Painlessスクリプト利用時の想定外の挙動


(Junkoshimane) #1

"painlessスクリプト"を利用した場合、想定外の挙動が見られました。
恐れ入りますが、不具合か否かご確認願えますでしょうか。

※同内容の投稿を英語でさせて頂きましたが、データに日本語が含まれますので、サンプルデータも含め、こちらで再投稿させて頂いております。
https://discuss.elastic.co/t/nested-data-not-shown-correctly-with-painless-script/157012

以下に挙動発見時の詳細を示します。


  • Elasticバージョン: 6.3.1
  • マッピング
{
  "mappings": {
    "_doc": {
      "properties": {
        "study_id": {
          "type": "keyword"
        },
        "ext_number":{
          "type": "keyword"
        },
        "study_timestamp":{
          "type": "date"
        },
        "study_secondslong":{
          "type": "float"
        },
        "student_learn_rate":{
          "type": "float"
        },
        "additional_study_timestamp":{
          "type": "date"
        },
        "additional_data01":{
          "type": "keyword"
        },
        "additional_data02":{
          "type": "keyword"
        },
        "study_text":{
          "type": "text",
          "analyzer" : "kuromoji"
        },
        "study_text_student":{
          "type": "text",
          "analyzer" : "kuromoji"
        },
        "study_text_teacher":{
          "type": "text",
          "analyzer" : "kuromoji"
        },
        "file_uri":{
          "type": "keyword"
        },
        "book_del_flg":{
          "type": "keyword"
        },
        "teach_cm":{
          "type": "double"
        },
        "student_cm":{
          "type": "double"
        },
        "claim_old":{
          "type": "integer"
        },
        "negative_task":{
          "type": "text"
        },
        "negative_score":{
          "type": "float"
        },
        "teacher":{
          "type": "keyword"
        },
        "teacher_flg":{
          "type": "keyword"
        },
        "claim":{
          "type": "integer"
        },
        "talker_data":{
          "type": "nested",
          "properties":{
            "talker_id":{
              "type": "keyword"
            },
            "version_number":{
              "type": "float"
            },
            "dict_name":{
              "type": "keyword"
            },
            "c_time":{
              "type": "float"
            },
            "u_time":{
              "type": "float"
            },
            "m_time1":{
              "type": "float"
            },
            "m_time2":{
              "type": "float"
            },
            "m_time3":{
              "type": "float"
            },
            "m_time4":{
              "type": "float"
            },
            "tf_done_flg":{
              "type": "keyword"
            },
           "cluster_done_flg":{
              "type": "keyword"
            },
            "evalexp_done_flg":{
              "type": "keyword"
            },
            "get_words_data":{
              "type": "nested",
              "properties":{
                "study_id": {
                  "type": "keyword"
                },
                "turn":{
                  "type": "integer"
                },
                "learn_begin_timeoffset":{
                  "type": "float"
                },
                "learn_end_timeoffset":{
                  "type": "float"
                },
                "learn_confidence":{
                  "type": "keyword"
                },
                "words_confidence":{
                  "type": "text"
                },
                "get_words":{
                  "type": "text",
                  "fielddata": true
                },
                "present_rate":{
                  "type": "float"
                },
                "silent_time":{
                  "type": "float"
                },
                "learn_position":{
                  "type": "integer"
                },
                "study_reason_flg":{
                  "type": "keyword"
                },
                "calib_words_confidence":{
                  "type": "text"
                }
              }
            }
          }
        }
      }
    }
  }
}

  • 発生事象
    検索結果の親データと子データの組み合わせが壊れることがあります。
### 正しい親子関係 ###
{
  "took" : 57,
  "timed_out" : false,
  "_shards" : {
    :
  },
  "hits" : {
    "total" : 3,
    "max_score" : 5.364271,
    "hits" : [
      {
        "_index" : "school",
        "_type" : "_doc",
        "_id" : "20171106_194842_1111",  ##### <===== 親データ
        "_score" : 5.364271,
        "fields" : {
          "test" : [
            {
              :
              "talker_data" : [
                {
                  :
                  "get_words_data" : [
                    {
                      :
                      "study_id" : "20171106_194842_1111", ##### <===== 子データ
                    },
                    :
                  ]
                }
              ],
            }
          ]
        }
      },

