springboot调用mongo

添加
删除
文档操作更新
简单聚合操作 count, distinct
普通查询
分组
分页查询
文件上传
文件下载

随便测试了一下，有问题请指出

pom.xml中添加依赖

<dependency>

    <groupId>org.springframework.boot</groupId>

    <artifactId>spring-boot-starter-data-mongodb</artifactId>

</dependency>

<dependency>

    <groupId>org.projectlombok</groupId>

    <artifactId>lombok</artifactId>

    <version>1.18.2</version>

</dependency>

application.yml中添加连接信息

spring:

  data:

    mongodb:

      uri: mongodb://xxx:27017/school

测试类

@SpringBootTest

@RunWith(SpringRunner.class)

public class MongoDBTest {

    @Autowired

    private MongoTemplate mongoTemplate;

    /*@Autowired

    private MongoRepository mongoRepository;*/

    @Autowired

    private GridFsTemplate gridFsTemplate;

	....

}

添加

通过三种形式来添加数据到mongo

@Test

public void add() {

    // 1. 这种插入的数据的id  就直接是mongodb中的_id

    Student student = new Student(1, "鲁班7号", "1", 80D, Arrays.asList("玩", "虚坤", "天书世界", "贪玩蓝月"));

    mongoTemplate.insert(student);

    // 2. 使用类似map的写法，这种插入的id，是mongodb中的一个字段，会另外自动生成_id

    BasicDBObject obj = new BasicDBObject();

    obj.put("id", 2);

    obj.put("name", "cxk");

    obj.put("score", 95);

    obj.put("clazz", "2");

    String[] hobby = {"唱", "跳", "篮球", "rap"};

    obj.put("hobby", hobby);

    mongoTemplate.insert(obj, "student");

    // 3. 使用json数据 会自动另外生成_id

    BasicDBObject parse = BasicDBObject.parse("{\n" +

                                              "  \"id\": 3,\n" +

                                              "  \"clazz\": \"2\",\n" +

                                              "  \"score\": 90,\n" +

                                              "  \"name\": \"渣渣辉\",\n" +

                                              " \"hobby\":[\"贪\",\"玩\",\"蓝\", \"月\"]\n" +

                                              "}");

    mongoTemplate.insert(parse, "student");

}

student.java

@Getter

@Setter

@NoArgsConstructor

@AllArgsConstructor

@ToString

@Builder

public class Student {

    // 与mongodb中的_id对应

    private Integer id;

    private String name;

    /**

     * 班级

     */

    private String clazz;

    private Double score;

    private List<String> hobby;

}

删除

@Test

public void delete() {

    // 根据id删除

    //        DeleteResult id = mongoTemplate.remove(Query.query(Criteria.where("_id").is(1)), "student");

    Query query = new Query();

    mongoTemplate.remove(query, "student");

}

文档操作更新

/**

 * 文档操作

 */

@Test

public void update() {

    // 只修改第一个条记录

    mongoTemplate.updateFirst(Query.query(Criteria.where("id").gt(2)), Update.update("name", "鸡太美"), "student");

    // 修改匹配到的所有数据

    mongoTemplate.updateMulti(Query.query(Criteria.where("id").gt(2)), Update.update("name", "鸡太美"), "student");

    // 向文档中添加数据 有则跟新 没有则添加

    Update update = new Update();

    update.addToSet("desc", "练习时长两年半的练习生");

    mongoTemplate.upsert(Query.query(Criteria.where("id").gte(2)), update, "student");

    // 删除文档中的数据

    Update delUpdate = new Update();

    delUpdate.unset("desc");

    mongoTemplate.updateMulti(Query.query(Criteria.where("id").gt(2)), delUpdate, "student");

}

简单聚合操作 count, distinct

/**

 * 简单聚合操作  count, distinct

 */

@Test

public void runCommongd() {

    /************* count *********************/

    // student集合中的总人数  select count(1) from student

    Document document = mongoTemplate.executeCommand("{count: 'student'}");

    mongoTemplate.getCollection("student").countDocuments();

    System.out.println(document);

