docker安装windows容器 Docker安装InfluxDB1.x和InfluxDB2.x以及与SpringBoot整合

两者区别：1.x 版本使用 influxQL 查询语言， 2.x 和 1.8+（beta）使用 flux 查询语法；相比V1 移除了database 和 RP ，增加了bucket 。V2具有以下几个概念：timestamp、field key、field value、field set、tag key、tag value、tag set、measurement、series、point、bucket、bucket schema、organization新增的概念：bucket：所有 InfluxDB 数据都存储在一个存储桶中。一个桶结合了数据库的概念和存储周期（时间每个数据点仍然存在持续时间）。一个桶属于一个组织bucket schema：具有明确的schema-type的存储桶需要为每个度量指定显式架构。测量包含标签、字段和时间戳。显式模式限制了可以写入该度量的数据的形状。organization：InfluxDB组织是一组用户的工作区。所有仪表板、任务、存储桶和用户都属于一个组织。本文所有代码：https://github.com/Tom-shushu/InfluxDB1.xAnd2.x-SpringBoot新得阅读地址：http://www.zhouhong.icu/archives/docker-an-zhuang-influxdb1x-he-influxdb2x-yi-ji-yu-springboot-zheng-he

一、InfluxDB1.x Docker安装以及与Boot整合A、docker安装InfluxDB1.x （influxdb1.8.4）1、安装：docker run -d--name influxdb -p 8086:8086 influxdb:1.8.4 2、查看
docker ps -a3、进入docker的influx中docker exec -it daf88772adc9 /bin/bash4、直接输入influx启动influx

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5、修改账户密码# 显示用户SHOW USERS# 创建用户CREATE USER "username" WITH PASSWORD 'password'# 赋予用户管理员权限GRANT ALL PRIVILEGES TO username# 创建管理员权限的用户CREATE USER <username> WITH PASSWORD '<password>' WITH ALL PRIVILEGES# 修改用户密码SET PASSWORD FOR username = 'password'# 撤消权限REVOKE ALL ON mydb FROM username# 查看权限SHOW GRANTS FOR username# 删除用户DROP USER "username"
6、在配置文件启用认证默认情况下， influxdb的配置文件是禁用认证策略的，所以需要修改设置一下。编辑配置文件vim /etc/influxdb/influxdb.conf ，把 [http] 下的 auth-enabled 选项设置为 true7、设置保存策略（多长时间之前的数据需要删除）---默认为 autogen 永久不删除a、查看数据库的保存策略show retention policies on 数据库名例子：# 选择使用telegraf数据库> use influx_test;Using database influx_test# 查询数据保存策略> show retention policies on influx_testnameduration shardGroupDuration replicaN default------------ ------------------ -------- -------autogen 0s168h0m0s1true
name 策略名称：默认autogenduration 持续时间： 0s 代表无限制shardGroupDuration shardGroup数据存储时间：shardGroup是InfluxDB的一个基本存储结构, 应该大于这个时间的数据在查询效率上应该有所降低。replicaN 副本个数：1 代表只有一个副本default 是否默认策略：true 代表设置为该数据库的默认策略b、设置保存策略# 新建一个策略CREATE RETENTION POLICY "策略名称" ON 数据库名 DURATION 时长 REPLICATION 副本个数;# 新建一个策略并且直接设置为默认策略CREATE RETENTION POLICY "策略名称" ON 数据库名 DURATION 时长 REPLICATION 副本个数 DEFAULT;例子：# 创建新的默认策略role_01保留数据时长1小时> CREATE RETENTION POLICY "1hour" ON influx_test DURATION 1h REPLICATION 1 DEFAULT;c、修改保存策略
ALTER RETENTION POLICY "策略名称" ON "数据库名" DURATION 时长ALTER RETENTION POLICY "策略名称" ON "数据库名" DURATION 时长 DEFAULTd、删除保存策略
drop retention POLICY "策略名" ON "数据库名"8、使用桌面可视化工具连接数据库工具链接：https://github.com/CymaticLabs/InfluxDBStudio/releases/download/v0.2.0-beta.1/InfluxDBStudio-0.2.0.zip

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如果刚才没有设置密码，这里可以不需要填写密码，如果有账号密码则需要勾上下面的Use SSL连接成功后如下：

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B、InfluxDB1.x与Spring整合（只列举部分代码，后面会放上整个项目的GitHub地址）整个项目结构如下：

