Docker版Grafana整合InfluxDB看這一篇就夠了（2020全網最詳細教程）

本文分為4段為您詳細講解Docker版Grafana整合influxdb監控資料

docker安裝

解除安裝

如果之前安裝過Docker需要解除安裝可以參照如下命令

# 列出當前docker相關的安裝包
$ yum list installed|grep docker
containerd.io.x86_64                 1.3.7-3.1.el7                  @docker-ce-stable
docker-ce.x86_64                     3:19.03.13-3.el7               @docker-ce-stable
docker-ce-cli.x86_64                 1:19.03.13-3.el7               @docker-ce-stable

# 解除安裝對應的包
$ yum -y remove containerd.io.x86_64
$ yum -y remove docker-ce.x86_64
$ yum -y remove docker-ce-cli.x86_64 

安裝

注意：且Docker 要求作業系統必須為64位，且centos核心版本為3.1及以上

• 檢視系統核心

  $ uname -r
  3.10.0-1062.el7.x86_6
  # 我這裡高於3.1
  

• 保證yum包是最新

  # 使用root執行，更新到最新
  $ yum update
  

• 列出可安裝的docker包

  # 列出可以按照的docker包
  $ yum list docker-ce --showduplicates | sort -r
  

• 安裝

  • 指定版本安裝

    $ yum list docker-ce.x86_64  --showduplicates | sort -r
    

  • 直接安裝最新版

    $ yum install docker-ce -y
    

• 檢視當前版本

  $ docker version
  
  Client: Docker Engine - Community
   Version:           19.03.13
   API version:       1.40
   Go version:        go1.13.15
   Git commit:        4484c46d9d
   Built:             Wed Sep 16 17:03:45 2020
   OS/Arch:           linux/amd64
   Experimental:      false
  Cannot connect to the Docker daemon at unix:///var/run/docker.sock. Is the docker daemon running?
  # 此處需要重啟
  

• 不能連線到Docker daemon異常

  裝完後使用docker命令後會提示異常
  Cannot connect to the Docker daemon at unix:///var/run/docker.sock. Is the docker daemon running?
  需要重啟下docker
  

• 重啟

  $ service docker restart
  

• 配置開機啟動

  $ systemctl enable docker
  

國內映象配置

1. 找到/etc/docker目錄下的daemon.json檔案進行編輯，輸入如下內容

   {
     "registry-mirrors": ["https://9cpn8tt6.mirror.aliyuncs.com"]
   }
   

2. 如果沒有該檔案，可自行建立，也可以使用如下命令

   tee /etc/docker/daemon.json <<-'EOF'
   {
     "registry-mirrors": ["https://9cpn8tt6.mirror.aliyuncs.com"]
   }
   EOF
   

3. 重啟docker

Docker整合influxDB

前面我們已經學習了Docker的安裝和相關命令，接下來，我們只講解influxdb的內容

InfluxDB是一個由InfluxData開發的開源時序型資料。它由Go寫成，著力於高效能地查詢與儲存時序型資料。InfluxDB被廣泛應用於儲存系統的監控資料，IoT行業的實時資料等場景。

influxDB介紹

InfluxDB（時序資料庫），常用的一種使用場景：監控資料統計。每毫秒記錄一下電腦記憶體的使用情況，然後就可以根據統計的資料，利用圖形化介面（InfluxDB V1一般配合Grafana）製作記憶體使用情況的折線圖；

可以理解為按時間記錄一些資料（常用的監控資料、埋點統計資料等），然後製作圖表做統計；

與傳統資料庫中的名詞做比較

influxDB中的名詞	傳統資料庫中的概念
database	資料庫
measurement	資料庫中的表
points	表裡面的一行資料

InfluxDB中獨有的一些概念
Point由時間戳（time）、資料（field）、標籤（tags）組成。

Point屬性	傳統資料庫中的概念
time	每個資料記錄時間，是資料庫中的主索引(會自動生成)
fields	各種記錄值（沒有索引的屬性）也就是記錄的值：溫度， 溼度
tags	各種有索引的屬性：地區，海拔

influxDB安裝

• 拉取最新版映象

  # 拉取最新版映象
  $ docker pull influxdb
  # 檢視映象
  $ docker images✨
  

• 使用映象建立容器

  # 使用映象建立容器
  $ docker run -d -p  8083:8083 -p 8086:8086 --name myinfluxdb influxdb
  	-d 讓容器在後臺執行 
  	-p 8083:8083 將容器的 8083 埠對映到主機的 8083 埠
  	–-name 容器的名字，隨便取，但是必須唯一
  

