Docs Menu
Docs Home
/
MongoDB Compass
/
Interact with Your Data
/
Analyze Data Schema

Export Your Schema

On this page

  • Schema Object Properties
  • Example Schema

You can export your schema after analyzing it. This is useful for sharing your schema and comparing schemas across collections.

If you have not already done so, analyze your schema:

  1. Select your desired collection and click the Schema tab.

  2. Click Analyze Schema.

Note

When Compass analyzes your schema, it samples a random subset of documents from your collection. To learn more about sampling, see Sampling.

Once your schema has been analyzed, export your schema:

  1. In the top menu bar, click Collection.

  2. From the dropdown, click Share Schema as JSON.

Image showing Collection dropdown

Your schema is copied to your clipboard as a JSON object.

Schema Object Properties

Schema objects have count and fields properties:

  • count is an integer that represents the number of documents sampled from the collection to generate the schema.

  • fields is an array of metadata objects that correspond to each field in the documents analyzed during sampling. Each element in the fields array contains the following fields:

Property
Data type
Description

name

String

Name of the corresponding field, e.g. _id.

path

String

Path to the corresponding field within a document.

count

Integer

Number of documents in which the corresponding field appears.

types

Array

Array of metadata objects that represent each data type that appears in the corresponding field.

types[n].name

String

Name of this data type.

types[n].bsonType

String

BSON type of this data type.

types[n].path

String

Path to the corresponding field within a document.

types[n].count

Integer

Number of times this data type appears in the corresponding field.

types[n].values

Array

Array of the actual sampled values that appear in the corresponding field and match this data type.

types[n].total_count

Integer

If the corresponding field is an array, the number of elements in that array.

types[n].probability

Number

Probability that the value of the corresponding field is this data type in a random document.

types[n].unique

Integer

Number of unique values of this data type that appear in the corresponding field.

types[n].has_duplicates

Boolean

true if a single value of this data type appears multiple times in the corresponding field. Otherwise false.

types[n].lengths

Array

If this data type is an array, an array of integers representing the lengths of arrays found in the corresponding field. Not present for other data types.

types[n].average_length

Number

If this data type is an array, the average length of arrays in the corresponding field across sampled documents. Not present for other data types.

total_count

Integer

Number of documents sampled from the collection.

type

String or Array

String or array of strings representing possible types for the corresponding field.

has_duplicates

Boolean

true if a single value appears multiple times in the corresponding field. Otherwise false.

probability

Number

Probability that a random document contains the corresponding field.

Example Schema

The following example uses a collection of 3 documents, each with a sport field and unique information about that sport:

1[
2  {
3    "_id": { "$oid":"5e8359ba7782b98ba98c16fd" },
4    "sport": "Baseball",
5    "equipment": [ "bat", "baseball", "glove", "helmet" ]
6  },
7  {
8    "_id": { "$oid":"5e835a727782b98ba98c16fe" },
9    "sport": "Football",
10    "variants": {
11        "us":"Soccer",
12        "eu":"Football"
13    }
14  },
15  {
16    "_id": { "$oid":"5e835ade7782b98ba98c16ff" },
17    "sport": "Cricket",
18    "origin": "England"
19  }
20]

You can import the above example to MongoDB Compass to experiment with schema outputs. To import the example collection into MongoDB Compass:

  1. Copy the JSON documents above.

  2. In MongoDB Compass, select a collection or create a new collection to import the copied documents to. The Documents tab displays.

  3. Click Add Data.

  4. Select Insert Document from the dropdown.

  5. In the JSON view of the dialog, paste the copied documents and click Insert.

The example above outputs the following schema:

