mongodb/tutorial.md
2010-03-13 21:51:05 -06:00

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MongoDB Haskell Mini Tutorial
-----------------------------
__Author:__ Brian Gianforcaro (b.gianfo@gmail.com)
__Updated:__ 2/28/2010
This is a mini tutorial to get you up and going with the basics
of the Haskell mongoDB drivers. It is modeled after the
[pymongo tutorial](http://api.mongodb.org/python/1.4%2B/tutorial.html).
You will need the mongoDB bindings installed as well as mongo itself installed.
$ = command line prompt
> = ghci repl prompt
Installing Haskell Bindings
---------------------------
From Source:
$ git clone git://github.com/srp/mongoDB.git
$ cd mongoDB
$ runhaskell Setup.hs configure
$ runhaskell Setup.hs build
$ runhaskell Setup.hs install
From Hackage using cabal:
$ cabal install mongoDB
Getting Ready
-------------
Start a MongoDB instance for us to play with:
$ mongod
Start up a haskell repl:
$ ghci
Now We'll need to bring in the MongoDB/BSON bindings:
> import Database.MongoDB
> import Database.MongoDB.BSON
Making A Connection
-------------------
Open up a connection to your DB instance, using the standard port:
> con <- connect "127.0.0.1" []
or for a non-standard port
> import Network
> con <- connectOnPort "127.0.0.1" (Network.PortNumber 666) []
By default mongoDB will try to find the master and connect to it and
will throw an exception if a master can not be found to connect
to. You can force mongoDB to connect to the slave by adding SlaveOK as
a connection option, eg:
> con <- connect "127.0.0.1" [SlaveOK]
Databases, Collections and FullCollections
------------------------------------------
As many database servers, MongoDB has databases--separate namespaces
under which collections reside. Most of the APIs for this driver
request the *FullCollection* which is simply the *Database* and the
*Collection* concatenated with a period.
For instance 'myweb_prod.users' is the the *FullCollection* name for
the *Collection 'users' in the database 'myweb_prod'.
Databases and collections do not need to be created, just start using
them and MongoDB will automatically create them for you.
In the below examples we'll be using the following *FullCollection*:
> import Data.ByteString.Lazy.UTF8
> let postsCol = (fromString "test.posts")
You can obtain a list of databases available on a connection:
> dbs <- databaseNames con
You can obtain a list of collections available on a database:
> cols <- collectionNames con (fromString "test")
> map toString cols
["test.system.indexes"]
Documents
---------
Data in MongoDB is represented (and stored) using JSON-style
documents. In mongoDB we use the *BsonDoc* type to represent these
documents. At the moment a *BsonDoc* is simply a tuple list of the
type '[(ByteString, BsonValue)]'. Here's a BsonDoc which could represent
a blog post:
> import Data.Time.Clock.POSIX
> now <- getPOSIXTime
> :{
let post = [(fromString "author", BsonString $ fromString "Mike"),
(fromString "text",
BsonString $ fromString "My first blog post!"),
(fromString "tags",
BsonArray [BsonString $ fromString "mongodb",
BsonString $ fromString "python",
BsonString $ fromString "pymongo"]),
(fromString "date", BsonDate now)]
:}
With all the type wrappers and string conversion, it's hard to see
what's actually going on. Fortunately the BSON library provides
conversion functions *toBson* and *fromBson* for converting native
between the wrapped BSON types and many native Haskell types. The
functions *toBsonDoc* and *fromBsonDoc* help convert from tuple lists
with plain *String* keys, or *Data.Map*.
Here's the same BSON data structure using these conversion functions:
> :{
let post = toBsonDoc [("author", toBson "Mike"),
("text", toBson "My first blog post!"),
("tags", toBson ["mongoDB", "Haskell"]),
("date", BsonDate now)]
:}
Inserting a Document
-------------------
To insert a document into a collection we can use the *insert* function:
> insert con postsCol post
BsonObjectId 23400392795601893065744187392
When a document is inserted a special key, *_id*, is automatically
added if the document doesn't already contain an *_id* key. The value
of *_id* must be unique across the collection. *insert* returns the
value of *_id* for the inserted document. For more information, see
the [documentation on _id](http://www.mongodb.org/display/DOCS/Object+IDs).
