/*
 * Description    : Fuzzy joins two datasets, Customer and Customer2, based on the similarity-jaccard function of their interest lists.
 *                  Customers has a keyword index on interests, 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 AddressType as closed {
  number: int32, 
  street: string,
  city: string
}

create type CustomerType as closed {
  cid: int32, 
  name: string,
  age: int32?,
  address: AddressType?,
  interests: [string],
  children: [ { name: string, age: int32? } ]
}

create dataset Customers(CustomerType) partitioned by key cid;
  
create dataset Customers2(CustomerType) partitioned by key cid;

create index interests_index on Customers(interests) type keyword;

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

for $a in dataset('Customers')
for $b in dataset('Customers2')
where /*+ indexnl */ similarity-jaccard($a.interests, $b.interests) >= 0.7f and $a.cid < $b.cid
return {"ainterests": $a.interests, "binterests": $b.interests}