blob: 19ec44fd5aa7c499ce4a7a61cd2f6b1e8ddb58f2 [file] [log] [blame]
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* 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 : Fuzzy self joins a dataset, Customers, based on the similarity-jaccard-check function of its interest sets.
* Customers has a keyword index on interests, and we expect the join to be transformed into an indexed nested-loop join.
* Success : Yes
*/
drop dataverse test if exists;
create dataverse test;
use test;
create type test.AddressType as
closed {
number : int32,
street : string,
city : string
}
create type test.CustomerType as
closed {
cid : int32,
name : string,
age : int32?,
address : AddressType?,
interests : {{string}},
children : [{
name : string,
age : int32?
}
]
}
create dataset Customers(CustomerType) primary key cid;
create index interests_index on Customers (interests) type keyword;
write output to asterix_nc1:"rttest/inverted-index-join_ulist-jaccard-check_03.adm"
select element {'arec':a,'brec':b}
from Customers as a,
Customers as b
where ( /*+ indexnl */ test.`similarity-jaccard-check`(a.interests,b.interests,0.700000f)[0] and (a.cid < b.cid))
;