Elasticsearch - generic facets structure - calculating aggregations combined with filters

Question

In a new project of ours, we were inspired by this article http://project-a.github.io/on-site-search-design-patterns-for-e-commerce/#generic-faceted-search for doing our “fa

Answer 1

The only way I can see forward with this model, is to calculate the aggregation for each selected facet and somehow merge the result.

This is exactly right. If one facet (e.g. brand) is selected than you can not use global brand filter if you also want to fetch other brands for multi-selection. What you can do is apply all other filters on selected facets, and all filters on non-selected facets. As a results you will have n+1 separate aggregations for n selected filters - first one is for all facets and the rest are for selected facets.

In your case query might look like:

{
  "aggs": {
    "agg_attr_strings_filter": {
      "filter": {
        "bool": {
          "filter": [
            {
              "nested": {
                "query": {
                  "bool": {
                    "filter": [
                      {
                        "term": {
                          "attributeStrings.facetName": {
                            "value": "Property"
                          }
                        }
                      },
                      {
                        "terms": {
                          "attributeStrings.facetValue": [
                            "Organic"
                          ]
                        }
                      }
                    ]
                  }
                },
                "path": "attributeStrings"
              }
            },
            {
              "nested": {
                "query": {
                  "bool": {
                    "filter": [
                      {
                        "term": {
                          "attributeStrings.facetName": {
                            "value": "Brand"
                          }
                        }
                      },
                      {
                        "terms": {
                          "attributeStrings.facetValue": [
                            "Adidas"
                          ]
                        }
                      }
                    ]
                  }
                },
                "path": "attributeStrings"
              }
            }
          ]
        }
      },
      "aggs": {
        "agg_attr_strings": {
          "nested": {
            "path": "attributeStrings"
          },
          "aggs": {
            "attr_name": {
              "terms": {
                "field": "attributeStrings.facetName"
              },
              "aggs": {
                "attr_value": {
                  "terms": {
                    "field": "attributeStrings.facetValue",
                    "size": 1000,
                    "order": [
                      {
                        "_term": "asc"
                      }
                    ]
                  }
                }
              }
            }
          }
        }
      }
    },
    "special_agg_property": {
      "filter": {
        "nested": {
          "query": {
            "bool": {
              "filter": [
                {
                  "term": {
                    "attributeStrings.facetName": {
                      "value": "Brand"
                    }
                  }
                },
                {
                  "terms": {
                    "attributeStrings.facetValue": [
                      "Adidas"
                    ]
                  }
                }
              ]
            }
          },
          "path": "attributeStrings"
        }
      },
      "aggs": {
        "special_agg_property": {
          "nested": {
            "path": "attributeStrings"
          },
          "aggs": {
            "agg_filtered_special": {
              "filter": {
                "query": {
                  "match": {
                    "attributeStrings.facetName": "Property"
                  }
                }
              },
              "aggs": {
                "facet_value": {
                  "terms": {
                    "size": 1000,
                    "field": "attributeStrings.facetValue"
                  }
                }
              }
            }
          }
        }
      }
    },
    "special_agg_brand": {
      "filter": {
        "nested": {
          "query": {
            "bool": {
              "filter": [
                {
                  "term": {
                    "attributeStrings.facetName": {
                      "value": "Property"
                    }
                  }
                },
                {
                  "terms": {
                    "attributeStrings.facetValue": [
                      "Organic"
                    ]
                  }
                }
              ]
            }
          },
          "path": "attributeStrings"
        }
      },
      "aggs": {
        "special_agg_brand": {
          "nested": {
            "path": "attributeStrings"
          },
          "aggs": {
            "agg_filtered_special": {
              "filter": {
                "query": {
                  "match": {
                    "attributeStrings.facetName": "Brand"
                  }
                }
              },
              "aggs": {
                "facet_value": {
                  "terms": {
                    "size": 1000,
                    "field": "attributeStrings.facetValue"
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

This query looks super big and scary but generating such query can be done with few dozen lines of code. When parsing query results, you need to first parse general aggregation (one that uses all filters) and after special facet aggregations. From the upper example, first parse results from agg_attr_strings_filter but those results will also contain aggregation values for Brand and Property that should be overwritten by aggregation values from special_agg_property and special_agg_brand Also, this query is efficient since Elasticsearch does good job in caching separate filter clauses so applying same filters in different parts of query should be cheap.