• 開放防火牆埠

  $ firewall-cmd --zone=public --add-port=8083/tcp --permanent
  $ firewall-cmd --zone=public --add-port=8086/tcp --permanent
  $ firewall-cmd --reload
  

• 停止容器

  $ docker stop myinfluxdb
  

• 移除容器

  # 移除的容器必須是已經停止的
  $ docker rm myinfluxdb
  

• 檢視容器列表

  # 只檢視正在執行的
  $ docker ps
  
  # 檢視所有的
  $ docker ps -a
  

• 進入容器內部

  # 該容器必須已經執行，才能進入
  $ docker exec -it myinfluxdb /bin/bash
  

influxDB配置

使用名進入到myinfluxdb容器內部後，我們來做一點小小的配置

1. 進入influxdb命令互動模式，類似於mysql的命令列

   # 直接輸入influx
   $ influx
   Connected to http://localhost:8086 version 1.8.3
   InfluxDB shell version: 1.8.3
   > 
   
   
   # 如果上述報錯，採用下面這種方式，輸入/usr/bin/influx
   $ /usr/bin/influx
   

2. 新增資料庫

   # 檢視現有資料庫
   > show databases;
   name: databases
   name
   ----
   _internal
   
   # 建立資料庫
   > create database mytest
   
   # 再次檢視你會發現有2個庫了
   > show databases;
   name: databases
   name
   ----
   _internal
   mytest
   
   # 使用資料庫
   > use mytest
   
   # 檢視使用者
   > show users;
   user admin
   ---- -----
   

3. 建立一個使用者

   > CREATE USER "master" WITH PASSWORD 'abcd1234' WITH ALL PRIVILEGES
   > exit 退出
   

4. influxdb預設沒有校驗許可權，修改influxdb.conf檔案

   # 在當前容器內執行
   $ vim /etc/influxdb/influxdb.conf
   # 此時你會發現vim命令不存在
   bash: vim: command not found
   

5. 安裝vim命令

   # 在當前容器類執行（此步驟時間會比較長）
   $ apt-get update
   $ apt-get install vim
   

6. 再次修改influxdb.conf檔案

   # 修改[http]處的auth-enabled屬性為true
   [http]
   ...
   auth-enabled = true
   

   注意有的版本配置檔案非常簡單，只有如下幾個配置：

   [meta]
     dir = "/var/lib/influxdb/meta"
   
   [data]
     dir = "/var/lib/influxdb/data"
     engine = "tsm1"
     wal-dir = "/var/lib/influxdb/wal"
   

   我這邊修改完後的配置檔案全內容如下：

   [meta]
     dir = "/var/lib/influxdb/meta"
   
   [data]
     dir = "/var/lib/influxdb/data"
     engine = "tsm1"
     wal-dir = "/var/lib/influxdb/wal"
   
   [http]
     enabled = true  
     bind-address = ":8086"  
     auth-enabled = true  # ✨ 此處預設是關閉的需要開啟，因為前面我們配置的使用者名稱密碼，所以需要開啟
     log-enabled = true  
     write-tracing = false  
     pprof-enabled = false  
     https-enabled = false 
   

   退出容器，重新啟動注意不要改錯，改錯了，容器就無法再起來了

   $ docker restart 
   

   其實最詳細的配置檔案如下：**

   ### Welcome to the InfluxDB configuration file.
   
   # Once every 24 hours InfluxDB will report usage data to usage.influxdata.com
   # The data includes a random ID, os, arch, version, the number of series and other
   # usage data. No data from user databases is ever transmitted.
   # Change this option to true to disable reporting.
   reporting-disabled = false
   
   # we'll try to get the hostname automatically, but if it the os returns something
   # that isn't resolvable by other servers in the cluster, use this option to
   # manually set the hostname
   # hostname = "localhost"
   
   ###
   ### [meta]
   ###
   ### Controls the parameters for the Raft consensus group that stores metadata
   ### about the InfluxDB cluster.
   ###
   
