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As a validation of the ingests done using the [1] new airflow based pipeline, this issue runs the ingestion using both [1] and [2] legacy step functions based pipeline.
The ingest is initiated via the veda-stac-ingestor api, endpoint /dataset/publish with the same inputs for both except the collection id, as can be seen below:
For [2], the input was:
{
"collection": "lis-global-da-tws-trend",
"title": "Terrestrial Water Storage Trend - LIS 10km Global DA",
"description": "Gridded trend in terrestrial water storage (theil-sen slope estimation in mm yr-1) from 10km global LIS with assimilation",
"license": "CC0-1.0",
"is_periodic": false,
"time_density": null,
"spatial_extent": {
"xmin": -179.95,
"ymin": -59.45,
"xmax": 179.95,
"ymax": 83.55
},
"temporal_extent": {
"startdate": "2003-01-01T00:00:00Z",
"enddate": "2021-12-31T23:59:59Z"
},
"sample_files": [
"s3://veda-data-store-staging/EIS/COG/LIS_GLOBAL_DA/DA_Trends/DATWS_STL_based_trend.cog.tif"
],
"discovery_items": [
{
"collection": "lis-global-da-tws-trend-airflow",
"discovery": "s3",
"cogify": false,
"upload": false,
"dry_run": false,
"prefix": "EIS/COG/LIS_GLOBAL_DA/DA_Trends/",
"bucket": "veda-data-store-staging",
"filename_regex": "(.*)DATWS_STL_based_trend.cog.tif$",
"start_datetime": "2003-01-01T00:00:00Z",
"end_datetime": "2021-12-31T23:59:59Z"
}
]
}
Similarly, for [1], the input was:
{
"collection": "lis-global-da-tws-trend-airflow",
"title": "Terrestrial Water Storage Trend - LIS 10km Global DA",
"description": "Gridded trend in terrestrial water storage (theil-sen slope estimation in mm yr-1) from 10km global LIS with assimilation",
"license": "CC0-1.0",
"is_periodic": false,
"time_density": null,
"spatial_extent": {
"xmin": -179.95,
"ymin": -59.45,
"xmax": 179.95,
"ymax": 83.55
},
"temporal_extent": {
"startdate": "2003-01-01T00:00:00Z",
"enddate": "2021-12-31T23:59:59Z"
},
"sample_files": [
"s3://veda-data-store-staging/EIS/COG/LIS_GLOBAL_DA/DA_Trends/DATWS_STL_based_trend.cog.tif"
],
"discovery_items": [
{
"collection": "lis-global-da-tws-trend-airflow",
"discovery": "s3",
"cogify": false,
"upload": false,
"dry_run": false,
"prefix": "EIS/COG/LIS_GLOBAL_DA/DA_Trends/",
"bucket": "veda-data-store-staging",
"filename_regex": "(.*)DATWS_STL_based_trend.cog.tif$",
"start_datetime": "2003-01-01T00:00:00Z",
"end_datetime": "2021-12-31T23:59:59Z"
}
]
}
After the ingestion run was done, the stac records for both were compared and they look like the following:
On comparison, the STAC records look exactly the same for ingests from both systems [1] and [2].
Note: Did notice a discrepancy where the context["matched"] value is wrong for the airflow ingestion, but that's an auto-generated value and not because of any ingestion faults, right @anayeaye?
@slesaad Thanks for posting this comparison. I'm actually not seeing the difference in the number matched for each collection. What endpoint returned that matched 0 result? I tried /collections/<collection-id>/items and the /search endpoints below and see one match for each collection (hopefully I didn't use the wrong collection ids but can't see it yet 🙃 ).
Description
As a validation of the ingests done using the [1] new airflow based pipeline, this issue runs the ingestion using both [1] and [2] legacy step functions based pipeline.
The ingest is initiated via the
veda-stac-ingestor
api, endpoint/dataset/publish
with the same inputs for both except the collection id, as can be seen below:For [2], the input was:
Similarly, for [1], the input was:
After the ingestion run was done, the stac records for both were compared and they look like the following:
Collection
[1]
[2]
Items
[1]
[2]
Comparison
On comparison, the STAC records look exactly the same for ingests from both systems [1] and [2].
PI Objective
https://github.com/NASA-IMPACT/veda-architecture/issues/164
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