Terry: Tika has a horrible problem to deal with and it's approaching a miracle that it does so well ;)
Let's take a PDF file. Which vendor's version? From what _decade_? Did that vendor adhere to the spec? Every spec has gray areas so even good-faith efforts can result in some version/vendor behaving slightly differently from the other. And what about Word .vs. PDF? One might have "last_modified" and the other might have "last_edited" to mean the same thing. You mentioned that you're aware of this, you can make it more useful if you have finer-grained control over the ETL process. You say "As I understand it, Tika is integrated with Solr" which is correct, you're talking about the "Extracting Request Handler". However that has a couple of important caveats: 1> It does the best it can. But Tika has a _lot_ of tuning options that allow you to get down-and-dirty with the data you're indexing. You mentioned that precision is important. You can do some interesting things with extracting specific fields from specific kinds of documents and making use of them. The "last_modified" and "last_edited" fields above are an example. 2> It loads the work on a single Solr node. So the very expensive process of extracting data from the semi-structure document is all on the Solr node. If you use Tika in a client-side program you can parallelize the extraction and get through your indexing much more quickly. 3> Tika can occasionally get its knickers in a knot over some particular document. That'll also bring down the Solr instance. Here's a blog that can get you started doing client-side parsing, ignore the RDBMS bits. https://lucidworks.com/2012/02/14/indexing-with-solrj/ I'll leave Tim to talk about tika-eval ;) But the general problem is that the extraction process can result in garbage, lots of garbage. OCR is particularly prone to nonsense. PDFs can be tricky, there's this spacing parameter that, depending on it's setting can render e r i c k as 5 separate letters or my name. Hey, you asked! Don't complain about long answers ;) Best, Erick On Tue, Apr 17, 2018 at 1:50 PM, Terry Steichen <te...@net-frame.com> wrote: > Hi Timothy, > > As I understand it, Tika is integrated with Solr. All my indexed > documents declare that they've been parsed by tika. For the eml files > it's: |org.apache.tika.parser.mail.RFC822Parser Word docs show they > were parsed by ||org.apache.tika.parser.microsoft.ooxml.OOXMLParser PDF > files show: ||org.apache.tika.parser.pdf.PDFParser| > > || > > || > > What do you mean by improving the output with "tika-eval?" I confess I > don't completely understand how documents should be prepared for > indexing. But with the eml docs, solr/tika seems to properly pull out > things like date, subject, to and from. Other (so-called 'rich text') > documents (like pdfs and Word-type), the metadata is not so useful, but > on the other hand, there's not much consistent structure to the > documents I have to deal with. > > I may be missing something - am I? > > Regards, > > Terry > > > On 04/17/2018 09:38 AM, Allison, Timothy B. wrote: >> +1 to Charlie's guidance. >> >> And... >> >>> 60,000 documents, mostly pdfs and emails. >>> However, there's a premium on precision (and recall) in searches. >> Please, oh, please, no matter what you're using for content/text extraction >> and/or OCR, run tika-eval[1] on the output to ensure that that you are >> getting mostly language-y content out of your documents. Ping us on the >> Tika user's list if you have any questions. >> >> Bad text, bad search. 😊 >> >> [1] https://wiki.apache.org/tika/TikaEval >> >> -----Original Message----- >> From: Charlie Hull [mailto:char...@flax.co.uk] >> Sent: Tuesday, April 17, 2018 4:17 AM >> To: solr-user@lucene.apache.org >> Subject: Re: Specialized Solr Application >> >> On 16/04/2018 19:48, Terry Steichen wrote: >>> I have from time-to-time posted questions to this list (and received >>> very prompt and helpful responses). But it seems that many of you are >>> operating in a very different space from me. The problems (and >>> lessons-learned) which I encounter are often very different from those >>> that are reflected in exchanges with most other participants. >> Hi Terry, >> >> Sounds like a fascinating use case. We have some similar clients - small >> scale law firms and publishers - who have taken advantage of Solr. >> >> One thing I would encourage you to do is to blog and/or talk about what >> you've built. Lucene Revolution is worth applying to talk at and if you do >> manage to get accepted - or if you go anyway - you'll meet lots of others >> with similar challenges and come away with a huge amount of useful >> information and contacts. Otherwise there are lots of smaller Meetup events >> (we run the London, UK one). >> >> Don't assume just because some people here are describing their 350 billion >> document learning-to-rank clustered monster that the small applications >> don't matter - they really do, and the fact that they're possible to build >> at all is a testament to the open source model and how we share information >> and tips. >> >> Cheers >> >> Charlie >>> So I thought it would be useful to describe what I'm about, and see if >>> there are others out there with similar implementations (or interest >>> in moving in that direction). A sort of pay-forward. >>> >>> We (the Lakota Peoples Law Office) are a small public interest, pro >>> bono law firm actively engaged in defending Native American North >>> Dakota Water Protector clients against (ridiculously excessive) criminal >>> charges. >>> >>> I have a small Solr (6.6.0) implementation - just one shard. I'm >>> using the cloud mode mainly to be able to implement access controls. >>> The server is an ordinary (2.5GHz) laptop running Ubuntu 16.04 with >>> 8GB of RAM and 4 cpu processors. We presently have 8 collections with >>> a total of about 60,000 documents, mostly pdfs and emails. The >>> indexed documents are partly our own files and partly those we obtain >>> through legal discovery (which, surprisingly, is allowed in ND for >>> criminal cases). We only have a few users (our lawyers and a couple >>> of researchers mostly), so traffic is minimal. However, there's a >>> premium on precision (and recall) in searches. >>> >>> The document repository is local to the server. I piggyback on the >>> embedded Jetty httpd in order to serve files (selected from the >>> hitlists). I just use a symbolic link to tie the repository to >>> Solr/Jetty's "webapp" subdirectory. >>> >>> We provide remote access via ssh with port forwarding. It provides >>> very snappy performance, with fully encrypted links. Appears quite stable. >>> >>> I've had some bizarre behavior apparently caused by an interaction >>> between repository permissions, solr permissions and the ssh link. I >>> seem "solved" for the moment, but time will tell for how long. >>> >>> If there are any folks out there who have similar requirements, I'd be >>> more than happy to share the insights I've gained and problems I've >>> encountered and (I think) overcome. There are so many unique parts of >>> this small scale, specialized application (many dimensions of which >>> are not strictly internal to Solr) that it probably won't be >>> appreciated to dump them on this (excellent) Solr list. So, if you >>> encounter problems peculiar to this kind of setup, we can perhaps help >>> handle them off-list (although if they have more general Solr >>> application, we should, of course, post them to the list). >>> >>> Terry Steichen >>> >> >> -- >> Charlie Hull >> Flax - Open Source Enterprise Search >> >> tel/fax: +44 (0)8700 118334 >> mobile: +44 (0)7767 825828 >> web: www.flax.co.uk >> >