######################################################

### 誤った親子関係 ###
      {
        "_index" : "school",
        "_type" : "_doc",
        "_id" : "20171106_194842_2222",  ##### <===== 親データ
        "_score" : 4.3486114,
        "fields" : {
          "test" : [
            {
              :
              "talker_data" : [
                {
                  :
                  "get_words_data" : [
                    {
                      :
                      "study_id" : "20171106_194842_3333", ##### <===== 誤った子データ
                      :
                    },
                    :
                  ]
                }
              ],
            }
          ]
        }
      },
      :

  • match_allクエリのみの場合、検索結果は正確に表示されます。
GET school/_search
{
  "query": {
    "match_all": {}
  }
}

### ↓↓↓↓↓ ###

{
  :
  "hits" : {
    "total" : 6,
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "school",
        "_type" : "_doc",
        "_id" : "20171106_194842_1111",
        "_score" : 1.0,
        "_source" : {
          :
          "talker_data" : [
            {
              :
              "get_words_data" : [
                {
                  "study_id" : "20171106_194842_1111",
                  :
                },
              ],
            }
          ]
        }
      },
      {
        "_index" : "school",
        "_type" : "_doc",
        "_id" : "20171106_194842_2222",
        "_score" : 1.0,
        "_source" : {
          :
          "talker_data" : [
            {
              :
              "get_words_data" : [
                {
                  "study_id" : "20171106_194842_2222",
                  :
                },
              ],
            }
          ]
        }
      },
      :


(Junkoshimane) #2
  • "painlessスクリプト"にて、即"params._source"をリターンした場合、検索結果は正確に表示されず、親子関係が崩れる場合があります。
GET school/_search
{
  "query": {
    "match_all": {}
  },
  "script_fields": {
    "test": {
      "script": {
        "lang": "painless",
        "source": "
          return params._source;
        "
      }
    }
  }
}

### ↓↓↓↓↓ ###

{
  :
  "hits" : {
    "total" : 6,
    "max_score" : 1.0,
    "hits" : [
      {
    "total" : 6,
    "max_score" : 1.0,
    "hits" : [
      :
      {
        "_id" : "20171106_194842_2222",
        "_score" : 1.0,
        "fields" : {
          "test" : [
            {
              :
              "talker_data" : [
                {
                  :
                  "get_words_data" : [
                    {
                      :
                      "study_id" : "20171106_194842_5555", ### 親子関係崩れる
                      :
                    },
                    :
                  }
                },
              ],
            }
          ]
        }
      },


(Junkoshimane) #3
  • "painlessスクリプト"にて、即"params._source.talker_data"をリターンした場合、検索結果は正確に表示されます。
{
  "query": {
    "match_all": {}
  },
  "script_fields": {
    "test": {
      "script": {
        "lang": "painless",
        "source": "
          return params._source.talker_data;
        "
      }
    }
  }
}

### ↓↓↓↓↓ ###

{
  "took" : 7,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 6,
    "max_score" : 1.0,
    "hits" : [
      :
      {
        "_index" : "school",
        "_type" : "_doc",
        "_id" : "20171106_194842_2222",
        "_score" : 1.0,
        "fields" : {
          "test" : [
            {
              :
              "get_words_data" : [
                {
                  :
                  "study_id" : "20171106_194842_2222",
                 :
                },
              ],
            }
          ]
        }
      },
      :

