部分单词搜索在使用 mongo-connector 的 elasticsearch (elasticsearch-py) 中不起作用

Question

Currently I've indexed my mongoDB collection into Elasticsearch running in a docker container. I am able to query a document by it's exact name, but Elasticsearch is unable to match the query if it is only part of the name. Here is an example:

>>> es = Elasticsearch('0.0.0.0:9200')
>>> es.indices.get_alias('*')
{'mongodb_meta': {'aliases': {}}, 'sigstore': {'aliases': {}}, 'my-index': {'aliases': {}}}
>>> x = es.search(index='sigstore', body={'query': {'match': {'name': 'KEGG_GLYCOLYSIS_GLUCONEOGENESIS'}}})
>>> x
{'took': 198, 'timed_out': False, '_shards': {'total': 1, 'successful': 1, 'skipped': 0, 'failed': 0}, 'hits': {'total': {'value': 1, 'relation': 'eq'}, 'max_score': 8.062855, 'hits': [{'_index': 'sigstore', '_type': 'sigs', '_id': '5d66c23228144432307c2c49', '_score': 8.062855, '_source': {'id': 1, 'name': 'KEGG_GLYCOLYSIS_GLUCONEOGENESIS', 'description': 'http://www.broadinstitute.org/gsea/msigdb/cards/KEGG_GLYCOLYSIS_GLUCONEOGENESIS', 'members': ['ACSS2', 'GCK', 'PGK2', 'PGK1', 'PDHB', 'PDHA1', 'PDHA2', 'PGM2', 'TPI1', 'ACSS1', 'FBP1', 'ADH1B', 'HK2', 'ADH1C', 'HK1', 'HK3', 'ADH4', 'PGAM2', 'ADH5', 'PGAM1', 'ADH1A', 'ALDOC', 'ALDH7A1', 'LDHAL6B', 'PKLR', 'LDHAL6A', 'ENO1', 'PKM2', 'PFKP', 'BPGM', 'PCK2', 'PCK1', 'ALDH1B1', 'ALDH2', 'ALDH3A1', 'AKR1A1', 'FBP2', 'PFKM', 'PFKL', 'LDHC', 'GAPDH', 'ENO3', 'ENO2', 'PGAM4', 'ADH7', 'ADH6', 'LDHB', 'ALDH1A3', 'ALDH3B1', 'ALDH3B2', 'ALDH9A1', 'ALDH3A2', 'GALM', 'ALDOA', 'DLD', 'DLAT', 'ALDOB', 'G6PC2', 'LDHA', 'G6PC', 'PGM1', 'GPI'], 'user': 'naji.taleb@medimmune.com', 'type': 'public', 'level1': 'test', 'level2': 'test2', 'time': '08-28-2019 14:03:29 EDT-0400', 'source': 'File', 'mapped': [''], 'notmapped': [''], 'organism': 'human'}}]}}

When using the full name of the document, elasticsearch is able to successfully query it. But this is what happens when I attempt to search part of the name or use a wildcard:

>>> x = es.search(index='sigstore', body={'query': {'match': {'name': 'KEGG'}}})
>>> x
{'took': 17, 'timed_out': False, '_shards': {'total': 1, 'successful': 1, 'skipped': 0, 'failed': 0}, 'hits': {'total': {'value': 0, 'relation': 'eq'}, 'max_score': None, 'hits': []}}



>>> x = es.search(index='sigstore', body={'query': {'match': {'name': 'KEGG*'}}})
>>> x
{'took': 3, 'timed_out': False, '_shards': {'total': 1, 'successful': 1, 'skipped': 0, 'failed': 0}, 'hits': {'total': {'value': 0, 'relation': 'eq'}, 'max_score': None, 'hits': []}}

In addition to the default index settings I also tried making an index that allows the use of the nGram tokenizer to enable me to do partial search, but that also didn't work. These are the settings I used for that index:

{
  "sigstore": {
    "aliases": {},
    "mappings": {},
    "settings": {
      "index": {
        "max_ngram_diff": "99",
        "number_of_shards": "1",
        "provided_name": "sigstore",
        "creation_date": "1579200699718",
        "analysis": {
          "filter": {
            "substring": {
              "type": "nGram",
              "min_gram": "1",
              "max_gram": "20"
            }
          },
          "analyzer": {
            "str_index_analyzer": {
              "filter": [
                "lowercase",
                "substring"
              ],
              "tokenizer": "keyword"
            },
            "str_search_analyzer": {
              "filter": [
                "lowercase"
              ],
              "tokenizer": "keyword"
            }
          }
        },
        "number_of_replicas": "1",
        "uuid": "3nf915U6T9maLdSiJozvGA",
        "version": {
          "created": "7050199"
        }
      }
    }
  }
}

and this is the corresponding python command that created it:

es.indices.create(index='sigstore',body={"mappings": {},"settings": { 'index': { "analysis": {"analyzer": {"str_search_analyzer": {"tokenizer": "keyword","filter": ["lowercase"]},"str_index_analyzer": {"tokenizer": "keyword","filter": ["lowercase", "substring"]}},"filter": {"substring": {"type": "nGram","min_gram": 1,"max_gram": 20}}}},'max_ngram_diff': '99'}})

I use mongo-connector as the pipeline between my mongoDB collection and elasticsearch. This is the command I use to start it:

mongo-connector -m mongodb://username:password@xx.xx.xxx.xx:27017/?authSource=admin -t elasticsearch:9200 -d elastic2_doc_manager -n sigstore.sigs

I'm unsure as to why my elasticsearch is unable to get a partial match, and wondering if there is some setting I'm missing or if there's some crucial mistake I've made somewhere. Thanks for reading.

Versions

MongoDB 4.0.10

elasticsearch==7.1.0

elastic2-doc-manager[elastic5]

Answer 1

Updated after checked your gist:

You need to apply the mapping to your field as written in the doc, cf the first link I share in the comment.

You need to do it after applying the settings on your index according to the gist it's line 11.

Something like:

PUT /your_index/_mapping
{
  "properties": {
    "name": {
      "type": "keyword",
      "ignore_above": 256,
      "fields": {
        "str_search_analyzer": {
          "type": "text",
          "analyzer": "str_search_analyzer"
        }
      }
    }
  }
}

After you set the mapping need to apply it to your document, using update_by_query

https://www.elastic.co/guide/en/elasticsearch/reference/master/docs-update-by-query.html

So you can continue to search with term search on your field name as it will be indexed with a keyword mapping (exact match) and on the sub_field name.str_search_analyzer with part of the word.

your_keyword = 'KEGG_GLYCOLYSIS_GLUCONEOGENESIS' OR 'KEGG*'

x = es.search(index='sigstore', body={'query': {'bool': {'should':[{'term':  {'name': your_keyword}},
{'match': {'name.str_search_analyzer': your_keyword}}
]}}
})