基于@Wolkenarchitekt的回答:https://stackoverflow.com/a/48117846/8808983，我写了一个脚本，可以在db中找到所有键的模式，我认为它可以帮助其他人阅读这个线程:

"""
Python 3
This script get list of patterns and print the collections that contains fields with this patterns.
"""

import argparse

import pymongo
from bson import Code


# initialize mongo connection:
def get_db():
    client = pymongo.MongoClient("172.17.0.2")
    db = client["Data"]
    return db


def get_commandline_options():
    description = "To run use: python db_fields_pattern_finder.py -p <list_of_patterns>"
    parser = argparse.ArgumentParser(description=description)
    parser.add_argument('-p', '--patterns', nargs="+", help='List of patterns to look for in the db.', required=True)
    return parser.parse_args()


def report_matching_fields(relevant_fields_by_collection):
    print("Matches:")

    for collection_name in relevant_fields_by_collection:
        if relevant_fields_by_collection[collection_name]:
            print(f"{collection_name}: {relevant_fields_by_collection[collection_name]}")

    # pprint(relevant_fields_by_collection)


def get_collections_names(db):
    """
    :param pymongo.database.Database db:
    :return list: collections names
    """
    return db.list_collection_names()


def get_keys(db, collection):
    """
    See: https://stackoverflow.com/a/48117846/8808983
    :param db:
    :param collection:
    :return:
    """
    map = Code("function() { for (var key in this) { emit(key, null); } }")
    reduce = Code("function(key, stuff) { return null; }")
    result = db[collection].map_reduce(map, reduce, "myresults")
    return result.distinct('_id')


def get_fields(db, collection_names):
    fields_by_collections = {}
    for collection_name in collection_names:
        fields_by_collections[collection_name] = get_keys(db, collection_name)
    return fields_by_collections


def get_matches_fields(fields_by_collections, patterns):
    relevant_fields_by_collection = {}
    for collection_name in fields_by_collections:
        relevant_fields = [field for field in fields_by_collections[collection_name] if
                           [pattern for pattern in patterns if
                            pattern in field]]
        relevant_fields_by_collection[collection_name] = relevant_fields

    return relevant_fields_by_collection


def main(patterns):
    """
    :param list patterns: List of strings to look for in the db.
    """
    db = get_db()

    collection_names = get_collections_names(db)
    fields_by_collections = get_fields(db, collection_names)
    relevant_fields_by_collection = get_matches_fields(fields_by_collections, patterns)

    report_matching_fields(relevant_fields_by_collection)


if __name__ == '__main__':
    args = get_commandline_options()
    main(args.patterns)

试试这个:

doc=db.thinks.findOne();
for (key in doc) print(key);

我们可以通过使用mongo js文件来实现这一点。在getCollectionName.js文件中添加以下代码，并在Linux控制台中运行js文件，如下所示:

mongodb——host 192.168.1.135 getCollectionName.js

db_set = connect("192.168.1.135:27017/database_set_name"); // for Local testing
// db_set.auth("username_of_db", "password_of_db"); // if required

db_set.getMongo().setSlaveOk();

var collectionArray = db_set.getCollectionNames();

collectionArray.forEach(function(collectionName){

    if ( collectionName == 'system.indexes' || collectionName == 'system.profile' || collectionName == 'system.users' ) {
        return;
    }

    print("\nCollection Name = "+collectionName);
    print("All Fields :\n");

    var arrayOfFieldNames = []; 
    var items = db_set[collectionName].find();
    // var items = db_set[collectionName].find().sort({'_id':-1}).limit(100); // if you want fast & scan only last 100 records of each collection
    while(items.hasNext()) {
        var item = items.next(); 
        for(var index in item) {
            arrayOfFieldNames[index] = index;
        }
    }
    for (var index in arrayOfFieldNames) {
        print(index);
    }

});

quit();

由于@ackuser

你可以用MapReduce来做:

mr = db.runCommand({
  "mapreduce" : "my_collection",
  "map" : function() {
    for (var key in this) { emit(key, null); }
  },
  "reduce" : function(key, stuff) { return null; }, 
  "out": "my_collection" + "_keys"
})

然后在结果集合上单独运行，以便找到所有的键:

db[mr.result].distinct("_id")
["foo", "bar", "baz", "_id", ...]

您可以在3.4.4版本中使用新的$objectToArray聚合操作符来将所有顶部键-值对转换为文档数组，然后使用$unwind和$group以及$addToSet来获得整个集合中的不同键。(使用$$ROOT来引用顶级文档。)

db.things.aggregate([
  {"$project":{"arrayofkeyvalue":{"$objectToArray":"$$ROOT"}}},
  {"$unwind":"$arrayofkeyvalue"},
  {"$group":{"_id":null,"allkeys":{"$addToSet":"$arrayofkeyvalue.k"}}}
])

您可以使用以下查询来获取单个文档中的键。

db.things.aggregate([
  {"$match":{_id: "<<ID>>"}}, /* Replace with the document's ID */
  {"$project":{"arrayofkeyvalue":{"$objectToArray":"$$ROOT"}}},
  {"$project":{"keys":"$arrayofkeyvalue.k"}}
])

下面是用Python编写的示例: 这个示例内联返回结果。

from pymongo import MongoClient
from bson.code import Code

mapper = Code("""
    function() {
                  for (var key in this) { emit(key, null); }
               }
""")
reducer = Code("""
    function(key, stuff) { return null; }
""")

distinctThingFields = db.things.map_reduce(mapper, reducer
    , out = {'inline' : 1}
    , full_response = True)
## do something with distinctThingFields['results']