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I have a ML database with a few tens of thousands of documents in it, and a query that returns some simple calculated values for either all or a subset of those documents. The document count has grown to the point that the "all documents" option no longer reliably runs without timing out, and is only going to get worse as the document count grows. The obvious solution is for the client application to use the other form and paginate the results. It's an offline batch process, so overall speed isn't an issue - we'd just like to keep individual requests sane.

The paged version of the query is very simple:

declare namespace ns = "http://some.namespace/here"

declare variable $fromCount external;
declare variable $toCount external;

<response> {
  for $doc in fn:doc()/ns:entity[$fromCount to $toCount]
  return
  <doc> omitted for brevity </doc>
} </response>

The problem is that the query is slower the further through the document set the requested page is; presumably because it's having to load every document in order, check whether it's the right type and iterate until its found $fromCount ns:entitys before it even begins building the response.

One wrinkle is that there are other types of document in the database, so just using fn:doc isn't a realistic option (although, they are in different directories, so xdmp:directory() might be an option; something I'll look into.)

There also isn't currently an index on the ns:entity element; would that help? It's always the root-node of a document, and the documents are quite large, so I'm concerned about the size of the index. Also, (the slow part of) this query isn't interested in the value of the element, just that it exists.

I thought about using the search: api for it's built-in paging, but it seems overkill for a query that is intended to match all documents; surely it's possible to manually construct the query that search:search() would build internally.

It seems like what I really need is an efficient list of all root-nodes of a certain type in the database. Does Marklogic maintain such a thing? If Not would an index solve the problem?

Edit: It turns out that the answer in my case is use the xdmp:directory() option, since ML apparently stores a fast, in-memory list of all documents. Still, if there is a more general solution to the problem, it's bound to be of interest, so I'll leave the question here.

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Your analysis is correct:

presumably because it's having to load every document in order, check whether it's the right type and iterate until its found $fromCount ns:entitys before it even begins building the response

The usual answer is cts:search plus the unfiltered option. You found that xdmp:directory was faster, but you should still be able to measure pagination times as O(n) even if the scale is smaller. See http://docs.marklogic.com/guide/performance/unfiltered#chapter - basically the database is guarding against returning false positives, unless you tell it not to.

Another approach might be to use cts:uris and its limit option, but this might require managing pagination state in terms of start values rather than page counts. For example if the last item on page 1 was "cat", you would use "cat" as arg2 when calling cts:uris for the next page. You could still use pagination start-stop values, too. That would still be O(n) - but at a much smaller scale.

于 2012-10-08T17:37:15.547 回答