本文介绍了如何在Spring Data MongoDB中实现聚合查询？的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我是Spring data MongoDB的新手，我正在尝试用Spring data MongoDB用Java实现聚合查询。我已尝试从此问题进行搜索，并使用MongoTemplate解决了它，但仍未找到结果。
我的数据格式：
[{
"_id" : ObjectId("5e1aea6c275360baf96bac29"),
"title" : "postim",
"upvotesBy" : [
"5e18b4c12753608718dfa007",
"5e19ac0f5161a4994ded1f35"
],
"file" : "test",
"description" : "description",
"postedBy" : "5e18b4c12753608718dfa007",
"createdAt" : ISODate("2020-01-12T09:44:12.119+0000"),
"_class" : "com.socialnetwork.post.Post"
},
{
"_id" : ObjectId("5e1aeaf8275360bb4bb47325"),
"title" : "postim2",
"upvotesBy" : [
"5e18b4c12753608718dfa007",
"5e19ac0f5161a4994ded1f35"
],
"file" : "test2",
"description" : "description2",
"postedBy" : "5e18b4c12753608718dfa007",
"createdAt" : ISODate("2020-01-12T09:46:32.909+0000"),
"_class" : "com.socialnetwork.post.Post"
}]
我的问题：
db.post.aggregate([
{
$match: {}
},
{
$lookup: {
from: "users",
localField: "postedBy",
foreignField: "_id",
as: "user"
}
},
{
$group: {
_id: {
username: "$user.name",
title: "$title",
description: "$description",
upvotes: { $size: "$upvotesBy" },
upvotesBy: "$upvotesBy",
isUpvoted: { $in: [req.query.userId, "$upvotesBy"] },
isPinned: {
$cond: {
if: { $gte: [{ $size: "$upvotesBy" }, 3] },
then: true,
else: false
}
},
file: "$file",
createdAt: {
$dateToString: {
format: "%H:%M %d-%m-%Y",
timezone: "+01",
date: "$createdAt"
}
},
id: "$_id"
}
}
},
{ $sort: { "_id.isPinned": -1, "_id.createdAt": -1 } }
])
这是我在我的Java后端中使用的查询，我可以用Mongoose很容易地完成这项工作。然而，我对它的Java实现遇到了一些困难。
private LookupOperation getLookupOperation() {
return LookupOperation.newLookup().from("user")
.localField("postedBy")
.foreignField("_id")
.as("user");
}
@Override
public List<PostSummary> aggregate() {
LookupOperation lookupOperation = getLookupOperation();
return mongoTemplate.aggregate(Aggregation.newAggregation(lookupOperation, Aggregation.group("id")
.addToSet("user.name").as("username")
.addToSet("title").as("title")
.addToSet("description").as("description")
.addToSet("id").as("id")
.push("upvotesBy").as("upvotesBy")
.addToSet("file").as("file")
.addToSet("createdAt").as("createdAt")
), Post.class, PostSummary.class).getMappedResults();
}
当我尝试运行此命令时，收到以下错误：
"Cannot convert [] of type class java.util.ArrayList into an instance of class java.lang.Object! Implement a custom Converter<class java.util.ArrayList, class java.lang.Object> and register it with the CustomConversions. Parent object was: com.socialnetwork.post.PostSummary@7159d908"
当我从组聚合中删除.addToSet("user.name").as("username")时，我也从.push("upvotesBy").as("upvotesBy")收到错误，因为它无法转换[] of type class java.util.ArrayList into an instance of class java.lang.String
Post类和PostSummary类的实现也很简单：
Post.java：
@Document
public class Post {
@Id
private String id;
private String title;
private List<String> upvotesBy;
private String file;
private String description;
private String postedBy;
private Date createdAt = new Date();
// ... Getters and Setters for each field
}
PostSummary.java：
public class PostSummary {
private String username;
private String title;
private String description;
private List<String> upvotesBy;
private String file;
private String createdAt;
private String id;
//... Getters and Setters for the class
}
我还需要实现查询的isUpvoted和isPinned部分，但了解如何处理第一个问题将是一个很好的开始。
编辑：我想要的输出：
[
{
"username" : "user1",
"title" : "postim2",
"upvotesBy" : [
"5e18b4c12753608718dfa007",
"5e19ac0f5161a4994ded1f35"
],
"file": "file1",
id: "5e18b4c12753608718dber01"
... Other fields of the original post
},
{
"username" : "user2",
"title" : "postim2",
"upvotesBy" : [
"5e18b4c12753608718dfa007",
"5e19ac0f5161a4994ded1f35"
],
id: "5e18b4c12753608718dber02",
"file": "file2",
... Other fields of the original post
}
]
因此，从查找操作中，我只需要获取用户名。
推荐答案
开始吧
我们需要更新您的聚合才能使其工作。
错误：
users的_id为ObjectId类型，但您在帖子中存储为String，因此$lookup应改为Uncorrelated sub-queries- 我们将
$group替换为更适合的‘$addFields’ - 我们添加作为最后阶段的
$project运算符，以排除所有未使用的字段。
db.post.aggregate([
{
$match: {}
},
{
$lookup: {
from: "users",
let: {
postedBy: "$postedBy"
},
pipeline: [
{
$match: {
$expr: {
$eq: [
{
"$toString": "$_id"
},
"$$postedBy"
]
}
}
}
],
as: "user"
}
},
{
$unwind: "$user"
},
{
$addFields: {
id: {
$toString: "$_id"
},
username: "$user.name",
upvotes: {
$size: "$upvotesBy"
},
isUpvoted: {
$in: [
"5e18b4c12753608718dfa007",
"$upvotesBy"
]
},
isPinned: {
$cond: [
{
$gte: [
{
$size: "$upvotesBy"
},
3
]
},
true,
false
]
},
createdAt: {
$dateToString: {
format: "%H:%M %d-%m-%Y",
timezone: "+01",
date: "$createdAt"
}
}
}
},
{
$sort: {
"isPinned": -1,
"createdAt": -1
}
},
{
$project: {
_id: 0,
