@Test
public void findStatesWithPopulationOver10MillionAggregationExample() {
/*
//complex mongodb aggregation framework example from
http://docs.mongodb.org/manual/tutorial/aggregation-examples/#largest-and-smallest-cities-by-state
db.zipcodes.aggregate(
{
$group: {
_id:"$state",
totalPop:{ $sum:"$pop"}
}
},
{
$sort: { _id: 1, "totalPop": 1 }
},
{
$match: {
totalPop: { $gte:10*1000*1000 }
}
}
)
*/
TypedAggregation<ZipInfo> agg =
newAggregation(
ZipInfo.class, //
group("state") //
.sum("population")
.as("totalPop"), //
sort(ASC, previousOperation(), "totalPop"), //
match(where("totalPop").gte(10 * 1000 * 1000)) //
);
assertThat(agg, is(notNullValue()));
assertThat(agg.toString(), is(notNullValue()));
AggregationResults<StateStats> result = mongoTemplate.aggregate(agg, StateStats.class);
assertThat(result, is(notNullValue()));
assertThat(result.getMappedResults(), is(notNullValue()));
assertThat(result.getMappedResults().size(), is(7));
StateStats stateStats = result.getMappedResults().get(0);
assertThat(stateStats, is(notNullValue()));
assertThat(stateStats.id, is("CA"));
assertThat(stateStats.state, is(nullValue()));
assertThat(stateStats.totalPopulation, is(29760021));
}
/**
* @see
* http://docs.mongodb.org/manual/tutorial/aggregation-examples/#return-the-five-most-common-likes
*/
@Test
public void returnFiveMostCommonLikesAggregationFrameworkExample() {
createUserWithLikesDocuments();
/*
...
$group: {
_id:"$like",
number:{ $sum:1}
}
...
*/
TypedAggregation<UserWithLikes> agg =
newAggregation(
UserWithLikes.class, //
unwind("likes"), //
group("likes").count().as("number"), //
sort(DESC, "number"), //
limit(5), //
sort(ASC, previousOperation()) //
);
assertThat(agg, is(notNullValue()));
assertThat(agg.toString(), is(notNullValue()));
AggregationResults<LikeStats> result = mongoTemplate.aggregate(agg, LikeStats.class);
assertThat(result, is(notNullValue()));
assertThat(result.getMappedResults(), is(notNullValue()));
assertThat(result.getMappedResults().size(), is(5));
assertLikeStats(result.getMappedResults().get(0), "a", 4);
assertLikeStats(result.getMappedResults().get(1), "b", 2);
assertLikeStats(result.getMappedResults().get(2), "c", 4);
assertLikeStats(result.getMappedResults().get(3), "d", 2);
assertLikeStats(result.getMappedResults().get(4), "e", 3);
}
@Test
public void complexAggregationFrameworkUsageLargestAndSmallestCitiesByState() {
/*
//complex mongodb aggregation framework example from http://docs.mongodb.org/manual/tutorial/aggregation-examples/#largest-and-smallest-cities-by-state
db.zipInfo.aggregate(
{
$group: {
_id: {
state: '$state',
city: '$city'
},
pop: {
$sum: '$pop'
}
}
},
{
$sort: {
pop: 1,
'_id.state': 1,
'_id.city': 1
}
},
{
$group: {
_id: '$_id.state',
biggestCity: {
$last: '$_id.city'
},
biggestPop: {
$last: '$pop'
},
smallestCity: {
$first: '$_id.city'
},
smallestPop: {
$first: '$pop'
}
}
},
{
$project: {
_id: 0,
state: '$_id',
biggestCity: {
name: '$biggestCity',
pop: '$biggestPop'
},
smallestCity: {
name: '$smallestCity',
pop: '$smallestPop'
}
}
},
{
$sort: {
state: 1
}
}
)
*/
TypedAggregation<ZipInfo> aggregation =
newAggregation(
ZipInfo.class, //
group("state", "city").sum("population").as("pop"), //
sort(ASC, "pop", "state", "city"), //
group("state") //
.last("city")
.as("biggestCity") //
.last("pop")
.as("biggestPop") //
.first("city")
.as("smallestCity") //
.first("pop")
.as("smallestPop"), //
project() //
.and("state")
.previousOperation() //
.and("biggestCity")
.nested(bind("name", "biggestCity").and("population", "biggestPop")) //
.and("smallestCity")
.nested(bind("name", "smallestCity").and("population", "smallestPop")), //
sort(ASC, "state") //
);
assertThat(aggregation, is(notNullValue()));
assertThat(aggregation.toString(), is(notNullValue()));
AggregationResults<ZipInfoStats> result =
mongoTemplate.aggregate(aggregation, ZipInfoStats.class);
assertThat(result, is(notNullValue()));
assertThat(result.getMappedResults(), is(notNullValue()));
assertThat(result.getMappedResults().size(), is(51));
ZipInfoStats firstZipInfoStats = result.getMappedResults().get(0);
assertThat(firstZipInfoStats, is(notNullValue()));
assertThat(firstZipInfoStats.id, is(nullValue()));
assertThat(firstZipInfoStats.state, is("AK"));
assertThat(firstZipInfoStats.smallestCity, is(notNullValue()));
assertThat(firstZipInfoStats.smallestCity.name, is("CHEVAK"));
assertThat(firstZipInfoStats.smallestCity.population, is(0));
assertThat(firstZipInfoStats.biggestCity, is(notNullValue()));
assertThat(firstZipInfoStats.biggestCity.name, is("ANCHORAGE"));
assertThat(firstZipInfoStats.biggestCity.population, is(183987));
ZipInfoStats lastZipInfoStats = result.getMappedResults().get(50);
assertThat(lastZipInfoStats, is(notNullValue()));
assertThat(lastZipInfoStats.id, is(nullValue()));
assertThat(lastZipInfoStats.state, is("WY"));
assertThat(lastZipInfoStats.smallestCity, is(notNullValue()));
assertThat(lastZipInfoStats.smallestCity.name, is("LOST SPRINGS"));
assertThat(lastZipInfoStats.smallestCity.population, is(6));
assertThat(lastZipInfoStats.biggestCity, is(notNullValue()));
assertThat(lastZipInfoStats.biggestCity.name, is("CHEYENNE"));
assertThat(lastZipInfoStats.biggestCity.population, is(70185));
}
