blob: 56b0e90da292925ae75bc368ff46c4b177ff9c2e [file] [log] [blame]
/*
* Licensed to the Apache Software Foundation (ASF) under one
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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
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* KIND, either express or implied. See the License for the
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*/
/*
* Description : Fuzzy joins two datasets, Customer and Customer2, based on the similarity-jaccard-check function of their 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.CustomerTypetmp as
closed {
cid : int32,
name : string,
age : int32?,
address : AddressType?,
interests : {{string}},
children : [{
name : string,
age : int32?
}
]
}
create type test.CustomerType as
closed {
nested : CustomerTypetmp
}
create dataset Customers(CustomerType) primary key nested.cid;
create dataset Customers2(CustomerType) primary key nested.cid;
create index interests_index on Customers (nested.interests) type keyword;
write output to asterix_nc1:"rttest/inverted-index-join_ulist-jaccard-check_01.adm"
select element {'arec':a,'brec':b}
from Customers as a,
Customers2 as b
where ( /*+ indexnl */ test.`similarity-jaccard-check`(a.nested.interests,b.nested.interests,0.700000f)[0] and (a.nested.cid < b.nested.cid))
;