本篇博文为mongodb的curd中一篇，前面介绍简单的查询使用，这一篇重点则放在插入数据;
I. 基本使用
首先是准备好基本环境，可以参考博文
- 181213-SpringBoot高级篇MongoDB之基本环境搭建与使用
- 190113-SpringBoot高级篇MongoDB之查询基本使用姿势
1. 新增一条数据
MongoDB一个基本数据称为document，和mysql不一样，没有强制约束哪些字段，可以随意的插入，下面是一个简单的插入演示
private static final String COLLECTION_NAME = "demo"; @Autowired private MongoTemplate mongoTemplate; /** * 新增一条记录 */ public void insert() { JSONObject object = new JSONObject(); object.put("name", "一灰灰blog"); object.put("desc", "欢迎关注一灰灰Blog"); object.put("age", 28); // 插入一条document mongoTemplate.insert(object, COLLECTION_NAME); JSONObject ans = mongoTemplate .findOne(new Query(Criteria.where("name").is("一灰灰blog").and("age").is(28)), JSONObject.class, COLLECTION_NAME); System.out.println(ans); } 复制代码
使用的关键地方为一行: mongoTemplate.insert(object, COLLECTION_NAME);
- 第一个参数为待插入的document
- 第二个参数为collection name （相当于mysql的table)
执行后输出结果为如下
{"name":"一灰灰blog","_id":{"counter":12472353,"date":1548333180000,"machineIdentifier":14006254,"processIdentifier":17244,"time":1548333180000,"timeSecond":1548333180,"timestamp":1548333180},"age":28,"desc":"欢迎关注一灰灰Blog"} 复制代码
2. 批量插入
一次插入多条记录，传集合进去即可
/** * 批量插入 */ public void insertMany() { List<Map<String, Object>> records = new ArrayList<>(); for (int i = 0; i < 3; i++) { Map<String, Object> record = new HashMap<>(4); record.put("wechart", "一灰灰blog"); record.put("blog", Arrays.asList("http://spring.hhui.top", "http://blog.hhui.top")); record.put("nums", 210); record.put("t_id", i); records.add(record); } // 批量插入文档 mongoTemplate.insert(records, COLLECTION_NAME); // 查询插入的内容 List<Map> result = mongoTemplate.find(new Query(Criteria.where("wechart").is("一灰灰blog")), Map.class, COLLECTION_NAME); System.out.println("Query Insert Records: " + result); } 复制代码
返回结果如下:
Query Insert Records: [{t_id=0, wechart=一灰灰blog, _id=5c49b07cd5b7ee435cbe5022, blog=[http://spring.hhui.top, http://blog.hhui.top], nums=210}, {t_id=1, wechart=一灰灰blog, _id=5c49b07cd5b7ee435cbe5023, blog=[http://spring.hhui.top, http://blog.hhui.top], nums=210}, {t_id=2, wechart=一灰灰blog, _id=5c49b07cd5b7ee435cbe5024, blog=[http://spring.hhui.top, http://blog.hhui.top], nums=210}] 复制代码
3. upsert，不存在才插入
我们希望在插入之前，判断数据是否存在，如果不存在则插入；如果存在则更新；此时就可以采用upsert来使用，一般三个参数
mongoTemplate.upsert(Query query, Update update, String collectionName) 复制代码
第一个为查询条件，第二个为需要更新的字段，最后一个指定对应的collection，一个简单的实例如下
/** * 数据不存在，通过 upsert 新插入一条数据 * * set 表示修改key对应的value * addToSet 表示在数组中新增一条 */ public void upsertNoMatch() { // addToSet 表示将数据塞入document的一个数组成员中 UpdateResult upResult = mongoTemplate.upsert(new Query(Criteria.where("name").is("一灰灰blog").and("age").is(100)), new Update().set("age", 120).addToSet("add", "额外增加"), COLLECTION_NAME); System.out.println("nomatch upsert return: " + upResult); List<JSONObject> re = mongoTemplate .find(new Query(Criteria.where("name").is("一灰灰blog").and("age").is(120)), JSONObject.class, COLLECTION_NAME); System.out.println("after upsert return should not be null: " + re); System.out.println("------------------------------------------"); } 复制代码
输出结果如下:
nomatch upsert return: AcknowledgedUpdateResult{matchedCount=0, modifiedCount=0, upsertedId=BsonObjectId{value=5c49b07ce6652f7e1add1ea2}} after upsert return should not be null: [{"add":["额外增加"],"name":"一灰灰blog","_id":{"counter":14491298,"date":1548333180000,"machineIdentifier":15099183,"processIdentifier":32282,"time":1548333180000,"timeSecond":1548333180,"timestamp":1548333180},"age":120}] ------------------------------------------ 复制代码
4. upsert，存在则更新
前面的demo是演示不存在，那么存在数据呢?
