Updated: Oct 2010
This is a mini tutorial to get you up and going with the basics of the Haskell mongoDB drivers. You will need the mongoDB driver installed as well as mongo itself. Prompts used in this tutorial are:
$ = command line prompt
> = ghci repl prompt
From Hackage using cabal:
$ cabal install mongoDB
From Source:
$ git clone git://github.com/TonyGen/mongoDB-haskell.git mongoDB
$ cd mongoDB
$ runhaskell Setup.hs configure
$ runhaskell Setup.hs build
$ runhaskell Setup.hs install
Start a MongoDB instance for us to play with in a separate terminal window:
$ mongod --dbpath <directory where Mongo will store the data>
Start up a haskell repl:
$ ghci
Import the MongoDB driver library, and set OverloadedStrings so literal strings are converted to UTF-8 automatically.
> import Database.MongoDB
> :set -XOverloadedStrings
Create a connection pool for your mongo server, using the standard port (27017):
> pool <- newConnPool 1 $ host "127.0.0.1"
or for a non-standard port
> pool <- newConnPool 1 $ Host "127.0.0.1" (PortNumber 30000)
newConnPool takes the connection pool size and the host to connect to. It returns a ConnPool, which is a potential pool of TCP connections. They are not created until first access, so it is not possible to get a connection error here.
Note, plain IO code in this driver never raises an exception unless it invokes third party IO code that does. Driver code that may throw an exception says so in its Monad type, for example, ErrorT IOError IO a.
A query/update executes in an Access monad, which has access to a Pipe, WriteMode, and read-mode (MasterSlaveOk), and may throw a Failure. A Pipe is a single TCP connection.
To run an Access action (monad), supply WriteMode, MasterOrSlaveOk, Connection, and action to access. For example, to get a list of all the database on the server:
> access safe Master conn allDatabases
access return either Left Failure or Right result. Failure means there was a connection failure or a read or write exception like cursor expired or duplicate key insert.
Since we are working in ghci, which requires us to start from the IO monad every time, we'll define a convenient run function that takes an action and executes it against our "test" database on the server we just connected to, with typical write and read mode:
> let run action = access safe Master pool $ use (Database "test") action
use adds a Database to the action context, so query/update operations know which database to operate on.
MongoDB can store multiple databases -- separate namespaces under which collections reside.
As before, you can obtain the list of databases available on a connection:
> run allDatabases
The "test" database in context is ignored in this case because allDatabases is not a query on a specific database but on the server as a whole.
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 database "test" (captured in run above) and the colllection "posts".
You can obtain a list of all collections in the "test" database:
> run allCollections
Data in MongoDB is represented (and stored) using JSON-style documents, called BSON documents. A *Document" is simply a list of Fields, where each field is a named value. A *Value" is a basic type like Bool, Int, Float, String, Time; a special BSON value like Binary, Javascript, ObjectId; a (embedded) Document; or a list of values. Here's an example document which could represent a blog post:
> import Data.Time
> now <- getCurrentTime
> :{
let post = ["author" =: "Mike",
"text" =: "My first blog post!",
"tags" =: ["mongoDB", "Haskell"],
"date" =: now]
:}
To insert a document into a collection we can use the insert function:
> run $ insert "posts" post
When a document is inserted a special field, _id, is automatically added if the document doesn't already contain that field. 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.
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:
> run allCollections
Note, the system.indexes collection is a special internal collection that was created automatically.
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:
> run $ findOne (select [] "posts")
The result is a document matching the one that we inserted previously. Note, the returned document contains the _id field, 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:
> run $ findOne (select ["author" =: "Mike"] "posts")
If we try with a different author, like "Eliot", we'll get no result:
> run $ findOne (select ["author" =: "Eliot"] "posts")
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 function which accepts a list of documents to be inserted. It send only a single command to the server:
> now <- getCurrentTime
> :{
let post1 = ["author" =: "Mike",
"text" =: "Another post!",
"tags" =: ["bulk", "insert"],
"date" =: now]
:}
> :{
let post2 = ["author" =: "Eliot",
"title" =: "MongoDB is fun",
"text" =: "and pretty easy too!",
"date" =: now]
:}
> run $ insertMany "posts" [post1, post2]
- Note that post2 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.
To get more than a single document as the result of a query we use the find method. find returns a Cursor, which allows us to iterate over all matching documents. There are several ways in which we can iterate: we can call next to get documents one at a time or we can get all the results by applying the cursor to rest:
> Right cursor <- run $ find (select ["author" =: "Mike"] "posts")
> run $ rest cursor
Of course you can use bind (>>=) to combine these into one line:
> run $ find (select ["author" =: "Mike"] "posts") >>= rest
Note, next automatically closes the cursor when the last document has been read out of it. Similarly, rest automatically closes the cursor after returning all the results.
We can count how many documents are in an entire collection:
> run $ count (select [] "posts")
Or count how many documents match a query:
> run $ count (select ["author" =: "Mike"] "posts")
To do
To do