(Junkoshimane) #4
  • ドキュメント 1
{"study_id":"20171106_194842_1111","ext_number":"1111","study_timestamp":"2017-11-06T19:48:42","study_secondslong":59.68,"student_learn_rate":59,"additional_study_timestamp":null,"additional_data01":null,"additional_data02":null,"study_text":"■。お電話ありがとうございます。新宿大学、鈴木でございます。□。鈴木さん、いつもお世話になっています。佐藤です。加入している部活について確認があるのですが。■。では、担当の田中に変わります。お待ちくださいませ。□。はい、手元に会員を用意しておきます。■。もしもしお電話代わりました。田中です。□。田中さん、会員番号は12345なのですが、部費内容をご確認頂けますか。■。会員番号を確認しますので、少々お待ちください。","study_text_student":"鈴木さん、いつもお世話になっています。佐藤です。加入している部活について確認があるのですが。はい、手元に会員を用意しておきます。田中さん、会員番号は12345なのですが、部費内容をご確認頂けますか。","study_text_teacher":"お電話ありがとうございます。新宿大学、鈴木でございます。では、担当の田中に変わります。お待ちくださいませ。もしもしお電話代わりました。田中です。会員番号を確認しますので、少々お待ちください。","file_uri":"dtp://192.168.201.31:61003/201711/06/3001/20171106_194842_1111.xml.crp","book_del_flg":"0","student_cm":-1135.919149395,"teach_cm":-1997.510647446,"claim_old":null,"negative_task":null,"negative_score":0.0,"teacher":null,"teacher_flg":"0","claim":0,"talker_data":[{"talker_id":"0","version_number":2,"dict_name":"NX2014.punc.cls.L_20141023_170000.wng","c_time":58.54,"u_time":25.82,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_1111","turn":6,"learn_begin_timeoffset":57.41,"learn_end_timeoffset":58.01,"learn_confidence":"90","words_confidence":" 71","get_words":"53106 105655","present_rate":0.0,"silent_time":0.0,"learn_position":10,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":2,"learn_begin_timeoffset":14.5,"learn_end_timeoffset":21.24,"learn_confidence":"90","words_confidence":" 96 100 57 100 49 90 96 99 100 99 94 90 99 96 100 100 82 94 81 50 53 80 100 63","get_words":"21062 133 102 760 5722 315 27 50 14 53116 321 105654 212 105654 222 5 45016 483 273 102 401 53 716 903 2094 53124 564 105654 14","present_rate":439.39,"silent_time":0.59,"learn_position":3,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":2,"learn_begin_timeoffset":6.03,"learn_end_timeoffset":13.91,"learn_confidence":"89","words_confidence":" 79 99 100 100 75 98 100 94 93 98 86 97 97 50 66 90 99 63 70","get_words":"11993 105654 1634 105654 11993 105654 569 105655 752 91 507 53102 105654 75119 105654 44635 0 105654 752","present_rate":407.41,"silent_time":0.23,"learn_position":2,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":4,"learn_begin_timeoffset":40.69,"learn_end_timeoffset":51.29,"learn_confidence":"89","words_confidence":" 73 99 33 51 83 10 77 90 86 98 89 97 100 100 100 98 96 100 100 100 72 63 100 82 100 83 54 99 100 98 73","get_words":"11993 105654 91 5630 105654 5 0 53246 2 53102 105654 3001 1437 2 180 118 53136 26 37 11 1992 4114 4 14 53108 53125 105654 202 53130 10 11 14 53108 53125 105654 53106 105655","present_rate":379.75,"silent_time":0.0,"learn_position":6,"study_reason_flg":"1","calib_words_confidence":""}]},{"talker_id":"1","version_number":2,"dict_name":"NX2014.punc.cls.R_20141023_170000.wng","c_time":59.68,"u_time":38.19,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_1111","turn":1,"learn_begin_timeoffset":0.29,"learn_end_timeoffset":5.8,"learn_confidence":"99","words_confidence":" 100 100 100 89 100 100 100 100 100 100 100 100 100 100","get_words":"99 121 46929 105655 53120 133 307 1115 535 105654 9951 7760 40311 1685 315 7 105655","present_rate":537.74,"silent_time":0.0,"learn_position":1,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":5,"learn_begin_timeoffset":49.6,"learn_end_timeoffset":59.18,"learn_confidence":"91","words_confidence":" 63 58 81 56 54 79 66 97 97 84 100 100 100 100 100 100 100 100 99 99 99 40 42 99 100 100","get_words":"1992 4114 105654 412 12 53102 53122 53231 26 53105 8870 1639 40311 13940 10298 1639 4 37 11 14 53108 53118 105654 412 163 439 44 7 564 105655","present_rate":439.02,"silent_time":0.0,"learn_position":9,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":5,"learn_begin_timeoffset":47.9,"learn_end_timeoffset":48.5,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":8,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":5,"learn_begin_timeoffset":43.97,"learn_end_timeoffset":44.61,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":7,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":3,"learn_begin_timeoffset":19.84,"learn_end_timeoffset":41.06,"learn_confidence":"93","words_confidence":" 71 96 43 96 91 99 100 55 100 100 100 100 100 100 100 100 100 100 100 100 99 100 100 100 100 100 100 100 100 81 100 99 80 80 98 100 63 94 94 100 100 100 98 56 91 98 97 55 23 97 97 100 100 89 80 88","get_words":"11993 105654 53117 53102 1969 52 53116 1013 105654 1926 0 11447 0 38260 472 2854 1639 105654 27435 105654 18414 105654 38801 105654 15194 105654 6579 40311 637 315 225 39 7 53107 105654 752 4778 0 4022 105654 12 105654 21062 34112 924 5 752 158 53145 7 105655 412 91 263 52 1019 26 1113 39 7 6239 105655","present_rate":582.47,"silent_time":0.0,"learn_position":5,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_1111","turn":3,"learn_begin_timeoffset":16.1,"learn_end_timeoffset":16.74,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":4,"study_reason_flg":"1","calib_words_confidence":""}]}]}

