SpringBoot 整合 InfluxDB1.x 三种方式

本文介绍: 本人已知Spr in gBo o t 集成InfluxDB有三种方式，原生集成、spring 封装集成、influxDB封装框架，使用如同My bat i s 简洁方便，本文将依次介绍使用方式。

一.Spr in gBo o t 集成InfluxDB 1.x

既然准备Spr in gBo o t 整合InfluxDB，想必你已经了解了InfluxDB的安装、配置、使用。

那么就直奔正文。

目前本人已知可以实现的方式有3种：

集成原生的InfluxDB

集成封装的InfluxDBTempla t e

集成InfluxDB封装的框架

环境：

influxDB 1.8

二.集成原生的InfluxDB

导入依赖

<!-- InfluxDB 原生依赖 --&gt;
<dependency&gt;
  <groupId&gt;org.influxdb</groupId&gt;
  <artifactId&gt;influxdb-java</artifactId&gt;
  <version&gt;2.18</version>
</dependency>

配置YAML文件

influxdb:
  url: http://127.0.0.1:8086
  username: root         #用户
  password: 123          #密码
  database: test         #库
  retention: autogen     #保存策略

创建InfluxDB工具类


import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import org.influxdb.InfluxDB;
import org.influxdb.InfluxDB.ConsistencyLevel;
import org.influxdb.InfluxDBFactory;
import org.influxdb.dto.*;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.stereotype.Component;
import org.influxdb.dto.Point.Builder;

import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;

/**
 * InfluxDB数据库连接操作类
 */
@Data
@Component
@Slf4j
public class InfluxDbComUtil {
    // 用户名
    @Value("${influxdb.username}")
    private String username;
    // 密码
    @Value("${influxdb.password}")
    private String password;
    // 连接地址
    @Value("${influxdb.url}")
    private String openurl;
    // 数据库名称
    @Value("${influxdb.database}")
    private String dbName;
    // 保留策略
    @Value("${influxdb.retention}")
    private String retentionPolicy;
    @Autowired
    private InfluxDB influxDB;

    public InfluxDbComUtil() {
    }
    /**
     * 连接时序数据库 ，若不存在则创建
     *
     * @return
     */
    @Bean
    public InfluxDB influxDbBuild() {
        if (influxDB == null) {
            influxDB = InfluxDBFactory.connect(openurl, username, password);
        }
        try {
            if (!influxDB.databaseExists(dbName)) {
                influxDB.createDatabase(dbName);
            }
        } catch (Exception e) {
            // 该数据库可能设置动态代理，不支持创建数据库
            e.printStackTrace();
        } finally {
            influxDB.setRetentionPolicy(retentionPolicy);
        }
        influxDB.setLogLevel(InfluxDB.LogLevel.NONE);
        return influxDB;
    }
    /**
     * 测试连接是否正常
     *
     * @return true 正常
     */
    public boolean ping() {
        boolean isConnected = false;
        Pong pong;
        try {
            pong = influxDB.ping();
            if (pong != null) {
                isConnected = true;
            }
        } catch (Exception e) {
            e.printStackTrace();
        }
        return isConnected;
    }
    /**
     * 创建数据库
     *
     * @param dbName
     */
    @SuppressWarnings("deprecation")
    public void createDB(String dbName) {
        influxDB.createDatabase(dbName);
    }
    /**
     * 删除数据库
     *
     * @param dbName
     */
    @SuppressWarnings("deprecation")
    public void deleteDB(String dbName) {
        influxDB.deleteDatabase(dbName);
    }
    /**
     * 切换数据库
     */
    @SuppressWarnings("deprecation")
    public void setDB(String dbName){
        influxDB.setDatabase(dbName);
    }
    /**
     * 关闭数据库
     */
    public void close() {
        influxDB.close();
    }
    /**
     * 切换数据库策略
     * @param dataBaseName 数据库
     * @param policyName 策略名
     */
    public void updRetentionPolicy(String dataBaseName,String policyName){
        String sql=String.format("ALTER RETENTION POLICY ""+policyName+"" ON ""+dataBaseName+"" DEFAULT");
        query(sql);
        this.dbName=dataBaseName;
        this.retentionPolicy=policyName;
    }
    /**
     * 切换策略
     * @param policyName 策略名
     */
    public void updRetentionPolicy(String policyName){
        String sql=String.format("ALTER RETENTION POLICY ""+policyName+"" ON ""+dbName+"" DEFAULT");
        query(sql);
        this.retentionPolicy=policyName;
    }
    /**
     * 创建自定义保留策略
     *
     * @param policyName  策略名
     * @param days        保存天数
     * @param replication 保存副本数量
     * @param isDefault   是否设为默认保留策略
     */
    public void createRetentionPolicy(String dataBaseName, String policyName, int days, int replication, Boolean isDefault) {
        String sql = String.format("CREATE RETENTION POLICY "%s" ON "%s" DURATION %sd REPLICATION %s ", policyName,
                dataBaseName, days, replication);
        if (isDefault) {
            sql = sql + " DEFAULT";
        }
        query(sql);
    }
    /**
     * 创建默认的保留策略
     *
     * 策略名：hour，保存天数：30天，保存副本数量：1,设为默认保留策略
     */
    public void createDefaultRetentionPolicy() {
        String command = String
                .format("CREATE RETENTION POLICY "%s" ON "%s" DURATION %s REPLICATION %s DEFAULT", "hour", dbName,
                        "30d", 1);
        this.query(command);
    }