But it seems very complex and kind of defeats the point of having the model as described in the article, so I hope there's a more clean solution and someone can give a hint at something to try.

There is really no way around the fact that you need to apply different filters to different facets and at the same time have different query filters. If you need to support "correct e-commerce facet behavior" you will have complex query :)

Disclaimer: I'm coauthor of the mentioned article.

Answer 2

The issue comes from the fact that you are adding a filter on Property and Organic inside your aggregation, hence the more facets you pick, the more you will restrain the terms you will get. In that article, the filter they use is in fact a post_filter, both names were allowed until recently, but filter got removed because that was causing ambiguities.

What you need to do is to move that filter outside the aggregations into the post_filter section, so that the results get correctly filtered out by whatever facets have been picked, but all your facets still get computed correctly on the whole document set.

{
  "post_filter": {
    "bool": {
      "filter": [
        {
          "nested": {
            "query": {
              "bool": {
                "filter": [
                  {
                    "term": {
                      "attributeStrings.facetName": {
                        "value": "Property"
                      }
                    }
                  },
                  {
                    "terms": {
                      "attributeStrings.facetValue": [
                        "Organic"
                      ]
                    }
                  }
                ]
              }
            },
            "path": "attributeStrings"
          }
        },
        {
          "nested": {
            "query": {
              "bool": {
                "filter": [
                  {
                    "term": {
                      "attributeStrings.facetName": {
                        "value": "Brand"
                      }
                    }
                  },
                  {
                    "terms": {
                      "attributeStrings.facetValue": [
                        "Adidas"
                      ]
                    }
                  }
                ]
              }
            },
            "path": "attributeStrings"
          }
        }
      ]
    }
  },
  "aggs": {
    "agg_attr_strings_full": {
      "nested": {
        "path": "attributeStrings"
      },
      "aggs": {
        "attr_name": {
          "terms": {
            "field": "attributeStrings.facetName"
          },
          "aggs": {
            "attr_value": {
              "terms": {
                "field": "attributeStrings.facetValue",
                "size": 1000,
                "order": [
                  {
                    "_term": "asc"
                  }
                ]
              }
            }
          }
        }
      }
    },
    "agg_attr_strings_filtered": {
      "filter": {
        "bool": {
          "filter": [
            {
              "nested": {
                "path": "attributeStrings",
                "query": {
                  "bool": {
                    "filter": [
                      {
                        "term": {
                          "attributeStrings.facetName": {
                            "value": "Property"
                          }
                        }
                      },
                      {
                        "terms": {
                          "attributeStrings.facetValue": [
                            "Organic"
                          ]
                        }
                      }
                    ]
                  }
                }
              }
            },
            {
              "nested": {
                "path": "attributeStrings",
                "query": {
                  "bool": {
                    "filter": [
                      {
                        "term": {
                          "attributeStrings.facetName": {
                            "value": "Brand"
                          }
                        }
                      },
                      {
                        "terms": {
                          "attributeStrings.facetValue": [
                            "Adidas"
                          ]
                        }
                      }
                    ]
                  }
                }
              }
            }
          ]
        }
      },
      "aggs": {
        "nested": {
          "path": "attributeStrings"
        },
        "aggs": {
          "attr_name": {
            "terms": {
              "field": "attributeStrings.facetName"
            },
            "aggs": {
              "attr_value": {
                "terms": {
                  "field": "attributeStrings.facetValue",
                  "size": 1000,
                  "order": [
                    {
                      "_term": "asc"
                    }
                  ]
                }
              }
            }
          }
        }
      }
    }
  }
}