(Junkoshimane) #5
  • ドキュメント 2
{"study_id":"20171106_194842_2222","ext_number":"1111","study_timestamp":"2017-11-06T19:48:42","study_secondslong":59.68,"student_learn_rate":59,"additional_study_timestamp":null,"additional_data01":null,"additional_data02":null,"study_text":"■。お電話ありがとうございます。新宿大学の渡辺です。□。もしもし鈴木と申します。田中さんいらっしゃいますか。■。お待ちくださいませ。■。お電話代わりました田中です。■。いつも鈴木さんにはお世話になっております。□。部活内容について確認があるのですが。会員番号は田中さん、もしもし田中さん。■。鈴木様、お電話少々遠いようですね。□。会員番号は、12345です。■。鈴木様、下のお名前も頂け頂けますか。□。鈴木太郎です。■。復唱します。鈴木太郎様、会員番号12345ですね。","study_text_student":"もしもし鈴木と申します。田中さんいらっしゃいますか。部活内容について確認があるのですが。会員番号は田中さん、もしもし田中さん。会員番号は、12345です。鈴木太郎です。","study_text_teacher":"お電話ありがとうございます。新宿大学の渡辺です。お待ちくださいませ。お電話代わりました田中です。いつも鈴木さんにはお世話になっております。鈴木様、お電話少々遠いようですね。鈴木様、下のお名前も頂け頂けますか。復唱します。鈴木太郎様、会員番号12345ですね。","file_uri":"dtp://192.168.201.31:61003/201711/06/3001/20171106_194842_2222.xml.crp","book_del_flg":"0","student_cm":-1135.919149395,"teach_cm":-1997.510647446,"claim_old":null,"negative_task":null,"negative_score":0.0,"teacher":null,"teacher_flg":"0","claim":0,"talker_data":[{"talker_id":"0","version_number":2,"dict_name":"NX2014.punc.cls.L_20141023_170000.wng","c_time":58.54,"u_time":25.82,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_2222","turn":6,"learn_begin_timeoffset":57.41,"learn_end_timeoffset":58.01,"learn_confidence":"90","words_confidence":" 71","get_words":"53106 105655","present_rate":0.0,"silent_time":0.0,"learn_position":10,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":2,"learn_begin_timeoffset":14.5,"learn_end_timeoffset":21.24,"learn_confidence":"90","words_confidence":" 96 100 57 100 49 90 96 99 100 99 94 90 99 96 100 100 82 94 81 50 53 80 100 63","get_words":"21062 133 102 760 5722 315 27 50 14 53116 321 105654 212 105654 222 5 45016 483 273 102 401 53 716 903 2094 53124 564 105654 14","present_rate":439.39,"silent_time":0.59,"learn_position":3,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":2,"learn_begin_timeoffset":6.03,"learn_end_timeoffset":13.91,"learn_confidence":"89","words_confidence":" 79 99 100 100 75 98 100 94 93 98 86 97 97 50 66 90 99 63 70","get_words":"11993 105654 1634 105654 11993 105654 569 105655 752 91 507 53102 105654 75119 105654 44635 0 105654 752","present_rate":407.41,"silent_time":0.23,"learn_position":2,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":4,"learn_begin_timeoffset":40.69,"learn_end_timeoffset":51.29,"learn_confidence":"89","words_confidence":" 73 99 33 51 83 10 77 90 86 98 89 97 100 100 100 98 96 100 100 100 72 63 100 82 100 83 54 99 100 98 73","get_words":"11993 105654 91 5630 105654 5 0 53246 2 53102 105654 3001 1437 2 180 118 53136 26 37 11 1992 4114 4 14 53108 53125 105654 202 53130 10 11 14 53108 53125 105654 53106 105655","present_rate":379.75,"silent_time":0.0,"learn_position":6,"study_reason_flg":"1","calib_words_confidence":""}]},{"talker_id":"1","version_number":2,"dict_name":"NX2014.punc.cls.R_20141023_170000.wng","c_time":59.68,"u_time":38.19,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_2222","turn":1,"learn_begin_timeoffset":0.29,"learn_end_timeoffset":5.8,"learn_confidence":"99","words_confidence":" 100 100 100 89 100 100 100 100 100 100 100 100 100 100","get_words":"99 121 46929 105655 53120 133 307 1115 535 105654 9951 7760 40311 1685 315 7 105655","present_rate":537.74,"silent_time":0.0,"learn_position":1,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":5,"learn_begin_timeoffset":49.6,"learn_end_timeoffset":59.18,"learn_confidence":"91","words_confidence":" 63 58 81 56 54 79 66 97 97 84 100 100 100 100 100 100 100 100 99 99 99 40 42 99 100 100","get_words":"1992 4114 105654 412 12 53102 53122 53231 26 53105 8870 1639 40311 13940 10298 1639 4 37 11 14 53108 53118 105654 412 163 439 44 7 564 105655","present_rate":439.02,"silent_time":0.0,"learn_position":9,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":5,"learn_begin_timeoffset":47.9,"learn_end_timeoffset":48.5,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":8,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":5,"learn_begin_timeoffset":43.97,"learn_end_timeoffset":44.61,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":7,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":3,"learn_begin_timeoffset":19.84,"learn_end_timeoffset":41.06,"learn_confidence":"93","words_confidence":" 71 96 43 96 91 99 100 55 100 100 100 100 100 100 100 100 100 100 100 100 99 100 100 100 100 100 100 100 100 81 100 99 80 80 98 100 63 94 94 100 100 100 98 56 91 98 97 55 23 97 97 100 100 89 80 88","get_words":"11993 105654 53117 53102 1969 52 53116 1013 105654 1926 0 11447 0 38260 472 2854 1639 105654 27435 105654 18414 105654 38801 105654 15194 105654 6579 40311 637 315 225 39 7 53107 105654 752 4778 0 4022 105654 12 105654 21062 34112 924 5 752 158 53145 7 105655 412 91 263 52 1019 26 1113 39 7 6239 105655","present_rate":582.47,"silent_time":0.0,"learn_position":5,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_2222","turn":3,"learn_begin_timeoffset":16.1,"learn_end_timeoffset":16.74,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":4,"study_reason_flg":"1","calib_words_confidence":""}]}]}