    // 班级为2的人数  注意字符串要有引号 js中单引号和双引号没啥区别 select count(1) from student where clazz = '2'

    Document document1 = mongoTemplate.executeCommand("{count: 'student', query:{clazz: {$eq:'2'}}}");

    System.out.println(document1);

    /************* distinct **************/

    // 去掉重复的班级  select distinct clazz from student

    Document document2 = mongoTemplate.executeCommand("{distinct: 'student', key: 'clazz'}");

    mongoTemplate.getCollection("person").distinct("clazz", Document.class);

    System.out.println(document2);

}

普通查询

/**

  * 查询

  */

@Test

public void findTest() {

    // 这个id默认是mognodb中的_id

    Student student = mongoTemplate.findById(1, Student.class, "student");

    System.out.println(student);

    Document doc = mongoTemplate.findById("5da57cb7f150ea3be420daf8", Document.class, "student");

    //Document{{_id=5da57cb7f150ea3be420daf8, id=2, name=cxk, hobby=[唱, 跳, rap]}}

    System.out.println(doc);

    // Criteria用来构建条件  Query 用来封装所有条件

    Query query = new Query(Criteria.where("_id").is("5da57cb7f150ea3be420daf9"));

    Document one = mongoTemplate.findOne(query, Document.class, "student");

    System.out.println(one);

    // 正则表达式查询 （查询名字中有数字的数据） 如果不需要后面的Pattern.CASE_INSENSITIVE，直接写正则字符串就行

    //Criteria regCriteria = Criteria.where("name").regex(Pattern.compile(".*\\d+.*", Pattern.CASE_INSENSITIVE));

    Criteria regCriteria = Criteria.where("name").regex(".*\\d+.*");

    Query regQuery = new Query(regCriteria);

    List<Student> student1 = mongoTemplate.find(regQuery, Student.class, "student");

    System.out.println(student1);

    // 查询文档中的部分记录

    BasicDBObject dbObject = new BasicDBObject();

    // 添加查询条件 等于的那种

    //dbObject.put("id", 2);

    // 指定返回的字段

    BasicDBObject fieldsObject = new BasicDBObject();

    fieldsObject.put("id", true);

    fieldsObject.put("name", true);

    fieldsObject.put("_id", false);

    Query basicQuery = new BasicQuery(dbObject.toJson(), fieldsObject.toJson());

    // 添加查询条件 更灵活

    query.addCriteria(Criteria.where("id").gt(2));

    List<Document> docs = mongoTemplate.find(basicQuery, Document.class, "student");

    System.out.println(docs);

}

分组

group

/**

     * group分组

     */

    @Test

    public void group() {

        // 查找80分以上的人的平均得分

        GroupBy groupBy = GroupBy.key("clazz")

                .initialDocument("{total:0, count:0}")

                // curr表示当前doc文档，result表示上一次处理之后的{total:0, count:0}对象

                .reduceFunction("function(curr, result) {result.total += curr.score; result.count++}")

                // 类似于having，比having更强大，js语法去操作最后的结果

                .finalizeFunction("function(result) {result.avg = Math.round(result.total/result.count);}");

        Criteria criteria = Criteria.where("score").gte(80);

        GroupByResults<Document> brs = mongoTemplate.group(criteria, "student", groupBy, Document.class);

        for (Document document : brs) {

            System.out.println(document);

        }

    }

Aggregate

/**

     * aggregate聚合查询

     */

    @Test

    public void aggregateTest() {

        //封装查询条件

        // 按班级clazz分组查询得分80以上的总分数

        List<AggregationOperation> operations = new ArrayList<>();

        // where

        operations.add(Aggregation.match(Criteria.where("score").gte(80)));

        // group by  [这个求sum]

        operations.add(Aggregation.group("clazz").sum("score").as("totleScore"));

        // 这个求count

        //operations.add(Aggregation.group("clazz").count().as("totleScore"));

        // having

        //operations.add(Aggregation.match(Criteria.where("totleScore").gt(80)));

        Aggregation aggregation = Aggregation.newAggregation(operations);

