Creating logger in CouchDB?

Question

I would like to create a logger using CouchDB. Basically, everytime someone accesses the file, I would like like to write to the database the username and time the file has been accessed. If this was MySQL, I would just add a row for every access correspond to the user. I am not sure what to do in CouchDB. Would I need to store each access in array? Then what do I do during update, is there a way to append to the document? Would each user have his own document?

Answer 1

I couldn't find any documentation on how to append to an existing document or array without retrieving and updating the entire document. So for every event you log, you'll have to retrieve the entire document, update it and save it to the database. So you'll want to keep the documents small for two reasons:

• Log files/documents tend to grow big. You don't want to send large documents across the wire for each new log entry you add.
• Log files/documents tend to get updated a lot. If all log entries are stored in a single document and you're trying to write a lot of concurrent log entries, you're likely to run into mismatching document revisions on updates.

Your suggestion of user-based documents sounds like a good solution, as it will keep the documents small. Also, a single user is unlikely to generate concurrent log entries, minimizing any race conditions.

Another option would be to store a new document for each log entry. Then you'll never have to update an existing document, eliminating any race conditions and the need to send large documents between your application and the database.

Answer 2

Niels' answer is going down the right path with transactions. As he said, you will want to create a different document for each access - think of them as actions. Here's what one of those documents might look like

{
  "_id": "32 char hash",
  "_rev": "32 char hash",
  "when": Unix time stamp,
  "by": "some unique identifier
}

If you were tracking multiple files, then you'd want to add a "file" field and include a unique identifier.

Now the power of Map/Reduce begins to really shine, as it's extremely good at aggregating multiple pieces of data. Here's how to get the total number of views:

Map:

function(doc)
{
  emit(doc.at, 1);
}

Reduce:

function(keys, values, rereduce)
{
  return sum(values);
}

The reason I threw the time stamp (doc.at) into the key is that it allows us to get total views for a range of time. Ex., /dbName/_design/designDocName/_view/viewName?startkey=1000&endkey=2000&group=true gives us the total number of views between those two time stamps.

Cheers.