blob: 92ab003f61836dc2e89285e05bd689e3d111b65a [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.
*/
drop dataverse events if exists;
create dataverse events;
use events;
create type events.AddressType as
closed {
street : string,
city : string,
zip : string
}
create type events.EventType as
closed {
name : string,
location : AddressType?,
organizers : {{{
name : string,
role : string
}
}},
sponsoring_sigs : [{
sig_name : string,
chapter_name : string
}
],
interest_keywords : {{string}},
price : double?,
start_time : datetime,
end_time : datetime
}
create nodegroup group1 if not exists on
asterix_nc1,
asterix_nc2
;
create dataset Event(EventType) primary key name on group1;
write output to asterix_nc1:"/tmp/q2.adm"
select element {'sig_name':sig_name,'total_count':sig_sponsorship_count,'chapter_breakdown':by_chapter}
from Event as event,
event.sponsoring_sigs as sponsor
with es as {'event':event,'sponsor':sponsor}
group by sponsor.sig_name as sig_name
with sig_sponsorship_count as count(es),
by_chapter as (
select element {'chapter_name':chapter_name,'escount':count(e)}
from es as e
group by e.sponsor.chapter_name as chapter_name
)
order by sig_sponsorship_count desc
limit 5
;