/*
 * Description    : Fuzzy joins two datasets, DBLP and CSX, based on ~= using Jaccard of their titles' word tokens.
 *                  DBLP has a keyword index on title, and we expect the join to be transformed into an indexed nested-loop join.
 *                  We expect the top-level equi join introduced because of surrogate optimization to be removed, since it is not necessary.
 * Success        : Yes
 */

drop dataverse test if exists;
create dataverse test;
use dataverse test;

create type DBLPType as closed {
  id: int32, 
  dblpid: string,
  title: string,
  authors: string,
  misc: string
}

create type CSXType as closed {
  id: int32, 
  csxid: string,
  title: string,
  authors: string,
  misc: string
}

create dataset DBLP(DBLPType) partitioned by key id;

create dataset CSX(CSXType) partitioned by key id;

create index keyword_index on DBLP(title) type keyword;

write output to nc1:"rttest/inverted-index-join-noeqjoin_word-fuzzyeq-jaccard.adm";

set simfunction 'jaccard';
set simthreshold '0.5f';

for $a in dataset('DBLP')
for $b in dataset('CSX')
where word-tokens($a.title) ~= word-tokens($b.title) and $a.id < $b.id
return {"atitle": $a.title, "btitle": $b.title}