如何在 ElasticSearch 中使用带有“q”的 msearch()？

Question

I've been using the standard Python ElasticSearch client to make single requests in the following format:

es.search(index='my_index', q=query, size=5, search_type='dfs_query_then_fetch')

I now want to make queries in batch for multiple strings q .

I've seen this question explaining how to use the msearch() functionality to do queries in batch. However, msearch requires the full json-formatted request body for each request. I'm not sure which parameters in the query API correspond to just the q parameter from search() , or size , or search_type , which seem to be API shortcuts specific to the single-example search() .

How can I use msearch but specify q , size , and search_type ?

Answer 1

I read through the API and figured out how to batch simple search queries:

from typing import List

from elasticsearch import Elasticsearch

import json

def msearch(
        es: Elasticsearch,
        max_hits: int,
        query_strings: List[str],
        index: str
    ):
    search_arr = []
    
    for q in query_strings:
        search_arr.append({'index': index })
        search_arr.append(
            {
                "query": {
                    "query_string": {
                        "query": q
                    }
            },
            'size': max_hits 
        })
    
    request = ''
    request = ' \n'.join([json.dumps(x) for x in search_arr])
    resp = es.msearch(body = request)
    return resp

msearch(es, query_strings=['query 1', 'query 2'], max_hits=1, index='my_index')

EDIT: For my use case, I made one more improvement, which was because I didn't want to return the entire document in the result– for my purpose, I just needed the document ID and its score.

So the final search request object part looked like this, including the '_source': False bit:

        search_arr.append(
            {
                # Queries `q` using Lucene syntax.
                "query": {
                    "query_string": {
                        "query": q
                    },
                },
                # Don't return the full profile string, etc. with the result.
                # We just want the ID and the score.
                '_source': False,
                # Only return `max_hits` documents.
                'size': max_hits 
            }
        )