CompleteSearch

Quick Intro

Follow these steps to checkout the CompleteSearch code from our SVN, compile it, build an index, run a server on that index, and ask queries to that server via HTTP. Don't be afraid, it's easy. If you have questions, send an email to Hannah Bast <bast@informatik.uni-freiburg.de>.

0. Get source code

svn checkout
http://ad-svn.informatik.uni-freiburg.de/completesearch/codebase
Username: [ask us]
Password: [ask us]

Third-party code you need to install:

sudo apt-get install libboost-dev        # Boost (http://www.boost.org)
sudo apt-get install libsparsehash-dev   # Google Hash Map (http://code.google.com/p/google-sparsehash)
sudo apt-get install libgtest-dev        # Google Test (http://code.google.com/p/googletest)
sudo apt-get install libstxxl-dev        # STXXL (http://stxxl.sourceforge.net)

1. Compile

Edit the Makefile and adjust CS_CODE_DIR and STXXL_CONFIG, then do:

make build-all

This will build three binaries: buildIndex, buildDocsDB, startCompletionServer.

If you call any of these binaries without parameters you will get usage info with all the available options.

2. Input (to be produced by a suitable parser)

Input 1: a file <base-name>.docs, with lines of the form

<doc id><TAB>u:<url of document><TAB>t:<title of document><TAB>H:<raw
text of document>

This file must be sorted so that sort -c -k1,1n does not complain.

Here is a simple example (the multi-spaces are all TABs)

1       u:http://some.url.wherever/foo  t:First document        H: This is a stupid document.
2       u:http://some.url.wherever/bar  t:Second document       H: This is a boring document.

Ínput 1: a file <base-name>.words, with lines of the form

<word><TAB><doc id><TAB><score><TAB><position>

This file must be sorted such that sort -c -k1,1 -k2,2n -k4,4n does not complain.

Here is a simple example, matching the example above (again multi-spaces are all TABs):

a         1      1      5
a         2      1      5
boring    2      1      6
document  1      2      2
document  1      1      7
document  2      2      2
document  2      1      7
first     1      1      1
is        1      1      4
is        2      1      4
second    2      1      1
stupid    1      1      6
this      1      1      3
this      2      1      3

3. Build the word index

buildIndex HYB <base-name>.words

This produces the (binary) index file <base-name>.hybrid. It enables fast processing of the powerful query language offered by CompleteSearch (including full-text search, prefix search and completion, synonym search, error-tolerant search, etc.).

buildIndex also produces the file <base-name>.vocabulary that provides the mapping from word ids to words. This is an ASCII file, you can just look at it.

Note that by default, the HYB index is built with block of fixed sizes. It is more efficient though to pass it an explicit list of block boundaries (-B option). TODO: say something about this here, it's actually quite easy.

4. Build the doc index

buildDocsDB <name>.docs

This produces the (binar) file <base-name>.docs.DB which provides an efficient mapping from doc ids to documents. This is needed if you want to show excerpts / snippets from documents matching the query (which is almost always the case).

5. Start server

startCompletionServer -Z <base-name>.hybrid

This starts the server. If you run it without argument, it prints usage information and shows you the (very many) command line options. The -Z argument lets the server run in the foreground, and output everything to the console, which is convenient for testing. The default mode is to run as a background process and write all output to a log file.

6. Queries

The server listens on the port you specified in step 6 (8888 by default), and speaks HTTP. For example:

curl "http://localhost:8888/?q=die*&h=1&c=3"

This will return the result as an XML, which should be self-explanatory.

Here is the list of parameters which you may pass along with the query (q=...)

• h : number of hits
• c : number of completions (of last query word, if you put a * behind it)
• f : send hits starting from this one (default: 0)
• en : number of excerpts per hit
• er : excerpt radius (number of words to the left and right of matching words)
• rd : how to rank the documents (0 = by score, 1 = by doc id, 2 = by word id, append a or d for ascending or descending)
• rw : how to rank the words (0 = by score, 1 = by doc count, 2 = by occurrence count, 3 = by word id, 4 = by doc id, append a or d as above)
• s : how to aggregate scores (expert option, ignore for the moment)
• format : one of xml, json, jsonp. Return result in that format.

More detailed information

Here is the link to the old Wiki from the MPII. This contains lots of detailed information, but most of this is really for developers of the code. For building applications, the above should be enough.