   [meta]
     # Where the metadata/raft database is stored
     dir = "/var/lib/influxdb/meta"
   
     retention-autocreate = true
   
     # If log messages are printed for the meta service
     logging-enabled = true
     pprof-enabled = false
   
     # The default duration for leases.
     lease-duration = "1m0s"
   
   ###
   ### [data]
   ###
   ### Controls where the actual shard data for InfluxDB lives and how it is
   ### flushed from the WAL. "dir" may need to be changed to a suitable place
   ### for your system, but the WAL settings are an advanced configuration. The
   ### defaults should work for most systems.
   ###
   
   [data]
     # Controls if this node holds time series data shards in the cluster
     enabled = true
   
     dir = "/var/lib/influxdb/data"
   
     # These are the WAL settings for the storage engine >= 0.9.3
     wal-dir = "/var/lib/influxdb/wal"
     wal-logging-enabled = true
     
     # Trace logging provides more verbose output around the tsm engine. Turning 
     # this on can provide more useful output for debugging tsm engine issues.
     # trace-logging-enabled = false
   
     # Whether queries should be logged before execution. Very useful for troubleshooting, but will
     # log any sensitive data contained within a query.
     # query-log-enabled = true
   
     # Settings for the TSM engine
   
     # CacheMaxMemorySize is the maximum size a shard's cache can
     # reach before it starts rejecting writes.
     # cache-max-memory-size = 524288000
   
     # CacheSnapshotMemorySize is the size at which the engine will
     # snapshot the cache and write it to a TSM file, freeing up memory
     # cache-snapshot-memory-size = 26214400
   
     # CacheSnapshotWriteColdDuration is the length of time at
     # which the engine will snapshot the cache and write it to
     # a new TSM file if the shard hasn't received writes or deletes
     # cache-snapshot-write-cold-duration = "1h"
   
     # MinCompactionFileCount is the minimum number of TSM files
     # that need to exist before a compaction cycle will run
     # compact-min-file-count = 3
   
     # CompactFullWriteColdDuration is the duration at which the engine
     # will compact all TSM files in a shard if it hasn't received a
     # write or delete
     # compact-full-write-cold-duration = "24h"
   
     # MaxPointsPerBlock is the maximum number of points in an encoded
     # block in a TSM file. Larger numbers may yield better compression
     # but could incur a performance penalty when querying
     # max-points-per-block = 1000
   
   ###
   ### [coordinator]
   ###
   ### Controls the clustering service configuration.
   ###
   
   [coordinator]
     write-timeout = "10s"
     max-concurrent-queries = 0
     query-timeout = "0"
     log-queries-after = "0"
     max-select-point = 0
     max-select-series = 0
     max-select-buckets = 0
   
   ###
   ### [retention]
   ###
   ### Controls the enforcement of retention policies for evicting old data.
   ###
   
   [retention]
     enabled = true
     check-interval = "30m"
   
   ###
   ### [shard-precreation]
   ###
   ### Controls the precreation of shards, so they are available before data arrives.
   ### Only shards that, after creation, will have both a start- and end-time in the
   ### future, will ever be created. Shards are never precreated that would be wholly
   ### or partially in the past.
   
   [shard-precreation]
     enabled = true
     check-interval = "10m"
     advance-period = "30m"
   
   ###
   ### Controls the system self-monitoring, statistics and diagnostics.
   ###
   ### The internal database for monitoring data is created automatically if
   ### if it does not already exist. The target retention within this database
   ### is called 'monitor' and is also created with a retention period of 7 days
   ### and a replication factor of 1, if it does not exist. In all cases the
   ### this retention policy is configured as the default for the database.
   
   [monitor]
     store-enabled = true # Whether to record statistics internally.
     store-database = "_internal" # The destination database for recorded statistics
     store-interval = "10s" # The interval at which to record statistics
   
   ###
   ### [admin]
   ###
   ### Controls the availability of the built-in, web-based admin interface. If HTTPS is
   ### enabled for the admin interface, HTTPS must also be enabled on the [http] service.
   ###
   
   [admin]
     enabled = true
     bind-address = ":8083"
     https-enabled = false
     https-certificate = "/etc/ssl/influxdb.pem"
   
   ###
   ### [http]
   ###
   ### Controls how the HTTP endpoints are configured. These are the primary
   ### mechanism for getting data into and out of InfluxDB.
   ###
   
   [http]
     enabled = true
     bind-address = ":8086"
     auth-enabled = true
     log-enabled = true
     write-tracing = false
     pprof-enabled = false
     https-enabled = false
     https-certificate = "/etc/ssl/influxdb.pem"
     ### Use a separate private key location.
     # https-private-key = ""
     max-row-limit = 10000
     realm = "InfluxDB"
   