(Junkoshimane) #6
  • ドキュメント 3
{"study_id":"20171106_194842_3333","ext_number":"1111","study_timestamp":"2017-11-06T19:48:42","study_secondslong":59.68,"student_learn_rate":59,"additional_study_timestamp":null,"additional_data01":null,"additional_data02":null,"study_text":"□。もしもし鈴木と申します。■。鈴木様、いつもお世話になっております。■。私、新宿大学、スクールメンバ、田中が承ります。□。怪我で休部することになって、部活金請求について伺いたいのですが。□。それで申し訳ないのですが、会員をなくしてしまったのです。■。では、担当の者に代わりますので、このままお待ち頂けますか。■。お電話代わりました、佐藤と申します。■。会員をなくされたのですね。先ほど電話で応対させて頂いた田中から、書類をお送りさせて頂きますので、ご記入の上、ご返送願えますか。□。不明点がありましたら、田中さんにお聞きするということでよろしいですか。■。はいそのように、よろしくお願い致します。","study_text_student":"もしもし鈴木と申します。怪我で休部することになって、部活金請求について伺いたいのですが。それで申し訳ないのですが、会員をなくしてしまったのです。させて頂きますので、ご記入の上、ご返送願えますか。不明点がありましたら、田中さんにお聞きするということでよろしいですか。","study_text_teacher":"鈴木様、いつもお世話になっております。私、新宿大学、スクールメンバ、田中が承ります。では、担当の者に代わりますので、このままお待ち頂けますか。お電話代わりました、佐藤と申します。会員をなくされたのですね。先ほど電話で応対させて頂いた田中から、書類をお送りさせて頂きますので、ご記入の上、ご返送願えますか。はいそのように、よろしくお願い致します。","file_uri":"dtp://192.168.201.31:61003/201711/06/3001/20171106_194842_3333.xml.crp","book_del_flg":"0","student_cm":-1135.919149395,"teach_cm":-1997.510647446,"claim_old":null,"negative_task":null,"negative_score":0.0,"teacher":null,"teacher_flg":"0","claim":0,"talker_data":[{"talker_id":"0","version_number":2,"dict_name":"NX2014.punc.cls.L_20141023_170000.wng","c_time":58.54,"u_time":25.82,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_3333","turn":6,"learn_begin_timeoffset":57.41,"learn_end_timeoffset":58.01,"learn_confidence":"90","words_confidence":" 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105655","present_rate":379.75,"silent_time":0.0,"learn_position":6,"study_reason_flg":"1","calib_words_confidence":""}]},{"talker_id":"1","version_number":2,"dict_name":"NX2014.punc.cls.R_20141023_170000.wng","c_time":59.68,"u_time":38.19,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_3333","turn":1,"learn_begin_timeoffset":0.29,"learn_end_timeoffset":5.8,"learn_confidence":"99","words_confidence":" 100 100 100 89 100 100 100 100 100 100 100 100 100 100","get_words":"99 121 46929 105655 53120 133 307 1115 535 105654 9951 7760 40311 1685 315 7 105655","present_rate":537.74,"silent_time":0.0,"learn_position":1,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_3333","turn":5,"learn_begin_timeoffset":49.6,"learn_end_timeoffset":59.18,"learn_confidence":"91","words_confidence":" 63 58 81 56 54 79 66 97 97 84 100 100 100 100 100 100 100 100 99 99 99 40 42 99 100 100","get_words":"1992 4114 105654 412 12 53102 53122 53231 26 53105 8870 1639 40311 13940 10298 1639 4 37 11 14 53108 53118 105654 412 163 439 44 7 564 105655","present_rate":439.02,"silent_time":0.0,"learn_position":9,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_3333","turn":5,"learn_begin_timeoffset":47.9,"learn_end_timeoffset":48.5,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":8,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_3333","turn":5,"learn_begin_timeoffset":43.97,"learn_end_timeoffset":44.61,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":7,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_3333","turn":3,"learn_begin_timeoffset":19.84,"learn_end_timeoffset":41.06,"learn_confidence":"93","words_confidence":" 71 96 43 96 91 99 100 55 100 100 100 100 100 100 100 100 100 100 100 100 99 100 100 100 100 100 100 100 100 81 100 99 80 80 98 100 63 94 94 100 100 100 98 56 91 98 97 55 23 97 97 100 100 89 80 88","get_words":"11993 105654 53117 53102 1969 52 53116 1013 105654 1926 0 11447 0 38260 472 2854 1639 105654 27435 105654 18414 105654 38801 105654 15194 105654 6579 40311 637 315 225 39 7 53107 105654 752 4778 0 4022 105654 12 105654 21062 34112 924 5 752 158 53145 7 105655 412 91 263 52 1019 26 1113 39 7 6239 105655","present_rate":582.47,"silent_time":0.0,"learn_position":5,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_3333","turn":3,"learn_begin_timeoffset":16.1,"learn_end_timeoffset":16.74,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":4,"study_reason_flg":"1","calib_words_confidence":""}]}]}