/*********************************增删查**************************************************/
    /**
     * 查询
     *
     * @param command 查询语句
     * @return
     */
    public QueryResult query(String command) {
        return influxDB.query(new Query(command, dbName));
    }
    /**
     * 插入
     *
     * @param measurement 表
     * @param tags        标签
     * @param fields      字段
     */
    public void insert(String measurement, Map<String, String> tags, Map<String, Object> fields, long time,
                       TimeUnit timeUnit) {
        Builder builder = Point.measurement(measurement);
        builder.tag(tags);
        builder.fields(fields);
        if (0 != time) {
            builder.time(time, timeUnit);
        }
        influxDB.write(dbName, retentionPolicy, builder.build());
    }
    /**
     * 删除
     *
     * @param command 删除语句
     * @return 返回错误信息
     */
    public String deleteMeasurementData(String command) {
        QueryResult result = influxDB.query(new Query(command, dbName));
        return result.getError();
    }
    /**
     * 构建Point
     * @param measurement 表
     * @param time 时间
     * @param timeUnit 延迟
     * @param tags  tags
     * @param fields
     * @return
     */
    public Point pointBuilder(String measurement, long time, TimeUnit timeUnit, Map<String, String> tags, Map<String, Object> fields) {
        Point point = Point.measurement(measurement).time(time, timeUnit).tag(tags).fields(fields).build();
        return point;
    }

    /**
     * 批量写入测点
     *
     * @param batchPoints
     */
    public void batchInsert(BatchPoints batchPoints, TimeUnit timeUnit) {
        influxDB.write(batchPoints);
        // influxDB.enableGzip();
        // influxDB.enableBatch(2000,100,timeUnit);
        // influxDB.disableGzip();
        // influxDB.disableBatch();
    }

    /**
     * 批量写入数据
     *
     * @param database        数据库
     * @param retentionPolicy 保存策略
     * @param consistency     一致性
     * @param records         要保存的数据（调用BatchPoints.lineProtocol()可得到一条record）
     */
    public void batchInsert(final String database, final String retentionPolicy, final ConsistencyLevel consistency, TimeUnit timeUnit, final List<String> records) {
        influxDB.write(database, retentionPolicy, consistency, timeUnit, records);
    }

}

使用


/**
 * 测试例子
 */
/**新增测试Util*/
InfluxDbComUtil influxDbComUtil = SpringUtils.getBean(InfluxDbComUtil.class);
Map<String, String> tags = new HashMap<>();
tags.put("tag1", "标签值");
Map<String, Object> fields = new HashMap<String, Object>();
fields.put("field1", "String类型");
// 数值型，InfluxDB的字段类型，由第一天插入的值得类型决定
fields.put("field2", 3.141592657);
// 时间使用毫秒为单位
influxDbComUtil.insert("表名", tags, fields, System.currentTimeMillis(), TimeUnit.MILLISECONDS);

/**查询*/
QueryResult result = influxDbComUtil.query("SELECT * FROM alarm_album");
QueryResult.Result oneResult=result.getResults().get(0);
if (oneResult.getSeries() != null) {
    List<List<Object>> valueList = oneResult.getSeries().stream()
                                    .map(QueryResult.Series::getValues)
                                    .collect(Collectors.toList()).get(0);
    if (valueList != null &amp;&amp; valueList.size() > 0) {
        for (List<Object> value : valueList) {
            Map<String, String> map = new HashMap<String, String>();
            // 数据库中字段1取值
            String field1 = value.get(0) == null ? null : value.get(0).toString();
            // 数据库中字段2取值
            String field2 = value.get(1) == null ? null : value.get(1).toString();
            // TODO 用取出的字段做你自己的业务逻辑……
            System.out.println(value);
        }
    }
}

