Re: [sleuthkit-users] Regular Expressions

[Brian C. <ca...@sl...>]

Hi Luis,

We currently (and will in the future) maintain two “copies” of the text to support text and regexp searches.   What will change if we adopt the 32KB approach is to start storing the text in a non-indexed “string” field (which has a size limitation of 32KB).  It will not be tokenized and Solr will apply the regular expression to each text field.  

So, this is in essence what Jon was also proposing of just doing a regexp on the extracted text.  Because this new field is not indexed, it will be slower.  Exact search performance hit TBD.  

brian





> On Nov 14, 2016, at 8:53 PM, Luís Filipe Nassif <lfc...@gm...> wrote:
> 
> Hi Brian,
> 
> I didn't understand exactly how text chunk size will help to index spaces and other chars that breaks words into tokens. You will index text twice? First with default tokenization, breaking words at spaces and similar chars, and second time will index the whole text chunk as one single token? Does the 32KB is the maximum Lucene token size? I think you can do the second indexing (with performance consequences if you index twice, it should be configurable, so users could disable it if they do not need regex or if performance is critical). But I think you should not disable the default indexing (with tokenization), otherwise users will have to always use * as prefix and suffix of their searches, if not they will miss a lot of hits. I do not known if they will be able to do phrase searches, because Lucene does not allow to use * into a phrase search (* between two " "). I do not know about Solr and if it extended that.
> 
> Regards,
> Luis Nassif 
> 
> 2016-11-14 20:14 GMT-02:00 Brian Carrier <ca...@sl...>:
> Making this a little more specific, we seem to have two options to solve this problem (which is inherent to Lucene/Solr/Elastic):
> 
> 1) We store text in 32KB chunks (instead of our current 1MB chunks) and can have the full power of regular expressions.   The downside of the smaller chunks is that there are more boundaries and places where a term could span the boundary and we could miss a hit if it spans that boundary.   If we needed to, we could do some fancy overlapping.   32KB of text is about 12 pages of English text (less for non-English).
> 
> 2) We limit the types of regular expressions that people can use and keep our 1MB chunks. We’ll add some logic into Autopsy to span tokens, but we won’t be able to support all expressions.  For example, if you gave us “\d\d\d\s\d\d\d\d” we’d turn that into a search for “\d\d\d \d\d\d\d”, but we wouldn’t able to support a search like “\d\d\d[\s-]\d\d\d\d”.  Well we could in theory, but we dont’ want to add crazy complexity here.
> 
> So, the question is if you’d rather have smaller chunks and the full breadth of regular expressions or a more limited set of expressions and bigger chunks.  We are looking at the performance differences now, but wanted to get some initial opinions.
> 
> 
> 
> 
> > On Nov 14, 2016, at 1:09 PM, Brian Carrier <ca...@sl...> wrote:
> >
> > Autopsy currently has a limitation when searching for regular expressions, that spaces are not supported.  It’s not a problem for Email addresses and URLs, but becomes an issue phone numbers, account numbers, etc.  This limitation comes from using an indexed search engine (since spaces are used to break text into tokens).
> >
> > We’re looking at ways of solving that and need some guidance.
> >
> > If you write your own regular expressions, can you please let me know and share what they look like.  We want to know how complex the expressions are that people use in real life.
> >
> > Thanks!
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