blob: 86981951669b49b2a3075502f1a899c7aed2deb6 [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 : Test that left-outer-join may use two available indexes, one for primary index in prob subtree and another for secondary rtree index in index subtree.
* Issue : 730, 741
* Expected Res : Success
* Date : 8th May 2014
*/
drop dataverse test if exists;
create dataverse test;
use test;
create type test.TwitterUserType as
closed {
`screen-name` : string,
lang : string,
`friends-count` : int32,
`statuses-count` : int32,
name : string,
`followers-count` : int32
}
create type test.TweetMessageType as
{
tweetid : int64,
user : TwitterUserType,
`send-time` : datetime,
`referred-topics` : {{string}},
`message-text` : string,
countA : int32,
countB : int32
}
create dataset TweetMessages(TweetMessageType) primary key tweetid;
create index twmSndLocIx on TweetMessages (`sender-location`:point) type rtree enforced;
create index msgCountAIx on TweetMessages (countA) type btree;
create index msgCountBIx on TweetMessages (countB) type btree;
create index msgTextIx on TweetMessages (`message-text`) type keyword;
write output to asterix_nc1:"rttest/rtree-index-join_leftouterjoin-probe-pidx-with-join-rtree-sidx_01.adm"
select element {'tweetid1':t1.tweetid,'loc1':t1.`sender-location`,'nearby-message':(
select element {'tweetid2':t2.tweetid,'loc2':t2.`sender-location`}
from TweetMessages as t2
where test.`spatial-intersect`(t2.`sender-location`,n)
order by t2.tweetid
)}
from TweetMessages as t1
with n as test.`create-circle`(t1.`sender-location`,0.5)
where (t1.tweetid < test.int64('10'))
order by t1.tweetid
;