After inserting the first document, the posts collection has actually
been created on the server. We can verify this by listing all of the
collections in our database:
> cols <- collectionNames con (fromString "test")
> map toString cols
[u'postsCol', u'system.indexes']
* Note The system.indexes collection is a special internal collection
that was created automatically.
Getting a single document with findOne
-------------------------------------
The most basic type of query that can be performed in MongoDB is
*findOne*. This method returns a single document matching a query (or
*Nothing* if there are no matches). It is useful when you know there is
only one matching document, or are only interested in the first
match. Here we use *findOne* to get the first document from the posts
collection:
> findOne con postsCol []
Just [(Chunk "_id" Empty,BsonObjectId (Chunk "K\151\153S9\CAN\138e\203X\182'" Empty)),(Chunk "author" Empty,BsonString (Chunk "Mike" Empty)),(Chunk "text" Empty,BsonString (Chunk "My first blog post!" Empty)),(Chunk "tags" Empty,BsonArray [BsonString (Chunk "mongoDB" Empty),BsonString (Chunk "Haskell" Empty)]),(Chunk "date" Empty,BsonDate 1268226361.753s)]
The result is a dictionary matching the one that we inserted
previously.
* Note: The returned document contains an *_id*, which was automatically
added on insert.
*findOne* also supports querying on specific elements that the
resulting document must match. To limit our results to a document with
author "Mike" we do:
> findOne con postsCol $ toBsonDoc [("author", toBson "Mike")]
Just [(Chunk "_id" Empty,BsonObjectId (Chunk "K\151\153S9\CAN\138e\203X\182'" Empty)),(Chunk "author" Empty,BsonString (Chunk "Mike" Empty)),(Chunk "text" Empty,BsonString (Chunk "My first blog post!" Empty)),(Chunk "tags" Empty,BsonArray [BsonString (Chunk "mongoDB" Empty),BsonString (Chunk "Haskell" Empty)]),(Chunk "date" Empty,BsonDate 1268226361.753s)]
If we try with a different author, like "Eliot", we'll get no result:
> findOne con postsCol $ toBsonDoc [("author", toBson "Eliot")]
Nothing
Bulk Inserts
------------
In order to make querying a little more interesting, let's insert a
few more documents. In addition to inserting a single document, we can
also perform bulk insert operations, by using the *insertMany* api
which accepts a list of documents to be inserted. This will insert
each document in the iterable, sending only a single command to the
server:
> now <- getPOSIXTime
> :{
let new_postsCol = [toBsonDoc [("author", toBson "Mike"),
("text", toBson "Another post!"),
("tags", toBson ["bulk", "insert"]),
("date", toBson now)],
toBsonDoc [("author", toBson "Eliot"),
("title", toBson "MongoDB is fun"),
("text", toBson "and pretty easy too!"),
("date", toBson now)]]
:}
> insertMany con postsCol new_posts
[BsonObjectId 23400393883959793414607732737,BsonObjectId 23400398126710930368559579137]
* Note that *new_posts !! 1* has a different shape than the other
posts - there is no "tags" field and we've added a new field,
"title". This is what we mean when we say that MongoDB is schema-free.
Querying for More Than One Document
------------------------------------
To get more than a single document as the result of a query we use the
*find* method. *find* returns a cursor instance, which allows us to
iterate over all matching documents. There are several ways in which
we can iterate: we can call *nextDoc* to get documents one at a time
or we can get a lazy list of all the results by applying the cursor
to *allDocs*:
> cursor <- find con postsCol $ toBsonDoc [("author", toBson "Mike")]
> allDocs cursor
Of course you can use bind (*>>=*) to combine these into one line:
> docs <- find con postsCol (toBsonDoc [("author", toBson "Mike")]) >>= allDocs
* Note: *nextDoc* automatically closes the cursor when the last
document has been read out of it. Similarly, *allDocs* automatically
closes the cursor when you've consumed to the end of the resulting
list.
Counting
--------
We can count how many documents are in an entire collection:
> num <- count con postsCol
Or we can query for how many documents match a query:
> num <- countMatching con postsCol (toBsonDoc [("author", toBson "Mike")])
Range Queries
-------------
No non native sorting yet.
Indexing
--------
WIP - coming soon.
Something like...
> index <- createIndex con testcol [("author", Ascending)] True