ElasticSearch mapping the result of collapse / do operations on a grouped documents

Question

There is a list of conversations and every conversation has a list of messages. Every message has different fields and an action field. We need to consider that

Answer 1

I solved it using the scripted_metric of elastic. Also, the index was changed from the initial state.

The script:

{
   "size": 0,
   "aggs": {
        "intentPathsCountAgg": {
            "scripted_metric": {
                "init_script": "state.messagesList = new ArrayList();",
                "map_script": "long currentMessageTime = doc['messageReceivedEvent.context.timestamp'].value.millis; Map currentMessage = ['conversationId': doc['messageReceivedEvent.context.conversationId.keyword'], 'time': currentMessageTime, 'intentsPath': doc['brainQueryRequestEvent.brainQueryRequest.user_data.intentsHistoryPath.keyword'].value]; state.messagesList.add(currentMessage);",  
                "combine_script": "return state",
                "reduce_script": "List messages = new ArrayList(); Map conversationsMap = new HashMap(); Map intentsMap = new HashMap(); String[] ifElseWorkaround = new String[1]; for (state in states) { messages.addAll(state.messagesList);} messages.stream().forEach((message) -> { Map existingMessage = conversationsMap.get(message.conversationId); if(existingMessage == null || message.time > existingMessage.time) { conversationsMap.put(message.conversationId, ['time': message.time, 'intentsPath': message.intentsPath]); } else { ifElseWorkaround[0] = ''; } }); conversationsMap.entrySet().forEach(conversation -> { if (intentsMap.containsKey(conversation.getValue().intentsPath)) { long intentsCount = intentsMap.get(conversation.getValue().intentsPath) + 1; intentsMap.put(conversation.getValue().intentsPath, intentsCount); } else {intentsMap.put(conversation.getValue().intentsPath, 1L);} }); return intentsMap.entrySet().stream().map(intentPath -> [intentPath.getKey().toString(): intentPath.getValue()]).collect(Collectors.toSet()) "
            }
        }
    }
}

Formatted script (for better readability - using .ts):

scripted_metric: {
  init_script: 'state.messagesList = new ArrayList();',
  map_script: `
    long currentMessageTime = doc['messageReceivedEvent.context.timestamp'].value.millis;
    Map currentMessage = [
      'conversationId': doc['messageReceivedEvent.context.conversationId.keyword'],
      'time': currentMessageTime,
      'intentsPath': doc['brainQueryRequestEvent.brainQueryRequest.user_data.intentsHistoryPath.keyword'].value
    ];
    state.messagesList.add(currentMessage);`,
  combine_script: 'return state',
  reduce_script: `
    List messages = new ArrayList();
    Map conversationsMap = new HashMap();
    Map intentsMap = new HashMap();
    boolean[] ifElseWorkaround = new boolean[1];

    for (state in states) {
      messages.addAll(state.messagesList);
    }

    messages.stream().forEach(message -> {
      Map existingMessage = conversationsMap.get(message.conversationId);
      if(existingMessage == null || message.time > existingMessage.time) {
        conversationsMap.put(message.conversationId, ['time': message.time, 'intentsPath': message.intentsPath]);
      } else {
        ifElseWorkaround[0] = true;
      }
    });

    conversationsMap.entrySet().forEach(conversation -> {
      if (intentsMap.containsKey(conversation.getValue().intentsPath)) {
        long intentsCount = intentsMap.get(conversation.getValue().intentsPath) + 1;
        intentsMap.put(conversation.getValue().intentsPath, intentsCount);
      } else {
        intentsMap.put(conversation.getValue().intentsPath, 1L);
      }
    });

    return intentsMap.entrySet().stream().map(intentPath -> [
      'path': intentPath.getKey().toString(),
      'count': intentPath.getValue()
    ]).collect(Collectors.toSet())`

The answer:

{
    "took": 2,
    "timed_out": false,
    "_shards": {
        "total": 5,
        "successful": 5,
        "skipped": 0,
        "failed": 0
    },
    "hits": {
        "total": {
            "value": 11,
            "relation": "eq"
        },
        "max_score": null,
        "hits": []
    },
    "aggregations": {
        "intentPathsCountAgg": {
            "value": [
                {
                    "smallTalk.greet -> smallTalk.greet2 -> smallTalk.greet3": 2
                },
                {
                    "smallTalk.greet -> smallTalk.greet2 -> smallTalk.greet3  -> smallTalk.greet4": 1
                },
                {
                    "smallTalk.greet -> smallTalk.greet2": 1
                }
            ]
        }
    }
}

Answer 2

Using script in Terms aggregation we can create buckets on first character of "context.action". Using similar terms sub aggregation we can get all the "context.action" under parent bucket ex A-> A.1->A.1.1 ...

Query:

{
  "size": 0,
  "aggs": {
    "conversations": {
      "terms": {
        "script": {
          "source": "def term=doc['context.action'].value; return term.substring(0,1);" 
--->  returns first character ex A,B,C etc
        },
        "size": 10
      },
      "aggs": {
        "sub_conversations": {
          "terms": {
            "script": {
              "source": "if(doc['context.action'].value.length()>1) return doc['context.action'];"--> All context.action under [A], length check to ignore [A]
            },
            "size": 10
          }
        },
        "count": {
          "cardinality": {
            "script": {
              "source": "if(doc['context.action'].value.length()>1) return doc['context.action'];"--> count of all context.action under A
            }
          }
        }
      }
    }
  }
}

Since in elastic search it not possible to join different documents. you will have to get combined key in client side by iterating over the aggregation bucket.

Result:

  "aggregations" : {
    "conversations" : {
      "doc_count_error_upper_bound" : 0,
      "sum_other_doc_count" : 0,
      "buckets" : [
        {
          "key" : "A",
          "doc_count" : 6,
          "sub_conversations" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : "A.1",
                "doc_count" : 2
              },
              {
                "key" : "A.1.1",
                "doc_count" : 2
              }
            ]
          },
          "count" : {
            "value" : 2
          }
        },
        {
          "key" : "B",
          "doc_count" : 2,
          "sub_conversations" : {
            "doc_count_error_upper_bound" : 0,
            "sum_other_doc_count" : 0,
            "buckets" : [
              {
                "key" : "B.1",
                "doc_count" : 1
              }
            ]
          },
          "count" : {
            "value" : 1
          }
        }
      ]
    }
  }