MongoDB千万级数据性能测试
MongoDB千万级数据性能测试
·
在自己的虚拟机上测了下
MongoDB千万级数据的性能，方法比较粗糙，仅供参考。
一、环境准备
CentOS 7.6 CPU 4核 内存 8G
MongoDB 5.0.9
二、测试代码
用Spring Boot写了个测试程序
Maven依赖 pom.xml
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<!-- mongodb -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-mongodb</artifactId>
</dependency>
<!-- lombok依赖 -->
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.18.16</version>
<scope>provided</scope>
</dependency>
</dependencies>
配置文件 application.properties
spring.data.mongodb.uri=mongodb://192.168.73.146:27017/springboot
实体类
package com.rkyao.spring.boot.mongo.entity;
import lombok.Data;
import lombok.ToString;
/**
* mongo表实体类
*
* @author Administrator
* @date 2022/6/17
*/
@Data
@ToString
public class MongoEntity {
private String userId;
private String userName;
private Integer age;
private String address;
private String field5;
private String field6;
private String field7;
private String field8;
private String field9;
private String field10;
private String field11;
private String field12;
private String field13;
private String field14;
private String field15;
private String field16;
private String field17;
private String field18;
private String field19;
private String field20;
}
插入、查询代码，性能测试结果参见注释
package com.rkyao.spring.boot.mongo.controller;
import com.rkyao.spring.boot.mongo.entity.MongoEntity;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.index.HashedIndex;
import org.springframework.data.mongodb.core.query.Criteria;
import org.springframework.data.mongodb.core.query.Query;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import java.util.UUID;
/**
* 性能测试程序
*
* 4核
* 8G
* 40G SSD
*
* @author Administrator
* @date 2022/6/17
*/
@RestController
@Slf4j
public class MongoController {
@Autowired
private MongoTemplate mongoTemplate;
public static final String MONGO_TABLE = "t_user_info";
/**
* localhost:8080/findOne
*
* 总量10000000条
*
* 查询单条耗时 4个字段 < 5ms
* 查询单条耗时 20个字段 < 5ms
*
* @return
*/
@RequestMapping("/findOne")
public String findOne() {
long start = System.currentTimeMillis();
Query query = new Query(Criteria.where("age").is(23));
MongoEntity mongoEntity = mongoTemplate.findOne(query, MongoEntity.class, MONGO_TABLE);
long cost = System.currentTimeMillis() - start;
String logStr = String.format("查询 %s 条数据耗时: %s ms", 1, cost);
log.info(logStr);
return logStr;
}
/**
* localhost:8080/find
*
* 总量10000000条
*
* 查询10000条耗时 无索引 4个字段 4000ms ~ 5000ms
* 查询10000条耗时 Test索引 4个字段 4000ms ~ 5000ms
* 查询10000条耗时 Hashed索引 4个字段 100ms ~ 150ms
*
* 查询10000条耗时 无索引 20个字段 25000ms ~ 30000ms
* 查询10000条耗时 Test索引 20个字段 23781ms
* 查询10000条耗时 Hashed索引 20个字段 500ms ~ 600ms (总量2千万时性能没有明显差距)
*
* @return
*/
@RequestMapping("/find")
public String find() {
long start = System.currentTimeMillis();
Query query = new Query(Criteria.where("age").is(23));
// query.fields().include("userId", "userName", "age", "address");
query.limit(10000);
List<MongoEntity> mongoEntityList = mongoTemplate.find(query, MongoEntity.class, MONGO_TABLE);
long cost = System.currentTimeMillis() - start;
String logStr = String.format("查询 %s 条数据耗时: %s ms", mongoEntityList.size(), cost);
log.info(logStr);
return logStr;
}
/**
* localhost:8080/insert
*
* 插入单条耗时 < 5ms
*
* @return
*/
@RequestMapping("/insert")
public String insert() {
long start = System.currentTimeMillis();
mongoTemplate.insert(createMongoEntity(), MONGO_TABLE);
long cost = System.currentTimeMillis() - start;
String logStr = String.format("插入 %s 条数据耗时: %s ms", 1, cost);
log.info(logStr);
return logStr;
}
/**
* localhost:8080/insertBatch
*
* 插入10000条耗时 逐条插入 4个字段 6000 ~ 10000ms
* 插入10000条耗时 逐条插入 20个字段 13468ms
*
* @return
*/
@RequestMapping("/insertBatch")
public String insertBatch() {
long start = System.currentTimeMillis();