        //查询、并获取结果

        AggregationResults<Document> results = mongoTemplate.aggregate(aggregation, "student", Document.class);

        Document map = results.getRawResults();

        System.out.println(map);

    }

mapReduce

    @Test

    public void mapReduce() {

        Query query = new Query();

        // emit中 key：指定分组的字段；values：要聚合的字段（数组）

        String mapFunction = "function() {emit(this.clazz, this.score);}";

        // key：分组字段，values：根据key分组之后的值放在一个数组中，这个values就是这个数组

        String reduceFunction = "function(key, values) {return Array.sum(values);}";

        // 可以对结果做一些处理

        MapReduceOptions mapReduceOptions = new MapReduceOptions();

//        mapReduceOptions.outputCollection("aaaa"); //生成的结果表（在mongo服务器上可以看到）

//        mapReduceOptions.limit(2);

        MapReduceResults<Document> results = mongoTemplate.mapReduce(query, "student", mapFunction, reduceFunction, mapReduceOptions, Document.class);

        Iterator<Document> it = results.iterator();

        for (;it.hasNext();) {

            System.out.println(it.next());

        }

        // 查询每个人的兴趣爱好个数

        Query query1 = new Query();

        String mapFunction1 = "function() {emit(this.name, this.hobby);}";

        String reduceFunction1 = "function(key, values) {" +

                "reduceVal = {name: key, hobbys: values};" +

                "return reduceVal;" +

                "}";

        String func_finalize = "function(name, hobbys) {return hobbys.length}";

        MapReduceOptions mapReduceOptions1 = new MapReduceOptions();

        mapReduceOptions1.finalizeFunction(func_finalize);

        MapReduceResults<Document> results1 = mongoTemplate.mapReduce(query1, "student", mapFunction1, reduceFunction1, mapReduceOptions1,  Document.class);

        for (Iterator<Document> it1 = results1.iterator(); it1.hasNext();) {

            System.out.println(it1.next());

        }

    }

group和mapReduce的区别在于group不能跨片查询，如果是分片集群的话使用mapReduce

查看mongo拓展的js的Array方法:

> for (var key in Array) {

    print(key)

}

contains

unique

shuffle

tojson

fetchRefs

sum

avg

stdDev

分页查询

/**

 * 分页查询

 */

@Test

public void pageQuery() {

    Query query = new Query();

    query.skip(1);

    query.limit(2);

    List<Document> student = mongoTemplate.find(query, Document.class, "student");

    System.out.println(student);

}

文件上传

/**

  * 文件上传

  */

@Test

public void uploadGridFs() throws Exception {

    File file = new File("E:\\1.xml");

    FileInputStream fin = new FileInputStream(file);

    Document doc = new Document();

    doc.put("filename", file.getName());

    doc.put("uploadDate", new Date());

    doc.put("author", "joe");

    gridFsTemplate.store(fin, file.getName(), "xml", doc);

}

文件下载

/**

 * 文件下载

 */

@Test

public void downLoadGridFs() throws Exception {

    Query query = new Query();

    //        query.addCriteria(Criteria.where("filename").is("1.xml"));

    query.addCriteria(Criteria.where("metadata.author").is("joe"));

    // 1.从fs.files中查询文件的相关信息

    GridFSFile gfsFile = gridFsTemplate.findOne(query);

    // 2.从fs.chunks中获取文件（通过1中查询的files_id）

    GridFsResource resource = gridFsTemplate.getResource(gfsFile);

    InputStream in = resource.getInputStream();

    FileOutputStream fout = new FileOutputStream(new File("E:\\1bak.xml"));

    try {

        byte[] buf = new byte[1024];

        for (int len;(len = in.read(buf, 0, 1024)) != -1;) {

            fout.write(buf, 0, len);

        }

        fout.flush();

    } catch (Exception e) {

        e.printStackTrace();

    }

}

巴特西

springboot调用mongo

添加

删除

文档操作更新

简单聚合操作 count, distinct

普通查询

分组

group

Aggregate

mapReduce

分页查询

文件上传

文件下载

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