(Junkoshimane) #7
  • ドキュメント 4
{"study_id":"20171106_194842_4444","ext_number":"1111","study_timestamp":"2017-11-06T19:48:42","study_secondslong":59.68,"student_learn_rate":59,"additional_study_timestamp":null,"additional_data01":null,"additional_data02":null,"study_text":"■。新宿大学、金沢でございます。□。部活の退部ために連絡をしたんですけども。□。退部の為の、書類をお送り願えますか。■。部費内容を確認しますので、お待ちください。■。失礼ですが、退部の理由を教えて頂けますか。□。他の部活団体で、部活料の安いものがあるので切り替えます。■。さようでございますか。■。それでは書類をお送りさせて頂きますので、必要事項を記載、捺印の上、返送願えますか。□。分かりました。印鑑は、シャチハタでも可能ですか。■。申し訳ありません。印鑑は、シャチハタ以外でお願い致します。","study_text_student":"部活の退部ために連絡をしたんですけども。退部の為の、書類をお送り願えますか。他の部活団体で、部活料の安いものがあるので切り替えます。分かりました。印鑑は、シャチハタでも可能ですか。","study_text_teacher":"新宿大学、金沢でございます。部費内容を確認しますので、お待ちください。失礼ですが、退部の理由を教えて頂けますか。さようでございますか。それでは書類をお送りさせて頂きますので、必要事項を記載、捺印の上、返送願えますか。申し訳ありません。印鑑は、シャチハタ以外でお願い致します。","file_uri":"dtp://192.168.201.31:61003/201711/06/3001/20171106_194842_4444.xml.crp","book_del_flg":"0","student_cm":-1135.919149395,"teach_cm":-1997.510647446,"claim_old":null,"negative_task":null,"negative_score":0.0,"teacher":null,"teacher_flg":"0","claim":0,"talker_data":[{"talker_id":"0","version_number":2,"dict_name":"NX2014.punc.cls.L_20141023_170000.wng","c_time":58.54,"u_time":25.82,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_4444","turn":6,"learn_begin_timeoffset":57.41,"learn_end_timeoffset":58.01,"learn_confidence":"90","words_confidence":" 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105655","present_rate":379.75,"silent_time":0.0,"learn_position":6,"study_reason_flg":"1","calib_words_confidence":""}]},{"talker_id":"1","version_number":2,"dict_name":"NX2014.punc.cls.R_20141023_170000.wng","c_time":59.68,"u_time":38.19,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_4444","turn":1,"learn_begin_timeoffset":0.29,"learn_end_timeoffset":5.8,"learn_confidence":"99","words_confidence":" 100 100 100 89 100 100 100 100 100 100 100 100 100 100","get_words":"99 121 46929 105655 53120 133 307 1115 535 105654 9951 7760 40311 1685 315 7 105655","present_rate":537.74,"silent_time":0.0,"learn_position":1,"study_reason_flg":"0","calib_words_confidence":""},{"study_id":"20171106_194842_4444","turn":5,"learn_begin_timeoffset":49.6,"learn_end_timeoffset":59.18,"learn_confidence":"91","words_confidence":" 63 58 81 56 54 79 66 97 97 84 100 100 100 100 100 100 100 100 99 99 99 40 42 99 100 100","get_words":"1992 4114 105654 412 12 53102 53122 53231 26 53105 8870 1639 40311 13940 10298 1639 4 37 11 14 53108 53118 105654 412 163 439 44 7 564 105655","present_rate":439.02,"silent_time":0.0,"learn_position":9,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_4444","turn":5,"learn_begin_timeoffset":47.9,"learn_end_timeoffset":48.5,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":8,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_4444","turn":5,"learn_begin_timeoffset":43.97,"learn_end_timeoffset":44.61,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":7,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_4444","turn":3,"learn_begin_timeoffset":19.84,"learn_end_timeoffset":41.06,"learn_confidence":"93","words_confidence":" 71 96 43 96 91 99 100 55 100 100 100 100 100 100 100 100 100 100 100 100 99 100 100 100 100 100 100 100 100 81 100 99 80 80 98 100 63 94 94 100 100 100 98 56 91 98 97 55 23 97 97 100 100 89 80 88","get_words":"11993 105654 53117 53102 1969 52 53116 1013 105654 1926 0 11447 0 38260 472 2854 1639 105654 27435 105654 18414 105654 38801 105654 15194 105654 6579 40311 637 315 225 39 7 53107 105654 752 4778 0 4022 105654 12 105654 21062 34112 924 5 752 158 53145 7 105655 412 91 263 52 1019 26 1113 39 7 6239 105655","present_rate":582.47,"silent_time":0.0,"learn_position":5,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_4444","turn":3,"learn_begin_timeoffset":16.1,"learn_end_timeoffset":16.74,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":4,"study_reason_flg":"1","calib_words_confidence":""}]}]}