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1、引入依赖（其他依赖未显示全，后面会放上整个项目的GitHub地址）
<dependency><groupId>com.influxdb</groupId><artifactId>influxdb-client-java</artifactId><version>4.0.0</version></dependency><dependency><groupId>org.influxdb</groupId><artifactId>influxdb-java</artifactId><version>2.20</version></dependency>2、新建yml文件
influx:url: 'http://xxx.xx.xxx.xx:8086'password: 'password'username: 'username'3、连接配置 InfluxDBConfig
@Data@Configuration@ConfigurationProperties(prefix = "influx")public class InfluxDBConfig {private String url;private String username;private String password;/*** description: 用于查询* date: 2022/1/20 23:11* author: zhouhong* @param* @param null* @return*/@Bean(destroyMethod = "close")public InfluxDB influxDBClient(){return InfluxDBFactory.connect(this.url, this.username, this.password);}/*** description: 用于写入* date: 2022/1/20 23:12* author: zhouhong* @param* @param null* @return*/@Bean(name = "influxDbWriteApi",destroyMethod = "close")public WriteApi influxDbWriteApi(){InfluxDBClient influxDBClient = InfluxDBClientFactory.createV1(this.url, this.username,this.password.toCharArray(), "influx_test", "autogen");return influxDBClient.getWriteApi();}}4、封装用于查询的方法
@Componentpublic class InfluxUtil {/*** description: 通用查询* date: 2022/1/20 23:13* author: zhouhong* @param* @param null* @return*/public QueryResult query(String command, String database, InfluxDB influxDB) {Query query = new Query(command, database);return influxDB.query(query);}}5、新建需要写入的数据的实体类、需要返回的类（省略，具体参考github示例）InsertParams.java InfluxResult.java6、新建server层和impl实现类InfluxServiceImpl.java 如下：
/*** description: 时序数据库Impl* date: 2022/1/16 20:47* author: zhouhong*/@Service@Slf4jpublic class InfluxServiceImpl implements InfluxService {@Resource(name = "influxDbWriteApi")private WriteApi influxDbWriteApi;@Resource(name = "influxDBClient")private InfluxDB influxDBClient;@Autowiredprivate InfluxUtil influxUtil;@Overridepublic void insert(InsertParams insertParams) {influxDbWriteApi.writeMeasurement(WritePrecision.MS, insertParams);}@Overridepublic Object queryAll(InsertParams insertParams) {List<InfluxResult> list = new ArrayList<>();InfluxResult influxResult = new InfluxResult();String sql = "SELECT * FROM \"influx_test\" WHERE time > '2022-01-16'tz('Asia/Shanghai')";QueryResult queryResult = influxUtil.query(sql, "influx_test", influxDBClient);queryResult.getResults().get(0).getSeries().get(0).getValues().forEach(item -> {influxResult.setTime(item.get(0).toString());influxResult.setCurrent(item.get(1).toString());influxResult.setEnergyUsed(item.get(2).toString());influxResult.setPower(item.get(3).toString());influxResult.setVoltage(item.get(4).toString());list.add(influxResult);});return list;}@Overridepublic Object querySumByOneDay(InsertParams insertParams) {String sql = "SELECTSUM(voltage)FROM \"influx_test\" WHERE time > '2022-01-18'GROUP BY time(1d)tz('Asia/Shanghai')";QueryResult queryResult = influxUtil.query(sql, "influx_test", influxDBClient);return queryResult.getResults().get(0).getSeries().get(0);}}7、controller层 InfluxDbController.java（返回结果是封装过后的，详情见github示例）
@RestControllerpublic class InfluxDbController {@Autowiredprivate InfluxService influxService;/*** description: 时序数据库插入测试* date: 2022/1/16 23:00* author: zhouhong* @param* @param null* @return*/@PostMapping("/influxdb/insert")public ResponseData insert(@RequestBody InsertParams insertParams) {influxService.insert(insertParams);return new SuccessResponseData();}/*** description: 时序数据库查询全部数据测试* date: 2022/1/16 23:00* author: zhouhong* @param* @param null* @return*/@PostMapping("/influxdb/queryAll")public ResponseData query(@RequestBody InsertParams insertParams) {return new SuccessResponseData(influxService.queryAll(insertParams));}/*** description: 时序数据库按天查询当前电压总和测试* date: 2022/1/16 23:00* author: zhouhong* @param* @param null* @return*/@PostMapping("/influxdb/queryByOneDay")public ResponseData queryByOneDay(@RequestBody InsertParams insertParams) {return new SuccessResponseData(influxService.querySumByOneDay(insertParams));}}8、PostMan测试（注意需要先新建一个数据库---influx_test）8.1 插入测试 localhost:9998/influxdb/insert入参：
{"energyUsed":243.78,"power":54.50,"current":783.34,"voltage":44.09}返回：
{"success": true,"code": 200,"message": "请求成功","localizedMsg": "请求成功","data": null}8.2、查询全部（注意，这里返回结果我封装了一下）localhost:9998/influxdb/queryAll入参：
{}返回：
{"success": true,"code": 200,"message": "请求成功","localizedMsg": "请求成功","data": [{"energyUsed": "243.78","power": "54.5","current": "783.34","voltage": "44.09","time": "2022-01-20T23:44:00.626+08:00"},{"energyUsed": "243.78","power": "54.5","current": "783.34","voltage": "44.09","time": "2022-01-20T23:44:00.626+08:00"}]}8.3聚合查询（统计2022-01-18到现在，以天为单位每天的用电量之和） localhost:9998/influxdb/queryByOneDay 精度问题暂时没处理入参：{ }返回：
{"success": true,"code": 200,"message": "请求成功","localizedMsg": "请求成功","data": {"name": "influx_test","tags": null,"columns": ["time","sum"],"values": [["2022-01-18T00:00:00+08:00",null],["2022-01-19T00:00:00+08:00",null],["2022-01-20T00:00:00+08:00",481.07000000000005]]}}C、常见的查询SQL 后面加上 tz('Asia/Shanghai') 解决时区差1、查所指定时间之后的所有
SELECT * FROM "real_water_amount" where time> '2022-01-01' tz('Asia/Shanghai')

