Kibana difference in doc and search strategies

2019 Unicorn Enterprises heavily recruiting engineers Python standard >>>

Both strategies included in the kibana: doc and search. Used two circular queue acquisition request, and responds.

doc code is as follows:
clientMethod: 'mget'

search code is as follows:
clientMethod: 'msearch'

It can be found by querying api:

mget command, you can execute multiple queries. But the query is basically index, type, id this

client.mget({
  body: {
    docs: [
      { _index: 'indexA', _type: 'typeA', _id: '1' },
      { _index: 'indexB', _type: 'typeB', _id: '1' },
      { _index: 'indexC', _type: 'typeC', _id: '1' }
    ]
  }
}, function(error, response){
  // ...
});

or

client.mget({
  index: 'myindex',
  type: 'mytype',
  body: {
    ids: [1, 2, 3]
  }
}, function(error, response){
  // ...
});

msearch command, you can implement complex queries, such as:

client.msearch({
  body: [
    // match all query, on all indices and types
    {},
    { query: { match_all: {} } },

    // query_string query, on index/mytype
    { _index: 'myindex', _type: 'mytype' },
    { query: { query_string: { query: '"Test 1"' } } }
  ]
});

Reproduced in: https: //my.oschina.net/u/204616/blog/545019