Spring Data MongoDB不存在切换错误

如何解决Spring Data MongoDB不存在切换错误

我在春季使用MongoDB在我的一项服务后面运行了aggreagaton逻辑。

聚合逻辑如下：

MatchOperation dateMatchOperation = Aggregation.match(
    Criteria.
            where("date").
            gte(new Date(startStamp)).lte(new Date(endStamp)));

MatchOperation propertyMatchOperation = Aggregation.match(
    Criteria.
            where("abc1").is(abcVal1)
            .and("abc2").is(abcVal2)
            .and("abc3").is(abcVal3)
            .and("abc4").is(abcVal4)
            .and("abc5").is(abcVal5)
);

List<Date> dates = new ArrayList<>();
//Create appropriate interval arraylist which will be passed to mongo
for (int i = 0; i < (endStamp - startStamp)/aggregationInterval; i ++) {
dates.add(new Date(startStamp + i * aggregationInterval));
}


BucketOperation bucketOperation = Aggregation.bucket("date").withBoundaries(dates.toArray())
    .andOutput(AccumulatorOperators.Sum.sumOf(aggregationInput)).as("value")
    .andOutput(AccumulatorOperators.Min.minOf("date")).as("from")
    .andOutput(AccumulatorOperators.Max.maxOf("date")).as("to");


AggregationOptions aggregationOptions = AggregationOptions.builder().allowDiskUse(true).build();
AggregationResults<MetricAggregationResult> aggregationResults = mongoTemplate.aggregate(
    Aggregation.newAggregation(dateMatchOperation,propertyMatchOperation,bucketOperation)
        .withOptions(aggregationOptions),"mongocollectionname",MetricAggregationResult.class);

我正在用450万个文档对它进行测试。当aggregationInterval很小并且arraylist中有很多元素时，它可以正常工作，但是在某些时候，逐渐增加聚合间隔的时间我注意到，在某个点聚合之后会引发以下错误：

com.mongodb.MongoCommandException: Command failed with error 40066: '$switch could not find a matching branch for an input,and no default was specified.'

这很奇怪，因为我没有在逻辑中使用任何$ switch聚合，例如 AggregationOptions ，我以为mongo aggregation was hitting it's 100MB limit并且允许使用磁盘。

这时我束手无策，我不知道是什么引起了问题（我在StackOverflow的各处搜索$ switch错误，但是我找不到任何东西，因为所有询问的人都在代码中使用$ switch在某种程度上），但我相当有信心这是蒙哥队所错过的。

解决方法

Use BucketAutoOperation

 BucketAutoOperation bucketAutoOperation = Aggregation.bucketAuto("date",2)
                .andOutput(AccumulatorOperators.Sum.sumOf(aggregationInput)).as("value")
                .andOutput(AccumulatorOperators.Min.minOf("date")).as("from")
                .andOutput(AccumulatorOperators.Max.maxOf("date")).as("to");

,

To use a bucket operation,we specify the following:

groupBy: the field that the boundaries will apply to. This field must be numeric or a date field.
boundaries: an array of boundary points. Documents which have a groupBy field falling between two elements in the array go into that bucket. The between test here is half-open,so the first point is inclusive,second point is exclusive,which is the behavior developers would expect
default: any documents in the pipeline which don’t go into one of the buckets will go into default. This is required. Using a match operation in the pipeline before the bucket operation will remove documents which shouldn’t be processed.
output: an aggregation expression to generate the output document for each bucket


IN the above code,we missed specifying default. 

final BucketOperation bucketOperation = Aggregation.bucket("date").
                withBoundaries(now.minus(10,ChronoUnit.DAYS),now.minus(9,DAYS),now.minus(8,now.minus(7,now.minus(6,now.minus(5,now.minus(4,now.minus(3,now.minus(2,now.minus(1,now.minus(0,DAYS)).
                withDefaultBucket("defaultBucket").
                andOutput(countingExpression).as("count");

请参考以下链接： https://chiralsoftware.com/idea/spring-data-aggregation-operations