(Junkoshimane) #8
  • ドキュメント 5
{"study_id":"20171106_194842_5555","ext_number":"1111","study_timestamp":"2017-11-06T19:48:42","study_secondslong":59.68,"student_learn_rate":59,"additional_study_timestamp":null,"additional_data01":null,"additional_data02":null,"study_text":"■。新宿大学、退部担当の金沢でございます。□。先日お送り頂いた書類のことでお聞きしたいことがあるのですけれども。■。部費内容を確認しますので、お待ちください。■。お待たせしました。書類のどの箇所になりますか。□。退部理由の欄で、書き損じてしまいました。どうしたらよいでしょうか。■。書類の訂正は、二重線を引き、捺印して下さい。□。分かりました。印鑑は三文判でも可能ですか。■。はい、印鑑は、三文判でも、シャチハタでもかまいません。","study_text_student":"先日お送り頂いた書類のことでお聞きしたいことがあるのですけれども。退部理由の欄で、書き損じてしまいました。どうしたらよいでしょうか。分かりました。印鑑は三文判でも可能ですか。","study_text_teacher":"新宿大学、退部担当の金沢でございます。部費内容を確認しますので、お待ちください。お待たせしました。書類のどの箇所になりますか。書類の訂正は、二重線を引き、捺印して下さい。はい、印鑑は、三文判でも、シャチハタでもかまいません。","file_uri":"dtp://192.168.201.31:61003/201711/06/3001/20171106_194842_5555.xml.crp","book_del_flg":"0","student_cm":-1135.919149395,"teach_cm":-1997.510647446,"claim_old":null,"negative_task":null,"negative_score":0.0,"teacher":null,"teacher_flg":"0","claim":0,"talker_data":[{"talker_id":"0","version_number":2,"dict_name":"NX2014.punc.cls.L_20141023_170000.wng","c_time":58.54,"u_time":25.82,"m_time1":1.88,"m_time2":3.09,"m_time3":0.6,"m_time4":0.37,"tf_done_flg":"1","cluster_done_flg":"0","evalexp_done_flg":"0","get_words_data":[{"study_id":"20171106_194842_5555","turn":6,"learn_begin_timeoffset":57.41,"learn_end_timeoffset":58.01,"learn_confidence":"90","words_confidence":" 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99 99 99 40 42 99 100 100","get_words":"1992 4114 105654 412 12 53102 53122 53231 26 53105 8870 1639 40311 13940 10298 1639 4 37 11 14 53108 53118 105654 412 163 439 44 7 564 105655","present_rate":439.02,"silent_time":0.0,"learn_position":9,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_5555","turn":5,"learn_begin_timeoffset":47.9,"learn_end_timeoffset":48.5,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":8,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_5555","turn":5,"learn_begin_timeoffset":43.97,"learn_end_timeoffset":44.61,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":7,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_5555","turn":3,"learn_begin_timeoffset":19.84,"learn_end_timeoffset":41.06,"learn_confidence":"93","words_confidence":" 71 96 43 96 91 99 100 55 100 100 100 100 100 100 100 100 100 100 100 100 99 100 100 100 100 100 100 100 100 81 100 99 80 80 98 100 63 94 94 100 100 100 98 56 91 98 97 55 23 97 97 100 100 89 80 88","get_words":"11993 105654 53117 53102 1969 52 53116 1013 105654 1926 0 11447 0 38260 472 2854 1639 105654 27435 105654 18414 105654 38801 105654 15194 105654 6579 40311 637 315 225 39 7 53107 105654 752 4778 0 4022 105654 12 105654 21062 34112 924 5 752 158 53145 7 105655 412 91 263 52 1019 26 1113 39 7 6239 105655","present_rate":582.47,"silent_time":0.0,"learn_position":5,"study_reason_flg":"1","calib_words_confidence":""},{"study_id":"20171106_194842_5555","turn":3,"learn_begin_timeoffset":16.1,"learn_end_timeoffset":16.74,"learn_confidence":"100","words_confidence":" 100","get_words":"49 105655","present_rate":0.0,"silent_time":0.0,"learn_position":4,"study_reason_flg":"1","calib_words_confidence":""}]}]}