int count = 10000;
for (int i = 0; i < count; i++) {
mongoTemplate.insert(createMongoEntity(), MONGO_TABLE);
}
long cost = System.currentTimeMillis() - start;
String logStr = String.format("插入 %s 条数据耗时: %s ms", count, cost);
log.info(logStr);
return logStr;
}
/**
* localhost:8080/insertBatch2
*
* 插入10000条耗时 批量插入 4个字段 300 ~ 500ms
* 插入10000条耗时 批量插入 20个字段 1060ms
*
* @return
*/
@RequestMapping("/insertBatch2")
public String insertBatch2() {
int count = 10000;
List<MongoEntity> mongoEntityList = new ArrayList<>();
for (int i = 0; i < count; i++) {
mongoEntityList.add(createMongoEntity());
}
long start = System.currentTimeMillis();
mongoTemplate.insert(mongoEntityList, MONGO_TABLE);
long cost = System.currentTimeMillis() - start;
String logStr = String.format("插入 %s 条数据耗时: %s ms", count, cost);
log.info(logStr);
return logStr;
}
/**
* localhost:8080/insertBatch3
*
* 插入10000000条耗时 批量插入 4个字段 298000ms 354557ms
* 插入10000000条耗时 批量插入 20个字段 1372460ms
*
* 存储大小: 6.69G 单索引大小：107.46MB
*
* @return
*/
@RequestMapping("/insertBatch3")
public String insertBatch3() {
int loop = 1000;
int count = 10000;
long start = System.currentTimeMillis();
for (int i = 0; i < loop; i++) {
List<MongoEntity> mongoEntityList = new ArrayList<>();
for (int j = 0; j < 10000; j++) {
mongoEntityList.add(createMongoEntity());
}
long startTemp = System.currentTimeMillis();
mongoTemplate.insert(mongoEntityList, MONGO_TABLE);
long costTemp = System.currentTimeMillis() - startTemp;
String logStr = String.format("插入 %s 条数据耗时: %s ms", i * count, costTemp);
log.info(logStr);
}
long cost = System.currentTimeMillis() - start;
String logStr = String.format("插入 %s 条数据耗时: %s ms", loop * count, cost);
log.info(logStr);
return logStr;
}
/**
* localhost:8080/createIndex
*
* 创建Text类型单列索引 表里有10000000数据 21538 ms
* 创建Hashed类型单列索引 表里有10000000数据 20962 ms
*
* @return
*/
@RequestMapping("/createIndex")
public String createIndex() {
long start = System.currentTimeMillis();
// 创建Text类型索引
// TextIndexDefinition textIndex = new TextIndexDefinition.TextIndexDefinitionBuilder().onField("age").build();
// mongoTemplate.indexOps(MONGO_TABLE).ensureIndex(textIndex);
// 创建Hashed类型索引
HashedIndex hashedIndex = HashedIndex.hashed("age");
mongoTemplate.indexOps(MONGO_TABLE).ensureIndex(hashedIndex);
long cost = System.currentTimeMillis() - start;
String logStr = String.format("创建索引耗时: %s ms", cost);
log.info(logStr);
return logStr;
}
private MongoEntity createMongoEntity() {
Random rd = new Random();
int temp = rd.nextInt(1000);
// 四个字段
MongoEntity mongoEntity = new MongoEntity();
mongoEntity.setUserId(UUID.randomUUID().toString());
mongoEntity.setUserName("rkyao" + temp);
mongoEntity.setAge(temp);
mongoEntity.setAddress("山东");
// 16个字段 数量可选，不需要的注释掉
mongoEntity.setField5(UUID.randomUUID().toString());
mongoEntity.setField6(UUID.randomUUID().toString());
mongoEntity.setField7(UUID.randomUUID().toString());
mongoEntity.setField8(UUID.randomUUID().toString());
mongoEntity.setField9(UUID.randomUUID().toString());
mongoEntity.setField10(UUID.randomUUID().toString());
mongoEntity.setField11(UUID.randomUUID().toString());
mongoEntity.setField12(UUID.randomUUID().toString());
mongoEntity.setField13(UUID.randomUUID().toString());
mongoEntity.setField14(UUID.randomUUID().toString());
mongoEntity.setField15(UUID.randomUUID().toString());
mongoEntity.setField16(UUID.randomUUID().toString());
mongoEntity.setField17(UUID.randomUUID().toString());
mongoEntity.setField18(UUID.randomUUID().toString());
mongoEntity.setField19(UUID.randomUUID().toString());
mongoEntity.setField20(UUID.randomUUID().toString());
return mongoEntity;
}
}
三、源码
https://github.com/yaorongke/spring-boot-demos/tree/main/spring-boot-mongo
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