/** * 只有一条数据匹配，upsert 即表示更新 */ public void upsertOneMatch() { // 数据存在，使用更新 UpdateResult result = mongoTemplate.upsert(new Query(Criteria.where("name").is("一灰灰blog").and("age").is(120)), new Update().set("age", 100), COLLECTION_NAME); System.out.println("one match upsert return: " + result); List<JSONObject> ans = mongoTemplate .find(new Query(Criteria.where("name").is("一灰灰blog").and("age").is(100)), JSONObject.class, COLLECTION_NAME); System.out.println("after update return should be one: " + ans); System.out.println("------------------------------------------"); } 复制代码
输出结果如下，注意下面的输出数据的 _id，正视前面插入的那条数据，两个数据唯一的不同，就是age被修改了
one match upsert return: AcknowledgedUpdateResult{matchedCount=1, modifiedCount=1, upsertedId=null} after update return should be null: [{"add":["额外增加"],"name":"一灰灰blog","_id":{"counter":14491298,"date":1548333180000,"machineIdentifier":15099183,"processIdentifier":32282,"time":1548333180000,"timeSecond":1548333180,"timestamp":1548333180},"age":100}] 复制代码
5. upsert，多条满足时
如果query条件命中多条数据，怎么办？会修改几条数据呢？
/** * 两条数据匹配时，upsert 将只会更新一条数据 */ public void upsertTwoMatch() { // 多条数据满足条件时，只会修改一条数据 System.out.println("------------------------------------------"); List<JSONObject> re = mongoTemplate .find(new Query(Criteria.where("name").is("一灰灰blog").and("age").in(Arrays.asList(28, 100))), JSONObject.class, COLLECTION_NAME); System.out.println("original record: " + re); UpdateResult result = mongoTemplate .upsert(new Query(Criteria.where("name").is("一灰灰blog").and("age").in(Arrays.asList(28, 100))), new Update().set("age", 120), COLLECTION_NAME); System.out.println("two match upsert return: " + result); re = mongoTemplate.find(new Query(Criteria.where("name").is("一灰灰blog").and("age").is(120)), JSONObject.class, COLLECTION_NAME); System.out.println("after upsert return size should be 1: " + re); System.out.println("------------------------------------------"); } 复制代码
根据实际输出进行查看，发现只有一条数据被修改；另外一条保持不变，结果如下
------------------------------------------ original record: [{"name":"一灰灰blog","_id":{"counter":12472353,"date":1548333180000,"machineIdentifier":14006254,"processIdentifier":17244,"time":1548333180000,"timeSecond":1548333180,"timestamp":1548333180},"age":28,"desc":"欢迎关注一灰灰Blog"}, {"add":["额外增加"],"name":"一灰灰blog","_id":{"counter":14491298,"date":1548333180000,"machineIdentifier":15099183,"processIdentifier":32282,"time":1548333180000,"timeSecond":1548333180,"timestamp":1548333180},"age":100}] two match upsert return: AcknowledgedUpdateResult{matchedCount=1, modifiedCount=1, upsertedId=null} after upsert return size should be 1: [{"name":"一灰灰blog","_id":{"counter":12472353,"date":1548333180000,"machineIdentifier":14006254,"processIdentifier":17244,"time":1548333180000,"timeSecond":1548333180,"timestamp":1548333180},"age":120,"desc":"欢迎关注一灰灰Blog"}] ------------------------------------------
