Mercurial > browser-couch

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<h1>Using BrowserCouch</h1>

<p>Suppose we want to add offline support for a blog.  To get a
database called <tt>blog-posts</tt> in BrowserCouch, you can use the
following function:</p>

<div class="example-code">
BrowserCouch.get('blog-posts', onRetrieveCb, new FakeStorage());
</div>

<p>It's clear that the first parameter is the name of the database we
want; the second parameter is the callback that will be passed the
database once it's fetched.</p>

<p>The third parameter specifies the engine that will be used to
persistently store our database across browsing sessions. In this case
we're using <tt>FakeStorage</tt>, which just stores everything
non-persistently in memory for the sake of example. We could just as
easily leave out the third parameter to have BrowserCouch figure out
the best storage backend based on our browser's capabilities.</p>

<p>If the database doesn't already exist, an empty one will be created
for us. Putting blog posts into the database can be done via
an <tt>onRetrieveCb()</tt> function like this:</p>

<div class="example-code">
function onRetrieveCb(db) {
  blogDb = db;
  blogDb.put(
    [{id: 0, author: 'Myk', title: 'Burritos', content: 'Burritos are yum.'},
     {id: 1, author: 'Thunder', title: 'Bacon', content: 'I like bacon.'},
     {id: 2, author: 'Thunder', title: 'Beer', content: 'Beer is good too.'}],
    onPutCb
  );
};
</div>

<p>Every item we put into our database needs to have an <tt>id</tt>
attribute, but aside from that, the item can contain any
JSON-encodable data.</p>

<p>Now that we've put some data into our database, we can play around
with generating views on the data using the <a
href="http://en.wikipedia.org/wiki/MapReduce">MapReduce</a> mechanism.
For instance, here's an ad-hoc view using only the map phase that
organizes all the post titles by author:</p>

<div class="example-code">
function onPutCb() {
  blogDb.view({
    map: function(doc, emit) {
      emit(doc.author, doc.title);
    },
    finished: function(result) {
      displayInElement(result, 'author-keyed-view');
      tryAnotherView();
    }
  });
}
</div>

<p>The output placed in the <tt>author-keyed-view</tt> element is:</p>

<div class="example-output" id="author-keyed-view">
</div>

<p>As you can see, BrowserCouch essentially iterated over all of the
blog posts, passing each one to <tt>map()</tt>, along with an
arbitrary function called <tt>emit()</tt>.  The <tt>map()</tt>
function then emitted key-value pairs which show up in the view. It's
worth noting that <tt>map()</tt> can call <tt>emit()</tt> as much as
it wants to; each call will add a new row to the view.</p>

<p>We could also try creating another view that adds a
<tt>reduce()</tt> function to group together the blog post titles with
the authors:</p>

<div class="example-code">
function tryAnotherView() {
  blogDb.view({
    map: function(doc, emit) {
      emit(doc.author, doc.title);
    },
    reduce: function(keys, values) {
      return values;
    },
    finished: function(result) {
      displayInElement(result, 'author-titles-view');
      tryMyView();
    }
  });
}
</div>

<p>The output is as follows:</p>

<div class="example-output" id="author-titles-view">
</div>

<p>The <tt>reduce()</tt> mechanism is a bit harder to
understand. Essentially, BrowserCouch takes all the rows generated by
<tt>map()</tt> and generates a new list of key-value rows, where the
value of each row is the list of all values that match the row's key.
This explains what the <tt>values</tt> argument passed to
<tt>reduce()</tt> is.</p>

<p>The <tt>keys</tt> argument is a list of two-tuples, the first of
which is the key, and the second of which is the document id that
emitted the key during the map phase.</p>

<p>The <tt>reduce()</tt> function is called for each unique key, and
its return value is the value for its key in the final view.</p>

<h1>Now You Try!</h1>

<p>If your eyes are crossed right now, no worries&mdash;it took me a
long time to understand exactly what MapReduce was doing, and I
probably didn't explain it very well either. That said, I also found
that the easiest way to understand how MapReduce worked was just to
play around with making my own view.</p>

<p>So, to get a better feel for how MapReduce works, you can use the
text field below to try making your own view. Just press the tab key
when you're done making changes to recompute the view.</p>

<textarea class="example-code try-code">
function tryMyView() {
  blogDb.view({
    map: function(doc, emit) {
      emit(doc.author, doc.title);
    },
    reduce: function(keys, values) {
      return values;
    },
    finished: function(result) {
      displayInElement(result, 'try-my-view');
    }
  });
}
</textarea>

<p>Here's the output to the above view:</p>

<div class="example-output" id="try-my-view"></div>

<h1>Where To Go From Here</h1>

<p>There's features in the API that aren't covered here, so check out
the check out the <a class="intra-wiki"
href="index.html#js/tests.js">annotated source code for the test
suite</a> for more sample code.</p>

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author	Atul Varma <varmaa@toolness.com>
date	Mon, 20 Apr 2009 16:37:07 -0700
parents	17ce8b6be452
children	38abd7bc4886