   ###
   ### [subsciber]
   ###
   ### Controls the subscriptions, which can be used to fork a copy of all data
   ### received by the InfluxDB host.
   ###
   
   [subsciber]
     enabled = true
     http-timeout = "30s"
   
   
   ###
   ### [[graphite]]
   ###
   ### Controls one or many listeners for Graphite data.
   ###
   
   [[graphite]]
     enabled = false
     # database = "graphite"
     # bind-address = ":2003"
     # protocol = "tcp"
     # consistency-level = "one"
   
     # These next lines control how batching works. You should have this enabled
     # otherwise you could get dropped metrics or poor performance. Batching
     # will buffer points in memory if you have many coming in.
   
     # batch-size = 5000 # will flush if this many points get buffered
     # batch-pending = 10 # number of batches that may be pending in memory
     # batch-timeout = "1s" # will flush at least this often even if we haven't hit buffer limit
     # udp-read-buffer = 0 # UDP Read buffer size, 0 means OS default. UDP listener will fail if set above OS max.
   
     ### This string joins multiple matching 'measurement' values providing more control over the final measurement name.
     # separator = "."
   
     ### Default tags that will be added to all metrics.  These can be overridden at the template level
     ### or by tags extracted from metric
     # tags = ["region=us-east", "zone=1c"]
   
     ### Each template line requires a template pattern.  It can have an optional
     ### filter before the template and separated by spaces.  It can also have optional extra
     ### tags following the template.  Multiple tags should be separated by commas and no spaces
     ### similar to the line protocol format.  There can be only one default template.
     # templates = [
     #   "*.app env.service.resource.measurement",
     #   # Default template
     #   "server.*",
     # ]
   
   ###
   ### [collectd]
   ###
   ### Controls one or many listeners for collectd data.
   ###
   
   [[collectd]]
     enabled = false
     # bind-address = ""
     # database = ""
     # typesdb = ""
   
     # These next lines control how batching works. You should have this enabled
     # otherwise you could get dropped metrics or poor performance. Batching
     # will buffer points in memory if you have many coming in.
   
     # batch-size = 1000 # will flush if this many points get buffered
     # batch-pending = 5 # number of batches that may be pending in memory
     # batch-timeout = "1s" # will flush at least this often even if we haven't hit buffer limit
     # read-buffer = 0 # UDP Read buffer size, 0 means OS default. UDP listener will fail if set above OS max.
   
   ###
   ### [opentsdb]
   ###
   ### Controls one or many listeners for OpenTSDB data.
   ###
   
   [[opentsdb]]
     enabled = false
     # bind-address = ":4242"
     # database = "opentsdb"
     # retention-policy = ""
     # consistency-level = "one"
     # tls-enabled = false
     # certificate= ""
     # log-point-errors = true # Log an error for every malformed point.
   
     # These next lines control how batching works. You should have this enabled
     # otherwise you could get dropped metrics or poor performance. Only points
     # metrics received over the telnet protocol undergo batching.
   
     # batch-size = 1000 # will flush if this many points get buffered
     # batch-pending = 5 # number of batches that may be pending in memory
     # batch-timeout = "1s" # will flush at least this often even if we haven't hit buffer limit
   
   ###
   ### [[udp]]
   ###
   ### Controls the listeners for InfluxDB line protocol data via UDP.
   ###
   
   [[udp]]
     enabled = false
     # bind-address = ""
     # database = "udp"
     # retention-policy = ""
   
     # These next lines control how batching works. You should have this enabled
     # otherwise you could get dropped metrics or poor performance. Batching
     # will buffer points in memory if you have many coming in.
   
     # batch-size = 1000 # will flush if this many points get buffered
     # batch-pending = 5 # number of batches that may be pending in memory
     # batch-timeout = "1s" # will flush at least this often even if we haven't hit buffer limit
     # read-buffer = 0 # UDP Read buffer size, 0 means OS default. UDP listener will fail if set above OS max.
   
