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A schema analyzer for MongoDB
Java JavaScript
branch: master

README.markdown

Meet Variety, a Schema Analyzer for MongoDB

This lightweight tool helps you get a sense of your application's schema, as well as any outliers to that schema. Particularly useful when you inherit a codebase with data dump and want to quickly learn how the data's structured. Also useful for finding rare keys.

Build Status


“I happen to slowly be falling in love with Variety! It is actually one of the most useful tools to get a sense for a messy/unknown data set, and I have put it in a few of our exercises at Zipfian Academy.”

Jon Dinu
Co-founder of Zipfian Academy


Also featured on the official MongoDB blog.

An Easy Example

We'll make a collection:

db.users.insert({name: "Tom", bio: "A nice guy.", pets: ["monkey", "fish"], someWeirdLegacyKey: "I like Ike!"});
db.users.insert({name: "Dick", bio: "I swordfight.", birthday: new Date("1974/03/14")});
db.users.insert({name: "Harry", pets: "egret", birthday: new Date("1984/03/14")});
db.users.insert({name: "Geneviève", bio: "Ça va?"});
db.users.insert({name: "Jim", someBinData: new BinData(2,"1234")});

So, let's see what we've got here:

$ mongo test --eval "var collection = 'users'" variety.js

+------------------------------------------------------------+
| key                | types        | occurrences | percents |
| ------------------ | ------------ | ----------- | -------- |
| _id                | ObjectId     |           5 |    100.0 |
| name               | String       |           5 |    100.0 |
| bio                | String       |           3 |     60.0 |
| birthday           | String       |           2 |     40.0 |
| pets               | Array,String |           2 |     40.0 |
| someBinData        | BinData-old  |           1 |     20.0 |
| someWeirdLegacyKey | String       |           1 |     20.0 |
+------------------------------------------------------------+

("test" is the database containing the collection we are analyzing.)

Hmm. Looks like everybody has a "name" and "_id". Most, but not all have a "bio".

Interestingly, it looks like "pets" can be either an array or a string. Will this cause any problems in the application, I wonder?

Seems like the first document created has a weird legacy key—those damn fools who built the prototype didn't clean up after themselves. If there were a thousand such early documents, I might cross-reference the codebase to confirm they are no longer used, and then delete them all. That way they'll not confuse any future developers.

Results are stored for future use in a varietyResults database.

See Progress When Analysis Takes a Long Time

Tailing the log is great for this. Mongo provides a "percent complete" measurement for you. These operations can take a long time on huge collections.

Analyze Only Recent Documents

Perhaps you have a really large collection, and you can't wait a whole day for Variety's results.

Perhaps you want to ignore a collection's oldest documents, and only see what the collection's documents' structures have been looking like, as of late.

One can apply a "limit" constraint, which analyzes only the newest documents in a collection (unless sorting), like so:

$ mongo test --eval "var collection = 'users', limit = 1" variety.js

Let's examine the results closely:

+----------------------------------------------------+
| key         | types       | occurrences | percents |
| ----------- | ----------- | ----------- | -------- |
| _id         | ObjectId    |           1 |    100.0 |
| name        | String      |           1 |    100.0 |
| someBinData | BinData-old |           1 |    100.0 |
+----------------------------------------------------+

We are only examining the last document here ("limit = 1"). It belongs to Geneviève, and only contains the _id, name and bio fields. So it makes sense these are the only three keys.

Analyze Documents to a Maximum Depth

Perhaps you have a potentially very deep nested object structure, and you don't want to see more than a few levels deep in the analysis.

One can apply a "maxDepth" constraint, which limits the depth Variety will recursively search to find new objects.

db.users.insert({name:"Walter", someNestedObject:{a:{b:{c:{d:{e:1}}}}}});

The default will traverse all the way to the bottom of that structure:

$ mongo test --eval "var collection = 'users'" variety.js

+----------------------------------------------------------------+
| key                        | types    | occurrences | percents |
| -------------------------- | -------- | ----------- | -------- |
| _id                        | ObjectId |           1 |    100.0 |
| name                       | String   |           1 |    100.0 |
| someNestedObject           | Object   |           1 |    100.0 |
| someNestedObject.a         | Object   |           1 |    100.0 |
| someNestedObject.a.b       | Object   |           1 |    100.0 |
| someNestedObject.a.b.c     | Object   |           1 |    100.0 |
| someNestedObject.a.b.c.d   | Object   |           1 |    100.0 |
| someNestedObject.a.b.c.d.e | Number   |           1 |    100.0 |
+----------------------------------------------------------------+

