The repository contains the code that accompanies the blog post Teaching An Old Dog a new Trick.
olddog is build using maven:
mvn clean package appassembler:assemble
OldDog takes a Lucene index as input, for example as created by the Anserini project. The Robust 04 collection can be indexed as explained on this Anserini page.
After creating the index, the CSV files representing the database tables can be created issuing the following command:
nohup target/appassembler/bin/nl.ru.convert.Convert -index path/to/index -docs /tmp/docs.csv -dict /tmp/dict.csv -terms /tmp/terms.csv
This creates multiple files that represent the columns of the docs, dict and terms tables as described in the blog post.
The column store relational database MonetDB can load
these files using the COPY INTO command.
After this final step it is possible issue the query described in the post:
WITH qterms AS (SELECT termid, docid, df FROM terms
WHERE termid IN (10575, 1285, 191)),
subscores AS (SELECT docs.docid, len, term_tf.termid,
tf, df, (log((528155-df+0.5)/(df+0.5))*((tf*(1.2+1)/
(tf+1.2*(1-0.75+0.75*(len/188.33)))))) AS subscore
FROM (SELECT termid, docid, df AS tf FROM qterms) AS term_tf
JOIN (SELECT docid FROM qterms
GROUP BY docid HAVING COUNT(distinct termid) = 3)
AS cdocs ON term_tf.docid = cdocs.docid
JOIN docs ON term_tf.docid=docs.docid
JOIN dict ON term_tf.termid=dict.termid)
SELECT scores.docid, score FROM (SELECT docid, sum(subscore) AS score
FROM subscores GROUP BY docid) AS scores JOIN docs ON
scores.docid=docs.docid ORDER BY score DESC;