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opensearch_custom_plugin

README.md

OpenSearch-Plugin-example

Reference blog post - My first steps in OpenSearch Plugins

Reference Source Code

Build ans Install

Buile

Project clone and move root directory

./gradlew clean build

Check plugin artifact

build/distributions/opensearch-plugin-example-1.0.0.zip

  1. jar file
  2. LICENSE.txt
  3. NOTICE.txt
  4. plugin-descriptor.properties

Plugin Test

1) Typo correction

If you plan to correct typos when searching for a specific field, create an additional field to index the string with the letter separation. The field is of type text because it needs to be analyzed. Create an analyzer to analyze this field and apply jamo_filter to the filter. The Term Suggest API enables typo correction through this field.

//Create Index
PUT /spell_test
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0,
    "index.max_ngram_diff": 10,
    "analysis": {
      "analyzer": {
        "jamo_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "custom_jamo"
          ]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "name": {
        "type": "keyword",
        "copy_to": ["name_jamo"]
      },
      "name_jamo": {
        "type": "text",
        "analyzer": "jamo_analyzer"
      }
    }
  }
}

//Indexing
POST /_bulk
{ "index" : { "_index" : "spell_test", "_id" : "1" } }
{ "name" : "손오공" }
{ "index" : { "_index" : "spell_test", "_id" : "2" } }
{ "name" : "오픈서치" }
{ "index" : { "_index" : "spell_test", "_id" : "3" } }
{ "name" : "아메리카노" }

//Test
POST /spell_test/_search
{
  "suggest": {
    "name_suggest": {
      "text": "아메리치노",
      "term": {
        "field": "name_jamo",
        "max_edits": 2
      }
    }
  }
}
//Result
{
  "took" : 7,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 0,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  },
  "suggest" : {
    "name_suggest" : [
      {
        "text" : "ㅇㅏㅁㅔㄹㅣㅊㅣㄴㅗ",
        "offset" : 0,
        "length" : 5,
        "options" : [
          {
            "text" : "ㅇㅏㅁㅔㄹㅣㅋㅏㄴㅗ",
            "score" : 0.8,
            "freq" : 1
          }
        ]
      }
    ]
  }
}

2) Correct typos in Korean/English conversions.

Create an additional field for indexing each of the converted strings. These fields are of type text because they need to be analyzed. Create analyzers with a han/eng filter applied and specify each analyzer as the search_analyzer of the han/eng converted field.

//Create Index
PUT /haneng_test
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0,
    "index.max_ngram_diff": 10,
    "analysis": {
      "analyzer": {
        "engtohan_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "custom_engtohan"
          ]
        },
        "hantoeng_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "custom_hantoeng"
          ]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "name": {
        "type": "keyword",
        "copy_to": ["name_hantoeng", "name_engtohan"]
      },
      "name_hantoeng": {
        "type": "text",
        "search_analyzer": "hantoeng_analyzer"
      },
      "name_engtohan": {
        "type": "text",
        "search_analyzer": "engtohan_analyzer"
      }
    }
  }
}

//Indexing
POST /_bulk
{ "index" : { "_index" : "haneng_test", "_id" : "1" } }
{ "name" : "손오공" }
{ "index" : { "_index" : "haneng_test", "_id" : "2" } }
{ "name" : "Open" }
{ "index" : { "_index" : "haneng_test", "_id" : "3" } }
{ "name" : "아메리카노" }

//hantoeng Test
POST /haneng_test/_search
{
  "query": {
    "match": {
      "name_hantoeng": "ㅐㅔ두"
    }
  }
}

//engtohan Test
POST /haneng_test/_search
{
  "query": {
    "match": {
      "name_engtohan": "thsdhrhd"
    }
  }
}
//Result
{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.9808291,
    "hits" : [
      {
        "_index" : "haneng_test",
        "_type" : "_doc",
        "_id" : "2",
        "_score" : 0.9808291,
        "_source" : {
          "name" : "open"
        }
      }
    ]
  }
}

//English to Koreans conversion typo correction search test results
{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.9808291,
    "hits" : [
      {
        "_index" : "haneng_test",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.9808291,
        "_source" : {
          "name" : "손오공"
        }
      }
    ]
  }
}

3) Search for chosung

Create an analyzer with an additional field of type text to index strings with a separated initialization and a filter for initialization. You can then search for initialization via that field.

//Create Index
PUT /chosung_test
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0,
    "index.max_ngram_diff": 10,
    "analysis": {
      "analyzer": {
        "chosung_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "custom_chosung"
          ]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "name": {
        "type": "keyword",
        "copy_to": ["name_chosung"]
      },
      "name_chosung": {
        "type": "text",
        "analyzer": "chosung_analyzer"
      }
    }
  }
}

//Indexing
POST /_bulk
{ "index" : { "_index" : "chosung_test", "_id" : "2" } }
{ "name" : "오픈서치" }
{ "index" : { "_index" : "chosung_test", "_id" : "3" } }
{ "name" : "아메리카노" }

//Test
POST /chosung_test/_search
{
  "query": {
    "match": {
      "name_chosung": "ㅇㅍㅅㅊ"
    }
  }
}
//Result
{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.6931471,
    "hits" : [
      {
        "_index" : "chosung_test",
        "_type" : "_doc",
        "_id" : "2",
        "_score" : 0.6931471,
        "_source" : {
          "name" : "오픈서치"
        }
      }
    ]
  }
}

4) Autocomplete

Create an additional field of type text for autocomplete. The index analyzer uses an ngram tokenizer to ensure that substrings are indexed together. The search analyzer only applies jamo_filter. The additional fields created for further analysis will allow searching via partial matching, which will allow the service to implement autocomplete functionality.

//Create Index
PUT /ac_test
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0,
    "index.max_ngram_diff": 30,
    "analysis": {
      "filter": {
        "ngram_filter": {
          "type": "ngram",
          "min_gram": 1,
          "max_gram": 20
        }
      },
      "analyzer": {
        "jamo_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "custom_jamo"
          ]
        },
        "ngram_jamo_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "custom_jamo",
            "ngram_filter"
          ]
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "name": {
        "type": "keyword",
        "copy_to": "name_ngram"
      },
      "name_ngram": {
        "type": "text",
        "analyzer": "ngram_jamo_analyzer",
        "search_analyzer": "jamo_analyzer"
      }
    }
  }
}

//Indexing
POST /_bulk
{ "index" : { "_index" : "ac_test", "_id" : "1" } }
{ "name" : "손오공" }
{ "index" : { "_index" : "ac_test", "_id" : "2" } }
{ "name" : "open" }
{ "index" : { "_index" : "ac_test", "_id" : "3" } }
{ "name" : "아메리카노" }

//Autocomplete Test
POST /ac_test/_search
{
  "query": {
    "match": {
      "name_ngram": "아멜"
    }
  }
}
//Result
{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.631392,
    "hits" : [
      {
        "_index" : "ac_test",
        "_type" : "_doc",
        "_id" : "3",
        "_score" : 1.631392,
        "_source" : {
          "name" : "아메리카노"
        }
      }
    ]
  }
}