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2、查询平均值 mean()
SELECT mean(value) FROM "real_water_amount" where time> '2022-01-01' tz('Asia/Shanghai')

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3、查询最大最小值 max() min()
SELECT max(value) FROM "real_water_amount" where time> '2022-01-01' tz('Asia/Shanghai')

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4、按年、月、天、周、小时、分钟、秒统计
SELECT sum(value) FROM "real_water_amount" where time> '2022-01-01'group by time(1d)tz('Asia/Shanghai')

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5、按照列过滤
SELECT * FROM "real_water_amount" where time> '2022-01-01'andiotId = '8ecJY59UJd1jwPLBmJA5000000'

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二、InfluxDB2.x Docker安装以及与Boot整合A、Docker安装InfluxDB2.x1、安装：默认拉取最新版本docker run -d --name influxdb -p 8086:8086 influxdb2、查看docker ps -a3、浏览器访问 IP:8086 （注意：部署在远程服务器上需要开启8086端口安全组）设置账号密码

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从上到下为：账号（zhouhong）、密码(66668888)、确认密码(66668888)、组织(my_influxdb)、Buucket(Tom)；完了之后点击 Quick Start4、然后点击 Data -- > Buucket 就可以看到我们刚才创建的名字为 Tom 的 Buucket了

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5、点击 API Tokens 获取当前用户的 Token（整合时需要）

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6、设置Bucket的保存策略
【docker安装windows容器 Docker安装InfluxDB1.x和InfluxDB2.x以及与SpringBoot整合】