     # set the expected UDP payload size; lower values tend to yield better performance, default is max UDP size 65536
     # udp-payload-size = 65536
   
   ###
   ### [continuous_queries]
   ###
   ### Controls how continuous queries are run within InfluxDB.
   ###
   
   [continuous_queries]
     log-enabled = true
     enabled = true
     # run-interval = "1s" # interval for how often continuous queries will be checked if they need to run
   

7. 退出容器，重新啟動注意不要改錯，改錯了，容器就無法再起來了

   $ docker restart myinfluxdb
   

8. 再次進入容器，並使用命令進行influx操作

   root@5f1bb39363e6:/# influx     
   Connected to http://localhost:8086 version 1.8.3
   InfluxDB shell version: 1.8.3
   > show users
   ERR: unable to parse authentication credentials
   Warning: It is possible this error is due to not setting a database.
   Please set a database with the command "use <database>".
   > 
   

   上述提示許可權校驗錯誤，接下來我們exit退出當前influx互動（不要退出容器），再次使用使用者密碼登入

   root@5f1bb39363e6:/# influx -username 'master' -password 'abcd1234'
   Connected to http://localhost:8086 version 1.8.3
   InfluxDB shell version: 1.8.3
   > show users
   user   admin
   ----   -----
   master true
   

   上述登入成功，並且能夠使用show users語句

先切換到我們建立的mytest資料庫

> use mytest

資料插入

由於InfluxDB的無結構（schemeless）特性，我們不需要預先建表，直接use [ database ]後就可以寫入資料了。舉個例子。

INSERT cpu,host=serverA,region=us_west value=0.64
 
INSERT temperature,machine=unit42,type=assembly external=25,internal=37

讀資料

SELECT "host", "region", "value" FROM "cpu"
SELECT * FROM "temperature"

-- measurement都可以用正則表示，下面表示讀一個db下的所有measurement的資料
SELECT * FROM /.*/
-- 配上where條件
SELECT "region", "value" FROM "cpu" where "host" = "server1"

客戶端工具

下載地址：
連結：https://pan.baidu.com/s/1FBFRc2fPkmDoHDYjdNgntA
提取碼：s4ut

常用InfluxQL

-- 檢視所有的資料庫
show databases;
-- 使用特定的資料庫
use database_name;
-- 檢視所有的measurement
show measurements;
-- 查詢10條資料
select * from measurement_name limit 10;
-- 資料中的時間欄位預設顯示的是一個納秒時間戳，改成可讀格式
precision rfc3339; -- 之後再查詢，時間就是rfc3339標準格式
-- 或可以在連線資料庫的時候，直接帶該引數
influx -precision rfc3339
-- 檢視一個measurement中所有的tag key 
show tag keys
-- 檢視一個measurement中所有的field key 
show field keys
-- 檢視一個measurement中所有的儲存策略(可以有多個，一個標識為default)
show retention policies;

程式碼批量插入

新建Java的SpringBoot專案，專案地址GitHub：

pom.xml

<parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>2.2.5.RELEASE</version>
        <relativePath/>
    </parent>
    <groupId>com.it235</groupId>
    <artifactId>influxdb</artifactId>
    <version>0.0.1-SNAPSHOT</version>

    <properties>
        <java.version>1.8</java.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <dependency>
            <groupId>org.influxdb</groupId>
            <artifactId>influxdb-java</artifactId>
            <version>2.15</version>
        </dependency>
    </dependencies>

application.yml

server:
  port: 8010
spring:
  influx:
    url: http://192.168.1.31:8086
    user: master
    username: master
    password: abcd1234
    database: mytest
    retention_policy: default
    retention_policy_time: 30d

Java程式碼

import lombok.extern.slf4j.Slf4j;
import org.influxdb.InfluxDB;
import org.influxdb.dto.Point;
import org.influxdb.dto.Query;
import org.influxdb.dto.QueryResult;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Component;

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

/**
 * @Author: it235.com
 * @Date: 2020-10-10
 * @Description: 工具支援類
 */
@Slf4j
@Component
public class InfluxDBSupport {
    /**
     * 資料儲存策略
     */
    @Value("${spring.influx.retentionPolicy:}")
    private String retentionPolicy;
    /**
     * 資料儲存策略中資料儲存時間
     */
    @Value("${spring.influx.retentionPolicyTime:}")
    private String retentionPolicyTime;

    @Value("${spring.influx.database:}")
    private String database;

    /**
     * InfluxDB例項
     */
    @Autowired
    private InfluxDB influxDB;

    public InfluxDBSupport() {
        // autogen預設的資料儲存策略
        this.retentionPolicy = retentionPolicy == null || "".equals(retentionPolicy) ? "autogen" : retentionPolicy;
        this.retentionPolicyTime = retentionPolicyTime == null || "".equals(retentionPolicy) ? "30d" : retentionPolicyTime;
    }