1{
2  "fields": [
3    {
4      "name": "_id",
5      "path": "_id",
6      "count": 3,
7      "types": [
8        {
9          "name": "ObjectID",
10          "bsonType": "ObjectID",
11          "path": "_id",
12          "count": 3,
13          "values": [
14            "5e8359ba7782b98ba98c16fd",
15            "5e835a727782b98ba98c16fe",
16            "5e835ade7782b98ba98c16ff"
17          ],
18          "total_count": 0,
19          "probability": 1,
20          "unique": 3,
21          "has_duplicates": false
22        }
23      ],
24      "total_count": 3,
25      "type": "ObjectID",
26      "has_duplicates": false,
27      "probability": 1
28    },
29    {
30      "name": "equipment",
31      "path": "equipment",
32      "count": 1,
33      "types": [
34        {
35          "name": "Undefined",
36          "type": "Undefined",
37          "path": "equipment",
38          "count": 2,
39          "total_count": 0,
40          "probability": 0.6666666666666666,
41          "unique": 1,
42          "has_duplicates": true
43        },
44        {
45          "name": "Array",
46          "bsonType": "Array",
47          "path": "equipment",
48          "count": 1,
49          "types": [
50            {
51              "name": "String",
52              "bsonType": "String",
53              "path": "equipment",
54              "count": 4,
55              "values": [
56                "bat",
57                "baseball",
58                "glove",
59                "helmet"
60              ],
61              "total_count": 0,
62              "probability": 1,
63              "unique": 4,
64              "has_duplicates": false
65            }
66          ],
67          "lengths": [
68            4
69          ],
70          "total_count": 4,
71          "probability": 0.3333333333333333,
72          "average_length": 4
73        }
74      ],
75      "total_count": 3,
76      "type": [
77        "Undefined",
78        "Array"
79      ],
80      "has_duplicates": true,
81      "probability": 0.3333333333333333
82    },
83    {
84      "name": "origin",
85      "path": "origin",
86      "count": 1,
87      "types": [
88        {
89          "name": "Undefined",
90          "type": "Undefined",
91          "path": "origin",
92          "count": 2,
93          "total_count": 0,
94          "probability": 0.6666666666666666,
95          "unique": 1,
96          "has_duplicates": true
97        },
98        {
99          "name": "String",
100          "bsonType": "String",
101          "path": "origin",
102          "count": 1,
103          "values": [
104            "England"
105          ],
106          "total_count": 0,
107          "probability": 0.3333333333333333,
108          "unique": 1,
109          "has_duplicates": false
110        }
111      ],
112      "total_count": 3,
113      "type": [
114        "Undefined",
115        "String"
116      ],
117      "has_duplicates": true,
118      "probability": 0.3333333333333333
119    },
120    {
121      "name": "sport",
122      "path": "sport",
123      "count": 3,
124      "types": [
125        {
126          "name": "String",
127          "bsonType": "String",
128          "path": "sport",
129          "count": 3,
130          "values": [
131            "Baseball",
132            "Football",
133            "Cricket"
134          ],
135          "total_count": 0,
136          "probability": 1,
137          "unique": 3,
138          "has_duplicates": false
139        }
140      ],
141      "total_count": 3,
142      "type": "String",
143      "has_duplicates": false,
144      "probability": 1
145    },
146    {
147      "name": "variants",
148      "path": "variants",
149      "count": 1,
150      "types": [
151        {
152          "name": "Undefined",
153          "type": "Undefined",
154          "path": "variants",
155          "count": 2,
156          "total_count": 0,
157          "probability": 0.6666666666666666,
158          "unique": 1,
159          "has_duplicates": true
160        },
161        {
162          "name": "Document",
163          "bsonType": "Document",
164          "path": "variants",
165          "count": 1,
166          "fields": [
167            {
168              "name": "eu",
169              "path": "variants.eu",
170              "count": 1,
171              "types": [
172                {
173                  "name": "String",
174                  "bsonType": "String",
175                  "path": "variants.eu",
176                  "count": 1,
177                  "values": [
178                    "Football"
179                  ],
180                  "total_count": 0,
181                  "probability": 1,
182                  "unique": 1,
183                  "has_duplicates": false
184                }
185              ],
186              "total_count": 1,
187              "type": "String",
188              "has_duplicates": false,
189              "probability": 1
190            },
191            {
192              "name": "us",
193              "path": "variants.us",
194              "count": 1,
195              "types": [
196                {
197                  "name": "String",
198                  "bsonType": "String",
199                  "path": "variants.us",
200                  "count": 1,
201                  "values": [
202                    "Soccer"
203                  ],
204                  "total_count": 0,
205                  "probability": 1,
206                  "unique": 1,
207                  "has_duplicates": false
208                }
209              ],
210              "total_count": 1,
211              "type": "String",
212              "has_duplicates": false,
213              "probability": 1
214            }
215          ],
216          "total_count": 0,
217          "probability": 0.3333333333333333
218        }
219      ],
220      "total_count": 3,
221      "type": [
222        "Undefined",
223        "Document"
224      ],
225      "has_duplicates": true,
226      "probability": 0.3333333333333333
227    }
228  ],
229  "count": 3
230}

Back

Analyze Data Schema

Next

View Performance