(Junkoshimane) #9
  • ドキュメント 6
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(Junkoshimane) #10

どなたか、コメントなどありましたら、投稿頂けるとありがたいです。
どうぞよろしくお願い致します。


(Makoto Nozawa) #11

手元の環境で試し、再現することは確認しました。
以下、推測を多分に含みすみませんが参考や議論の足しになればと。

nested datatypeではnestされた部分のデータ、今回で言えばtalker_dataの個々の要素は内部的には個別のdocumentとして格納されます

*今回の6つのデータをindexした後に_cat/indicesなどでdocument数を確認するとずっと多い数字が返されるはずです

元のdocumentとそれに紐づくnested documentは同一のshardに格納され、検索や集計(aggregation)を行うときはそれぞれ専用のものを使うことになります(nested query / nested aggregation)
そうして特別に用意された方法を使わなければ内部的に独立したdocument間の関連性をうまく扱えないのだと理解しています。

referenceやインターネット上の情報を確認した限りでは、painlessには今の所nested datatypeを扱うための「専用の機能」が見当たりません。なのでpainlessではnested datatypeの関係性をうまく扱えないのではないか、というのが私の推測です。
(不具合というよりはそもそも機能自体が存在していないように思います)


(Junkoshimane) #12

mnozawa様

事象の再現、およびコメントありがとうございます。

referenceやインターネット上の情報を確認した限りでは、painlessには今の所nested datatypeを扱うための「専用の機能」が見当たりません。なのでpainlessではnested datatypeの関係性をうまく扱えないのではないか、というのが私の推測です。
(不具合というよりはそもそも機能自体が存在していないように思います)

私のほうでも、専用機能(があるか否か)について確認させて頂きます。


(Junkoshimane) #13
  • 参考

(system) #14

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