Elasticsearch在URL查询和JSON POST上有不同的结果

Question

I'm completing a search function on a big online webstore.

I have a problem with additional fields. When I try searching for some fields in browser, it works, but when posting a JSON using bool filter, it gives me 0 results (doesn't raise an error).

Basically: when I visit localhost:9200/search/items/_search?pretty=true&q=field-7:Diesel It works well, however, in JSON it doesn't.

I've been googling all day and couldn't find any help in ElasticSeach documents. What frustrates me even more is that some other fields in bool query work OK, but this one doesn't.

I don't have any mapping and ES works for me out of the box - querying on the "name" field works well, as well as any other field, as well as for this field too - but only inside browser.

I realise that querying ES over browser uses so called "query string query".

Anyway, here is an example JSON that I'm posting to ElasticSearch. (searching all items that have "golf mk5" in their name, which have diesel fuel type - by searching field-7).

  {
        "query": {
            "filtered": {
                "filter": {
                    "bool": {
                        "must_not": [
                            {
                                "term": {
                                    "sold": "1"
                                }
                            },
                            {
                                "term": {
                                    "user_id": "0"
                                }
                            }
                        ],
                        "must": [
                            {
                                "term": {
                                    "locked": "0"
                                }
                            },
                            {
                                "term": {
                                    "removed": "0"
                                }
                            },
                            {
                                "terms": {
                                    "field-7": [
                                        "Diesel"
                                    ]
                                }
                            }
                        ]
                    }
                },
                "query": {
                    "match": {
                        "name": {
                            "operator": "and",
                            "query": "+golf +Mk5"
                        }
                    }
                }
            }
        },

        "sort": [
            {
                "ordering": {
                    "price": "desc"
                }
            }
        ],
        "from": 0,
        "size": 24,
        "facets": {
            "category_count": {
                "terms": {
                    "field": "category_id",
                    "size": 20,
                    "order": "count"
                }
            },
            "price": {
                "statistical": {
                    "field": "price"
                }
            }
        }
    }

Answer 1

Using a query_string-query, the text is analyzed. With the term-query (and -filter), it is not.

Since you're not specifying a mapping, you'll get the standard-analyzer for string fields. It tokenizes, lowercases and removes stopwords.

Thus, the term Diesel will be indexed as diesel. Your terms-filter is looking up the exact term Diesel, which is different.