the repository. There is also a Postman collection here that you can load into Postman for testing the API routes.


For changes, see the Changelog


We are always welcoming contributions. For the development notes: Contributing


To install from PyPI:
pip install stac_fastapi.elasticsearch

or
pip install stac_fastapi.opensearch

Build Elasticsearch API backend
docker-compose up elasticsearch
docker-compose build app-elasticsearch

Running Elasticsearch API on localhost:8080
docker-compose up app-elasticsearch

By default, docker-compose uses Elasticsearch 8.x and OpenSearch 2.11.1.
If you wish to use a different version, put the following in a
file named .env in the same directory you run docker-compose from:
ELASTICSEARCH_VERSION=7.17.1
OPENSEARCH_VERSION=2.11.0

The most recent Elasticsearch 7.x versions should also work. See the opensearch-py docs for compatibility information.
To create a new Collection:
curl -X "POST" "http://localhost:8080/collections" \
-H 'Content-Type: application/json; charset=utf-8' \
-d $'{
"id": "my_collection"
}'

Note: this "Collections Transaction" behavior is not part of the STAC API, but may be soon.
Configure the API
By default the API title and description are set to stac-fastapi-<backend>. Change the API title and description from the default by setting the STAC_FASTAPI_TITLE and STAC_FASTAPI_DESCRIPTION environment variables, respectively.
By default the API will read from and write to the collections and items_<collection name> indices. To change the API collections index and the items index prefix, change the STAC_COLLECTIONS_INDEX and STAC_ITEMS_INDEX_PREFIX environment variables.
The application root path is left as the base url by default. If deploying to AWS Lambda with a Gateway API, you will need to define the app root path to be the same as the Gateway API stage name where you will deploy the API. The app root path can be defined with the STAC_FASTAPI_ROOT_PATH environment variable (/v1, for example)
Collection pagination
The collections route handles optional limit and token parameters. The links field that is
returned from the /collections route contains a next link with the token that can be used to
get the next page of results.
curl -X "GET" "http://localhost:8080/collections?limit=1&token=example_token"

Ingesting Sample Data CLI Tool
Usage: data_loader.py [OPTIONS]

Load STAC items into the database.

Options:
--base-url TEXT Base URL of the STAC API [required]
--collection-id TEXT ID of the collection to which items are added
--use-bulk Use bulk insert method for items
--data-dir PATH Directory containing collection.json and feature
collection file
--help Show this message and exit.

python3 data_loader.py --base-url http://localhost:8080

Elasticsearch Mappings
Mappings apply to search index, not source. The mappings are stored in index templates on application startup.
These templates will be used implicitly when creating new Collection and Item indices.
Managing Elasticsearch Indices
Snapshots
This section covers how to create a snapshot repository and then create and restore snapshots with this.
Create a snapshot repository. This puts the files in the elasticsearch/snapshots in this git repo clone, as
the elasticsearch.yml and docker-compose files create a mapping from that directory to
/usr/share/elasticsearch/snapshots within the Elasticsearch container and grant permissions on using it.
curl -X "PUT" "http://localhost:9200/_snapshot/my_fs_backup" \
-H 'Content-Type: application/json; charset=utf-8' \
-d $'{
"type": "fs",
"settings": {
"location": "/usr/share/elasticsearch/snapshots/my_fs_backup"
}
}'

The next step is to create a snapshot of one or more indices into this snapshot repository. This command creates
a snapshot named my_snapshot_2 and waits for the action to be completed before returning. This can also be done
asynchronously, and queried for status. The indices parameter determines which indices are snapshotted, and
can include wildcards.
curl -X "PUT" "http://localhost:9200/_snapshot/my_fs_backup/my_snapshot_2?wait_for_completion=true" \
-H 'Content-Type: application/json; charset=utf-8' \
-d $'{
"metadata": {
"taken_because": "dump of all items",
"taken_by": "pvarner"
},
"include_global_state": false,
"ignore_unavailable": false,
"indices": "items_my-collection"
}'

To see the status of this snapshot:
curl http://localhost:9200/_snapshot/my_fs_backup/my_snapshot_2

To see all the snapshots:
curl http://localhost:9200/_snapshot/my_fs_backup/_all

To restore a snapshot, run something similar to the following. This specific command will restore any indices that
match items_* and rename them so that the new index name will be suffixed with -copy.
curl -X "POST" "http://localhost:9200/_snapshot/my_fs_backup/my_snapshot_2/_restore?wait_for_completion=true" \
-H 'Content-Type: application/json; charset=utf-8' \
-d $'{
"include_aliases": false,
"include_global_state": false,
"ignore_unavailable": true,
"rename_replacement": "items_$1-copy",
"indices": "items_*",
"rename_pattern": "items_(.+)"
}'