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准备工作完成，开始整合B、InfluxDB2.x与SpringBoot整合1、依赖
<dependency><groupId>com.influxdb</groupId><artifactId>influxdb-client-java</artifactId><version>4.0.0</version></dependency><dependency><groupId>org.influxdb</groupId><artifactId>influxdb-java</artifactId><version>2.20</version></dependency>2、yml配置文件
influx:influxUrl: 'http://XXX.XX.XXX.XX:8086'bucket: 'tom'org: 'my_influxdb'token: 'Rt23UemGI_cfS-lFDrurtjh46P1enfhrji-KrZYR04wUR1Yxw_oBCZPL6GmFYSDn20Q9gM_P9DIBhHc2RJjNkA=='3、配置类
@Setter@Getterpublic class InfluxBean{/*** 数据库url地址*/private String influxUrl;/*** 桶(表)*/private String bucket;/*** 组织*/private String org;/*** token*/private String token;/*** 数据库连接*/private InfluxDBClient client;/*** 构造方法*/public InfluxBean(String influxUrl, String bucket, String org, String token) {this.influxUrl = influxUrl;this.bucket = bucket;this.org = org;this.token = token;this.client = getClient();}/*** 获取连接*/private InfluxDBClient getClient() {if (client == null) {client= InfluxDBClientFactory.create(influxUrl, token.toCharArray());}return client;}/*** 写入数据(以秒为时间单位)*/public void write(Object object){try (WriteApi writeApi = client.getWriteApi()) {writeApi.writeMeasurement(bucket, org, WritePrecision.NS, object);}}/*** 读取数据*/public List<FluxTable> queryTable(String fluxQuery){return client.getQueryApi().query(fluxQuery, org);}}@Data@Configuration@ConfigurationProperties(prefix = "influx")public class InfluxConfig {/*** url地址*/private String influxUrl;/*** 桶(表)*/private String bucket;/*** 组织*/private String org;/*** token*/private String token;/*** 初始化bean*/@Bean(name = "influx")public InfluxBean InfluxBean() {return new InfluxBean(influxUrl, bucket, org, token);}}4、实现类
@Service@Slf4jpublic class InfluxServiceImpl implements InfluxService {@Resourceprivate InfluxBean influxBean;@Overridepublic void insert(InsertParams insertParams) {insertParams.setTime(Instant.now());influxBean.write(insertParams);}@Overridepublic List<InfluxResult> queue(){// 下面两个 private 方法赋值给 list 查询对应的数据List<FluxTable> list = queryInfluxAll();List<InfluxResult> results = new ArrayList<>();for (int i = 0; i < list.size(); i++) {for (int j = 0; j < list.get(i).getRecords().size(); j++) {InfluxResult influxResult = new InfluxResult();influxResult.setCurrent(list.get(i).getRecords().get(j).getValues().get("current").toString());influxResult.setEnergyUsed(list.get(i).getRecords().get(j).getValues().get("energyUsed").toString());influxResult.setPower(list.get(i).getRecords().get(j).getValues().get("power").toString());influxResult.setVoltage(list.get(i).getRecords().get(j).getValues().get("voltage").toString());influxResult.setTime(list.get(i).getRecords().get(j).getValues().get("_time").toString());System.err.println(list.get(i).getRecords().get(j).getValues().toString());results.add(influxResult);}}return results;}/*** description: 查询一小时内的InsertParams所有数据* date: 2022/1/21 13:44* author: zhouhong* @param* @param null* @return*/private List<FluxTable> queryInfluxAll(){String query = " from(bucket: \"tom\")" +"|> range(start: -60m, stop: now())" +"|> filter(fn: (r) => r[\"_measurement\"] == \"influx_test\")" +"|> pivot( rowKey:[\"_time\"], columnKey: [\"_field\"], valueColumn: \"_value\" )";return influxBean.queryTable(query);}/*** description: 根据某一个字段的值过滤(查询用电量 energyUsed 为 322 的那条记录)* date: 2022/1/21 12:44* author: zhouhong* @param* @param null* @return*/public List<FluxTable> queryFilterByEnergyUsed(){String query = " from(bucket: \"tom\")" +"|> range(start: -60m, stop: now())" +"|> filter(fn: (r) => r[\"_measurement\"] == \"influx_test\")" +"|> filter(fn: (r) => r[\"energyUsed\"] == \"322\")" +"|> pivot( rowKey:[\"_time\"], columnKey: [\"_field\"], valueColumn: \"_value\" )";return influxBean.queryTable(query);}}C、测试1、插入 localhost:9998/inlfuxdb/insert入参：
{"energyUsed":"23.12","power":"321.60","current":"782.72","voltage":"67.43"}返回：{"success": true,"code": 200,"message": "请求成功","localizedMsg": "请求成功","data": null}2、查询所有入参：{}返回：
{"success": true,"code": 200,"message": "请求成功","localizedMsg": "请求成功","data": [{"energyUsed": "23.12","power": "321.60","current": "782.72","voltage": "67.43","time": "2022-01-20T17:51:01.819Z"},{"energyUsed": "243.78","power": "541.50","current": "32.34","voltage": "89.09","time": "2022-01-20T17:33:47.246Z"}]}D、Flux常见查询语句1、指定数据源：from(bucket:"tom")指定时间范围：使用管道转发运算符 ( |>) 将数据从数据源通过管道传输到range() 函数，该函数指定查询的时间范围。它接受两个参数：start和stop 。范围可以是使用相对负持续时间或使用绝对时间
//使用绝对时间from(bucket:"tom")|> range(start: 2022-01-05T23:30:00Z, stop: 2022-01-21T00:00:00Z) //过去十五天的数据from(bucket:"tom")|> range(start: -15d)

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2、数据过滤将范围数据传递到filter()函数中，以根据数据属性或列缩小结果范围// 根据 _measurement 和 _field 过滤from(bucket:"tom")|> range(start: -15d)|> filter(fn: (r) =>r._measurement == "influx_test" andr._field == "power" andr.energyUsed == "23.12")

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3、数据转换使用函数，将数据聚合为平均值、下采样数据等from(bucket:"tom")|> range(start: -15d)|> filter(fn: (r) =>r._measurement == "influx_test")|> window(every: 10m)from(bucket:"tom")|> range(start: -15d)|> filter(fn: (r) =>r._measurement == "influx_test")|> window(every: 10m)|> mean()其他查询函数请查看官网：https://docs.influxdata.com/flux/v0.x/stdlib/universe/输了不可怕，大不了从头再来，我们还年轻---周红