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From Erick Erickson <erickerick...@gmail.com>
Subject Re: Efficiently mining or parsing data out of XML source files
Date Sun, 03 Jun 2012 12:42:44 GMT
This seems really odd. How big are these XML files? Where are you parsing them?
You could consider using a SolrJ program with a SAX-style parser.

But the first question I'd answer is "what is slow?". The implications
of your post is that
parsing the XML is the slow part, it really shouldn't be taking
anywhere near this long IMO...

Best
Erick

On Thu, May 31, 2012 at 9:14 AM, Van Tassell, Kristian
<kristian.vantassell@siemens.com> wrote:
> I'm just wondering what the general consensus is on indexing XML data to Solr in terms
of parsing and mining the relevant data out of the file and putting them into Solr fields.
Assume that this is the XML file and resulting Solr fields:
>
> XML data:
> <mydoc id="1234">
> <title>foo</title>
> <bar attr1="val1"/>
> <baz>garbage data</baz>
> </ mydoc >
>
> Solr Fields:
> Id=1234
> Title=foo
> Bar=val1
>
> I'd previously set this process up using XSLT and have since tested using XMLBeans, JAXB,
etc. to get the relevant data. The speed at which this occurs, however, is not acceptable.
2800 objects take 11 minutes to parse and index into Solr.
>
> The big slowdown appears to be that I'm parsing the data with an XML parser.
>
> So, now I'm testing mining the data by opening the file as just a text file (using Groovy)
and picking out relevant data using regular expression matching. I'm now able to parse (mine)
the data and index the 2800 files in 72 seconds.
>
> So I'm wondering if the typical solution people use is to go with a non-XML solution.
It seems to make sense considering the search index would only want to store (as much data)
as possible and not rely on the incoming documents being xml compliant.
>
> Thanks in advance for any thoughts on this!
> -Kristian
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