    /**
     * 設定資料儲存策略 defalut 策略名 /database 資料庫名/ 30d 資料儲存時限30天/ 1 副本個數為1/ 結尾DEFAULT
     * 表示 設為預設的策略
     */
    public void createRetentionPolicy() {
        String command = String.format("CREATE RETENTION POLICY \"%s\" ON \"%s\" DURATION %s REPLICATION %s DEFAULT",
                retentionPolicy, database, retentionPolicyTime, 1);
        this.query(command);
    }

    /**
     * 查詢
     *
     * @param command 查詢語句
     * @return
     */
    public QueryResult query(String command) {
        return influxDB.query(new Query(command, database));
    }

    /**
     * 插入
     *
     * @param measurement 表
     * @param tags        標籤
     * @param fields      欄位
     */
    public void insert(String measurement, Map<String, String> tags, Map<String, Object> fields) {
        Point.Builder builder = Point.measurement(measurement);
        // 納秒時會出現異常資訊：partial write: points beyond retention policy dropped=1
        // builder.time(System.nanoTime(), TimeUnit.NANOSECONDS);
        builder.time(System.currentTimeMillis(), TimeUnit.MILLISECONDS);
        builder.tag(tags);
        builder.fields(fields);

        log.info("influxDB insert data:[{}]", builder.build().toString());
        influxDB.write(database, "", builder.build());
    }

import lombok.extern.slf4j.Slf4j;
import org.influxdb.dto.QueryResult;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

import java.util.HashMap;
import java.util.Map;

/**
 * @Author: it235.com
 * @Date: 2020-10-10
 * @Description: 啟動主程式
 */
@Slf4j
@SpringBootApplication
public class InfluxdbDemoApplication implements CommandLineRunner {

    public static void main(String[] args) {
        SpringApplication.run(InfluxdbDemoApplication.class, args);
    }

    @Autowired
    private InfluxDBSupport influxDBSupport;

    @Override
    public void run(String... args) throws Exception {
        //插入測試
        insertTest();

        //查詢測試
        //querTest();
    }

    /**
     * 插入測試
     * @throws InterruptedException
     */
    public void insertTest() throws InterruptedException {
        Map<String, String> tagsMap = new HashMap<>();
        Map<String, Object> fieldsMap = new HashMap<>();
        System.out.println("influxDB start time :" + System.currentTimeMillis());
        int i = 0;
        for (; ; ) {
            Thread.sleep(100);
            tagsMap.put("value", String.valueOf(i % 10));
            tagsMap.put("host", "https://www.it235.com");
            tagsMap.put("region", "west" + (i % 5));
            fieldsMap.put("count", i % 5);
            influxDBSupport.insert("cpu_test", tagsMap, fieldsMap);
            i++;
        }
    }

    /**
     * 查詢測試
     */
    public void querTest(){
        QueryResult rs = influxDBSupport.query("select * from usage");
        log.info("query result => {}", rs);
        if (!rs.hasError() && !rs.getResults().isEmpty()) {
            rs.getResults().forEach(System.out::println);
        }
    }

}

啟動程式測試，觀看控制檯可以看到在批量插入資料，此時也可以去influxdb中去看看

Docker安裝Grafana整合influxDB

Grafana介紹

Grafana安裝

前面我們已經學習了Docker的安裝和相關命令，接下來，我們只講解Grafana的內容

• 映象拉取

  $ docker pull grafana/grafana
  $ docker images
  

• 安裝配置

  $ docker run -d -p 3000:3000 --name=it35graf grafana/grafana
  $ docker ps -a
  

• 開放防火牆埠

  $ firewall-cmd --zone=public --add-port=3000/tcp --permanent
  $ firewall-cmd --reload
  

• 瀏覽器訪問http://ip:3000，使用者名稱密碼預設：admin

• 到此Grafana安裝完成

配置influxDB資料來源

建立Dashboard

dashboard是Grafana種用於展示呈現的工具，我們可以將influxdb中的資料展示到dashboard中

注意上述選擇的表一定是要有資料的，否則看不到效果

資料整合測試

• 開啟程式碼批量插入程式

• 觀看Grafana皮膚中的效果

到此Docker版的Grafana+influxdb就整合完成了。