新增结果

查询结果(数据库内仅有一条数据)

配置实体类


@Data
@Measurement(name="terminal_heart_beat")
public class TerminalHeartBeatModel{
    @Column(name="id", tag = true)  //tag 可以理解为influxdb的索引
    private Long id;
    @Column(name="mac")
    private String mac;
}

使用原生InfluxDBMapper


InfluxDbComUtil influxDbComUtil = SpringUtils.getBean(InfluxDbComUtil.class);
influxDbComUtil.setDB(influxDbComUtil.getDbName());//讲influxdb的库设置成默认的库 你也可以自己填。
InfluxDBMapper influxDBMapper = new InfluxDBMapper(influxDbComUtil.getInfluxDB());
//根据对象进行新增或查询
Test test=new Test();
test.setId(new Long(10));
test.setMac("aa:bb:cc...");

influxDBMapper.save(test);

List<Test> testList = influxDBMapper.query(Test.class);

但是关于time列，通过原生InfluxDB：Point进行新增操作，是以long型或Number型

三.集成Spring封装的InfluxDB Template

导入依赖

<!-- Spring封装的InfluxDB -->
<dependency>
    <groupId>plus.ojbk</groupId>
    <artifactId>influxdb-spring-boot-starter</artifactId>
    <version>1.0.2</version>
</dependency>

配置YAML

influxdb:
  url: http://127.0.0.1:8086
  username: root         #用户
  password: 123          #密码
  database: test         #库

配置实体类


@Data
@Measurement(name="terminal_heart_beat")
public class TerminalHeartBeatModel{
    @Column(name="id", tag = true)  //tag 可以理解为influxdb的索引
    private Long id;
    @Column(name="mac")
    private String mac;
    @Column(name="time")
    private LocalDateTime time;
}

使用


@Resource
private InfluxdbTemplate influxdbTemplate;

/**
     * 获取集合
     * @param map
     * @param start
     * @param end
     * @return
     */
public List<TerminalHeartBeatModel> getList(Map<String,Object> map,LocalDateTime start, LocalDateTime end){
    //类似MybatisPlus中的QueryWrapper
    QueryModel queryModel = new QueryModel();
    queryModel.setMeasurement(InfluxdbUtils.getMeasurement(TerminalHeartBeatModel.class));
    //Map<String, Object> map = new TreeMap<>();
    //map.put("mac", "00:aa:00:aa:00:00");
    queryModel.setMap(map);
    queryModel.setStart(start);
    queryModel.setEnd(end);
    queryModel.setUseTimeZone(true);  //时区
    queryModel.setOrder(Order.DESC);  //排序
    //where 条件中额外参数可放入model.setMap();
    queryModel.setWhere(Op.where(queryModel));
    return influxdbTemplate.selectList(Query.build(queryModel), TerminalHeartBeatModel.class);
}
/** 新增 */
public void save(TerminalHeartBeatModel model){
    influxdbTemplate.insert(model);
}

相较于原版，它封装了自有的Util以及Template等

对于原版Point的time列类型问题，它对number和long 型转换成了LocalDateTime类型

并且封装了更多的方法（具体自行拓展）

四.集成InfluxDB封装的框架

导入依赖

<!-- git作者个人封装的框架 -->
<dependency>
    <groupId>io.github.betacatcode</groupId>
    <artifactId>spring-boot-starter-influxdb</artifactId>
    <version>0.0.4-RELEASE</version>
</dependency>
<dependency>
    <groupId>org.influxdb</groupId>
    <artifactId>influxdb-java</artifactId>
    <version>2.18</version>
</dependency>

配置YAML

spring:
  influx:
    url: http://127.0.0.1:8086
    user: admin
    password: 123456
    mapper-location: com.github.betacatcode

配置实体类


@Data
@Measurement(database = "test",name = "student")
public class Student {
    private String id;

    @Column(name = "sname",tag = true)
    private String sname;

    @Column(name = "value")
    private Double value;

    @TimeColumn
    @Column(name = "time")
    private Instant time;
}

创建Mapper 继承InfluxDBBaseMapper接口


public interface StudentMapper extends InfluxDBBaseMapper {

    @Select(value = "select * from test.autogen.student where sname=#{sname}",
            resultType = Student.class)
    List<Student> selectByName(String sname);

    @Delete(value = "delete from student",database = "test")
    void deleteAll();

    @Insert
    void insertOne(Student student);

    @Insert
    void insertBatch(List<Student> students);

}