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/*
* Licensed to the Apache Software Foundation (ASF) under one
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* distributed with this work for additional information
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* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
/*
* Description : Tests whether an ngram_index is applied to optimize a selection query using the similarity-jaccard-check function on 3-gram tokens.
* Tests that the optimizer rule correctly drills through the let clauses.
* The index should be applied.
* Success : Yes
*/
drop dataverse test if exists;
create dataverse test;
use dataverse test;
set import-private-functions 'true';
create type DBLPType as closed {
id: int32,
dblpid: string,
title: string,
authors: string,
misc: string
}
create dataset DBLP(DBLPType) primary key id;
create index ngram_index on DBLP(title) type ngram(3);
write output to nc1:"rttest/inverted-index-complex_ngram-jaccard-check-multi-let.adm";
// This test is complex because we have three assigns to drill into.
for $paper in dataset('DBLP')
let $paper_tokens := gram-tokens($paper.title, 3, false)
let $query_tokens := gram-tokens("Transactions for Cooperative Environments", 3, false)
let $jacc := similarity-jaccard-check($paper_tokens, $query_tokens, 0.5f)
where $jacc[0]
return {"Paper": $paper_tokens, "Query": $query_tokens }