user: 0,
upvotesBy: 0,
_class: 0
}
}
])
现在，我们将该查询转换为Spring-data语法。
Java实现
package postman;
import static org.springframework.data.mongodb.core.aggregation.Aggregation.match;
import static org.springframework.data.mongodb.core.aggregation.Aggregation.project;
import static org.springframework.data.mongodb.core.aggregation.Aggregation.sort;
import static org.springframework.data.mongodb.core.aggregation.Aggregation.unwind;
import java.util.Arrays;
import java.util.List;
import org.bson.Document;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.domain.Sort.Direction;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.aggregation.Aggregation;
import org.springframework.data.mongodb.core.aggregation.AggregationOperation;
import org.springframework.data.mongodb.core.aggregation.AggregationOperationContext;
import org.springframework.data.mongodb.core.query.Criteria;
import org.springframework.stereotype.Service;
@Service
public class PostmanService {
@Autowired
private MongoTemplate mongoTemplate;
public List<PostSummary> find(String userId){
Aggregation aggregation = Aggregation.newAggregation(
match(new Criteria()),
//lookup("users", "postedBy", "_id", "user")
new AggregationOperation() {
@Override
public Document toDocument(AggregationOperationContext context) {
return new Document("$lookup",
new Document("from", "users")
.append("let", new Document("postedBy", "$postedBy"))
.append("pipeline", Arrays.asList(
new Document("$match",
new Document("$expr",
new Document("$eq", Arrays.asList(
new Document("$toString", "$_id"),
"$$postedBy"
))))))
.append("as", "user"));
}
},
unwind("$user"),
new AggregationOperation() {
@Override
public Document toDocument(AggregationOperationContext context) {
return new Document("$addFields",
new Document("id", new Document("$toString", "$_id"))
.append("username", "$user.name")
.append("upvotes", new Document("$size", "$upvotesBy"))
.append("isUpvoted", new Document("$in", Arrays.asList(userId, "$upvotesBy")))
.append("isPinned", new Document("$cond",
Arrays.asList(new Document("$gte",
Arrays.asList(new Document("$size", "$upvotesBy"), 3)), Boolean.TRUE, Boolean.FALSE)))
.append("createdAt", new Document("$dateToString",
new Document("format", "%H:%M %d-%m-%Y")
.append("timezone", "+01")
.append("date", "$createdAt")
)));
}
},
sort(Direction.DESC, "isPinned", "createdAt"),
project().andExclude("user", "_class")
);
System.out.println("Aggregation: " + aggregation.toString());
return mongoTemplate.aggregate(aggregation, mongoTemplate.getCollectionName(Post.class), PostSummary.class).getMappedResults();
}
}
现在，我们调用聚合管道：
List<PostSummary> l = postmanService.find("5e18b4c12753608718dfa007");
for(PostSummary post: l) {
ObjectWriter ow = new ObjectMapper().writer().withDefaultPrettyPrinter();
System.out.println(ow.writeValueAsString(post));
}
2020-01-12 16:15:22.043 INFO 11148 --- [ main] o.s.b.w.embedded.tomcat.TomcatWebServer : Tomcat started on port(s): 8080 (http) with context path ''
2020-01-12 16:15:22.047 INFO 11148 --- [ main] Postman.PostmanApplication : Started PostmanApplication in 4.602 seconds (JVM running for 5.301)
Aggregation: { "aggregate" : "__collection__", "pipeline" : [{ "$match" : {}}, { "$lookup" : { "from" : "users", "let" : { "postedBy" : "$postedBy"}, "pipeline" : [{ "$match" : { "$expr" : { "$eq" : [{ "$toString" : "$_id"}, "$$postedBy"]}}}], "as" : "user"}}, { "$unwind" : "$user"}, { "$addFields" : { "id" : { "$toString" : "$_id"}, "username" : "$user.name", "upvotes" : { "$size" : "$upvotesBy"}, "isUpvoted" : { "$in" : ["5e18b4c12753608718dfa007", "$upvotesBy"]}, "isPinned" : { "$cond" : [{ "$gte" : [{ "$size" : "$upvotesBy"}, 3]}, true, false]}, "createdAt" : { "$dateToString" : { "format" : "%H:%M %d-%m-%Y", "timezone" : "+01", "date" : "$createdAt"}}}}, { "$sort" : { "isPinned" : -1, "createdAt" : -1}}, { "$project" : { "user" : 0, "_class" : 0}}]}
2020-01-12 16:15:22.161 INFO 11148 --- [ main] org.mongodb.driver.connection : Opened connection [connectionId{localValue:2, serverValue:277}] to localhost:27017
{
"username" : "user1",
"title" : "postim2",
"description" : "description2",
"upvotesBy" : [ "5e18b4c12753608718dfa007", "5e19ac0f5161a4994ded1f35" ],
"file" : "test2",
"createdAt" : "10:46 12-01-2020",
"id" : "5e1aeaf8275360bb4bb47325"
}
{
"username" : "user1",
"title" : "postim",
"description" : "description",
"upvotesBy" : [ "5e18b4c12753608718dfa007", "5e19ac0f5161a4994ded1f35" ],
"file" : "test",
"createdAt" : "10:44 12-01-2020",
"id" : "5e1aea6c275360baf96bac29"
}
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