Summary of recommendations/changes in Mapping

Following some of the recommendations presented on Monday 25th, here are some stats to help to make decision about how ES performance improves.

https://docs.google.com/document/d/11rdMT-ZoFpOmJY4ND1ujb5kwyiSZCMro7_47QbkiY9U

Region field

Change mapping for “regions” field, getting rid of “nested” type and using a plain “keyword” field (concatenating region_type and region) and then to use “regex” in aggregations.

Data changes

New mapping for regions:

"regions": {"type": "keyword"},
"region_type": {"type": "keyword"},

Data before:

"regions": [
      {
        "uri": "http://linked.data.gov.au/dataset/asgs2016/stateorterritory/5",
        "label": "Western Australia",
        "dataset": {
          "uri": "http://linked.data.gov.au/dataset/asgs2016/stateorterritory",
          "label": "States and territories"
        }
      },
      {
        "uri": "http://linked.data.gov.au/dataset/wwf-terr-ecoregions/14110",
        "label": "Southwest Australia savanna",
        "dataset": {
          "uri": "http://linked.data.gov.au/dataset/wwf-terr-ecoregions",
          "label": "WWF ecoregions"
        }
      },
      {
        "uri": "http://linked.data.gov.au/dataset/local-gov-areas-2011/56790",
        "label": "Northampton (S)",
        "dataset": {
          "uri": "http://linked.data.gov.au/dataset/local-gov-areas-2011",
          "label": "Local government areas"
        }
      },
      {
        "uri": "http://linked.data.gov.au/dataset/nrm-2017/5010",
        "label": "Northern Agricultural Region",
        "dataset": {
          "uri": "http://linked.data.gov.au/dataset/nrm-2017",
          "label": "NRM regions"
        }
      },
      {
        "uri": "http://linked.data.gov.au/dataset/capad-2018-terrestrial/BHA_26",
        "label": "Eurardy",
        "dataset": {
          "uri": "http://linked.data.gov.au/dataset/capad-2018-terrestrial",
          "label": "Terrestrial CAPAD regions"
        }
      },
      {
        "uri": "http://linked.data.gov.au/dataset/bioregion/GES01",
        "label": "Geraldton Hills",
        "dataset": {
          "uri": "http://linked.data.gov.au/dataset/bioregion",
          "label": "Subregions"
        }
      },
      {
        "uri": "http://linked.data.gov.au/dataset/bioregion/GES",
        "label": "Geraldton Sandplains",
        "dataset": {
          "uri": "http://linked.data.gov.au/dataset/bioregion/IBRA7",
          "label": "Bioregions"
        }
      }
],

Data after:

"regions": [
      "http://linked.data.gov.au/dataset/asgs2016/stateorterritory|http://linked.data.gov.au/dataset/asgs2016/stateorterritory/5",
      "http://linked.data.gov.au/dataset/wwf-terr-ecoregions|http://linked.data.gov.au/dataset/wwf-terr-ecoregions/14110",
      "http://linked.data.gov.au/dataset/local-gov-areas-2011|http://linked.data.gov.au/dataset/local-gov-areas-2011/56790",
      "http://linked.data.gov.au/dataset/nrm-2017|http://linked.data.gov.au/dataset/nrm-2017/5010",
      "http://linked.data.gov.au/dataset/capad-2018-terrestrial|http://linked.data.gov.au/dataset/capad-2018-terrestrial/BHA_26",
      "http://linked.data.gov.au/dataset/bioregion|http://linked.data.gov.au/dataset/bioregion/GES01",
      "http://linked.data.gov.au/dataset/bioregion/IBRA7|http://linked.data.gov.au/dataset/bioregion/GES"
],
"region_types": [
      "http://linked.data.gov.au/dataset/asgs2016/stateorterritory",
      "http://linked.data.gov.au/dataset/wwf-terr-ecoregions",
      "http://linked.data.gov.au/dataset/local-gov-areas-2011",
      "http://linked.data.gov.au/dataset/nrm-2017",
      "http://linked.data.gov.au/dataset/capad-2018-terrestrial",
      "http://linked.data.gov.au/dataset/bioregion",
      "http://linked.data.gov.au/dataset/bioregion/IBRA7"
]

Index size stats

Approach	No docs	No docs (incl. hidden docs)	Docs increase
Nested docs	2,563,630	27,284,158	x10.64278
Keyword	2,563,630	10,292,406	x4.014778

Old index is ~2.65 times bigger in terms of number of documents

ES Queries

Old query for regions aggregation:

{
    "aggs": {
        "nested_agg": {
            "nested": {
                "path": "regions"
            },
            "aggs": {
                "value": {
                    "terms": {
                        "field": "regions.dataset.uri",
                        "size": 1000
                    }
                }
            }
        }
    },
    "size": 0
}

{
    "aggs": {
        "nested_agg": {
            "nested": {
                "path": "regions"
            },
            "aggs": {
                "filtering": {
                    "filter": {
                        "term": {
                            "regions.dataset.uri": "http://linked.data.gov.au/dataset/asgs2016/stateorterritory"
                        }
                    },
                    "aggs": {
                        "value": {
                            "terms": {
                                "field": "regions.uri",
                                "size": 1000
                            }
                        }
                    }
                }
            }
        }
    },
    "size": 0
}

New queries:

{
    "aggs": {
        "regions": {
            "terms": {
                "field": "region_types"
            }
        }
    },
    "size": 0,
    "track_total_hits": true
}

{
    "aggs": {
        "regions": {
            "terms": {
                "field": "regions",
                "include": "http://linked.data.gov.au/dataset/bioregion\\|.*"
            }
        }
    },
    "size": 0,
    "track_total_hits": true
}

Requests time stats

Summary Excel:

JSONs with results of tests:

POSTMAN queries (collection) → Importable to Postman by anyone.

Not nested regions is slighly faster in most of the executions