$ mongo test --eval "var collection = 'users', maxDepth = 3" variety.js

+----------------------------------------------------------+
| key                  | types    | occurrences | percents |
| -------------------- | -------- | ----------- | -------- |
| _id                  | ObjectId |           1 |    100.0 |
| name                 | String   |           1 |    100.0 |
| someNestedObject     | Object   |           1 |    100.0 |
| someNestedObject.a   | Object   |           1 |    100.0 |
| someNestedObject.a.b | Object   |           1 |    100.0 |
+----------------------------------------------------------+

As you can see, Variety only traversed three levels deep.

Analyze a Subset of Documents

Perhaps you have a large collection, or you only care about some subset of the documents.

One can apply a "query" constraint, which takes a standard Mongo query object, to filter the set of documents required before analysis.

$ mongo test --eval "var collection = 'users', query = {'caredAbout':true}" variety.js

Analyze Documents Sorted In a Particular Order

Perhaps you want to analyze a subset of documents sorted in an order other than creation order, say, for example, sorted by when documents were updated.

One can apply a "sort" constraint, which analyzes documents in the specified order like so:

$ mongo test --eval "var collection = 'users', sort = { updated_at : -1 }" variety.js

Render Output As JSON For Easy Ingestion and Parsing

Variety supports two different output formats:

  • ASCII: nicely formatted tables (as in this README)
  • JSON: valid JSON results for subsequent processing in other tools (see also quiet option)

Default format is ascii. You can select the type of format with property outputFormat provided to Variety. Valid values are ascii and json.

$ mongo test --quiet --eval "var collection = 'users', outputFormat='json'" variety.js

Quiet Option

Both MongoDB and Variety output some additional information to standard output. If you want to remove this info, you can use --quiet option provided to mongo executable. Variety can also read that option and mute unnecessary output. This is useful in connection with outputFormat=json. You would then receive only JSON, without any other characters around it.

$ mongo test --quiet --eval "var collection = 'users', sort = { updated_at : -1 }" variety.js

Save Results in MongoDB For Future Use

By default, Variety prints results only to standard output and does not store them in MongoDB itself. If you want to persist them automatically in database for later usage, you can set the parameter persistResults. Variety then stores result documents in database varietyResults and the collection name is derived from the source collection's name. If the source collection's name is users, Variety will store results in collection usersKeys under varietyResults database.

$ mongo test --quiet --eval "var collection = 'users', persistResults=true" variety.js
"But my dad told me MongoDB is a schemaless database!"

First of all, your father is a great guy. Moving on...

A Mongo collection does not enforce a predefined schema like a relational database table. Still, documents in real-world collections nearly always have large sections for which the format of the data is the same. In other words, there is a schema to the majority of collections, it's just enforced by the application, rather than by the database system. And this schema is allowed to be a bit fuzzy, in the same way that a given table column might not be required in all rows, but to a much greater degree of flexibility. So we examine what percent of documents in the collection contain a key, and we get a feel for, among other things, how crucial that key is to the proper functioning of the application.

Dependencies

Absolutely none, except MongoDB. Written in 100% JavaScript. (mongod's "noscripting" may not be set to true, and 'strict mode' must be disabled.)

Reporting Issues / Contributing

Please report any bugs and feature requests on the Github issue tracker. I will read all reports!

I accept pull requests from forks. Very grateful to accept contributions from folks.

Core Maintainers

Special Thanks

Additional special thanks to Gaëtan Voyer-Perraul (@gatesvp) and Kristina Chodorow (@kchodorow) for answering other people's questions about how to do this on Stack Overflow, thereby providing me with the initial seed of code which grew into this tool.

Much thanks also, to Kyle Banker (@Hwaet) for writing an unusually good book on MongoDB, which has taught me everything I know about it so far.

Tools Which Use Variety (Open Source)

  • MightyMightyMongo (experimental): a browser-based GUI for exploring MongoDB collections, it allows users to also view Variety results. The project is not directly affiliated with Variety, however the creator/core committer has also contributed to Variety.
Stay Safe

I have every reason to believe this tool will not corrupt your data or harm your computer. But if I were you, I would not use it in a production environment.

Released by Maypop Inc, © 2012–2015, under the MIT License.

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