Now the item documents have been restored in to the new index (e.g., my-collection-copy), but the value of the
collection field in those documents is still the original value of my-collection. To update these to match the
new collection name, run the following Elasticsearch Update By Query command, substituting the old collection name
into the term filter and the new collection name into the script parameter:
curl -X "POST" "http://localhost:9200/items_my-collection-copy/_update_by_query" \
-H 'Content-Type: application/json; charset=utf-8' \
-d $'{
"query": {
"match_all": {}
},
"script": {
"lang": "painless",
"params": {
"collection": "my-collection-copy"
},
"source": "ctx._source.collection = params.collection"
}
}'

Then, create a new collection through the api with the new name for each of the restored indices:
curl -X "POST" "http://localhost:8080/collections" \
-H 'Content-Type: application/json' \
-d $'{
"id": "my-collection-copy"
}'

Voila! You have a copy of the collection now that has a resource URI (/collections/my-collection-copy) and can be
correctly queried by collection name.
Reindexing
This section covers how to reindex documents stored in Elasticsearch/OpenSearch.
A reindex operation might be useful to apply changes to documents or to correct dynamically generated mappings.
The index templates will make sure that manually created indices will also have the correct mappings and settings.
In this example, we will make a copy of an existing Item index items_my-collection-000001 but change the Item identifier to be lowercase.
curl -X "POST" "http://localhost:9200/_reindex" \
-H 'Content-Type: application/json' \
-d $'{
"source": {
"index": "items_my-collection-000001"
},
"dest": {
"index": "items_my-collection-000002"
},
"script": {
"source": "ctx._source.id = ctx._source.id.toLowerCase()",
"lang": "painless"
}
}'

If we are happy with the data in the newly created index, we can move the alias items_my-collection to the new index items_my-collection-000002.
curl -X "POST" "http://localhost:9200/_aliases" \
-h 'Content-Type: application/json' \
-d $'{
"actions": [
{
"remove": {
"index": "*",
"alias": "items_my-collection"
}
},
{
"add": {
"index": "items_my-collection-000002",
"alias": "items_my-collection"
}
}
]
}'

The modified Items with lowercase identifiers will now be visible to users accessing my-collection in the STAC API.
Auth
Authentication is an optional feature that can be enabled through Route Dependencies examples can be found and a more detailed explanation in examples/auth.
Aggregation
Sfeos supports the STAC API Aggregation Extension. This enables geospatial aggregation of points and geometries, as well as frequency distribution aggregation of any other property including dates. Aggregations can be defined at the root Catalog level (/aggregations) and at the Collection level (/<collection_id>/aggregations). The /aggregate route also fully supports base search and the STAC API Filter Extension. Any query made with /search may also be executed with /aggregate, provided that the relevant aggregation fields are available,
A field named aggregations should be added to the Collection object for the collection for which the aggregations are available, for example:
"aggregations": [
{
"name": "total_count",
"data_type": "integer"
},
{
"name": "datetime_max",
"data_type": "datetime"
},
{
"name": "datetime_min",
"data_type": "datetime"
},
{
"name": "datetime_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "datetime"
},
{
"name": "sun_elevation_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "numeric"
},
{
"name": "platform_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "string"
},
{
"name": "sun_azimuth_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "numeric"
},
{
"name": "off_nadir_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "numeric"
},
{
"name": "cloud_cover_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "numeric"
},
{
"name": "grid_code_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "string"
},
{
"name": "centroid_geohash_grid_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "string"
},
{
"name": "centroid_geohex_grid_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "string"
},
{
"name": "centroid_geotile_grid_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "string"
},
{
"name": "geometry_geohash_grid_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "numeric"
},
{
"name": "geometry_geotile_grid_frequency",
"data_type": "frequency_distribution",
"frequency_distribution_data_type": "string"
}
]

Available aggregations are:

total_count (count of total items)
collection_frequency (Item collection field)
platform_frequency (Item.Properties.platform)
cloud_cover_frequency (Item.Properties.eo:cloud_cover)
datetime_frequency (Item.Properties.datetime, monthly interval)
datetime_min (earliest Item.Properties.datetime)
datetime_max (latest Item.Properties.datetime)
sun_elevation_frequency (Item.Properties.view:sun_elevation)
sun_azimuth_frequency (Item.Properties.view:sun_azimuth)
off_nadir_frequency (Item.Properties.view:off_nadir)
grid_code_frequency (Item.Properties.grid:code)
centroid_geohash_grid_frequency (geohash grid on Item.Properties.proj:centroid)
centroid_geohex_grid_frequency (geohex grid on Item.Properties.proj:centroid)
centroid_geotile_grid_frequency (geotile on Item.Properties.proj:centroid)
geometry_geohash_grid_frequency (geohash grid on Item.geometry)
geometry_geotile_grid_frequency (geotile grid on Item.geometry)

Support for additional fields and new aggregations can be added in the associated database_logic.py file.