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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 : Fuzzy joins two datasets, Customers and Customers2, based on the edit-distance function of their names.
* Customers has a 3-gram index on name, and we expect the join to be transformed into an indexed nested-loop join.
* We test the inlining of variables that enable the select to be pushed into the join for subsequent optimization with an index.
* Success : Yes
*/
drop dataverse test if exists;
create dataverse test;
use test;
create type test.AddressType as
{
number : int64,
street : string,
city : string
}
create type test.CustomerNestedType as
closed {
cid : int64,
name : string,
age : int64?,
address : AddressType?,
interests : [string],
children : [{
name : string,
age : int64?
}
]
}
create type test.CustomerType as
closed {
nested : CustomerNestedType
}
create dataset Customerstmp(CustomerNestedType) primary key cid;
create dataset Customers2tmp(CustomerNestedType) primary key cid;
create dataset Customers(CustomerType) primary key nested.cid;
create dataset Customers2(CustomerType) primary key nested.cid;