本文提供简单的Springboot集成influxDB，实现基础的增删改查
package com.sinochem.it.influx.config;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;
import org.influxdb.InfluxDB;
import org.influxdb.InfluxDB.ConsistencyLevel;
import org.influxdb.InfluxDBFactory;
import org.influxdb.dto.BatchPoints;
import org.influxdb.dto.Point;
import org.influxdb.dto.Point.Builder;
import org.influxdb.dto.Pong;
import org.influxdb.dto.Query;
import org.influxdb.dto.QueryResult;
public class InfluxDBConnection {
// 用户名
private String username;
// 密码
private String password;
// 连接地址
private String openurl;
// 数据库
private String database;
// 保留策略
private String retentionPolicy;
private InfluxDB influxDB;
public InfluxDBConnection(String username, String password, String openurl, String database,
String retentionPolicy) {
this.username = username;
this.password = password;
this.openurl = openurl;
this.database = database;
this.retentionPolicy = retentionPolicy == null || retentionPolicy.equals("") ? "autogen" : retentionPolicy;
influxDbBuild();
}
/**
* 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);
}
/**
* 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;
}
/**
* 连接时序数据库 ，若不存在则创建
*
* @return
*/
public InfluxDB influxDbBuild() {
if (influxDB == null) {
influxDB = InfluxDBFactory.connect(openurl, username, password);
}
try {
// if (!influxDB.databaseExists(database)) {
// influxDB.createDatabase(database);
// }
} 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;
}
/**
* 创建自定义保留策略
*
* @param policyName
* 策略名
* @param duration
* 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 policyName, String duration, int replication, Boolean isDefault) {
String sql = String.format("CREATE RETENTION POLICY \"%s\" ON \"%s\" DURATION %s REPLICATION %s ", policyName,
database, duration, replication);
if (isDefault) {
sql = sql + " DEFAULT";
}
this.query(sql);
}
/**
* 创建默认的保留策略
*
* @param 策略名：default，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",
"default", database, "30d", 1);
this.query(command);
}
/**
* 查询
*
* @param command
* 查询语句
* @return
*/
public QueryResult query(String command) {
return influxDB.query(new Query(command, database));
}
/**
* 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(database, retentionPolicy, builder.build());
}
public void insert(String measurement, Map<String, String> tags, Map<String, Object> fields) {
Builder builder = Point.measurement(measurement);
builder.tag(tags);
builder.fields(fields);
influxDB.write(database, retentionPolicy, builder.build());
}
/**
* 批量写入测点
*
* @param batchPoints
*/
public void batchInsert(BatchPoints batchPoints) {
influxDB.write(batchPoints);
// influxDB.enableGzip();
// influxDB.enableBatch(2000,100,TimeUnit.MILLISECONDS);
// 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,
final List<String> records) {
influxDB.write(database, retentionPolicy, consistency, records);
}
/**
* 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, database));
return result.getError();
}
/**
* 关闭数据库
*/
public void close() {
influxDB.close();
}
/**
* 构建Point
*
* @param measurement
* @param time
* @param fields
* @return
*/
public Point pointBuilder(String measurement, long time, Map<String, String> tags, Map<String, Object> fields) {
Point point = Point.measurement(measurement).time(time, TimeUnit.MILLISECONDS).tag(tags).fields(fields).build();
return point;
}
}
测试类
package com.sinochem.it.influx;
import com.sinochem.it.influx.config.InfluxDBConnection;
import org.influxdb.dto.QueryResult;
import org.junit.jupiter.api.Test;
import org.springframework.boot.test.context.SpringBootTest;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;
@SpringBootTest
class ZhnyInfluxApplicationTests {
@Test
void contextLoads() {
InfluxDBConnection influxDBConnection = new InfluxDBConnection("root", "SX&Root2021@ZHNY#.M", "http://10.156.130.234:39100", "testDB", "");
for (int i = 0; i <1000 ; i++) {
HashMap<String, String> targs = new HashMap<>();
targs.put("host","serverB");
HashMap<String, Object> fields = new HashMap<>();
fields.put("region","us_wwww");
fields.put("time",System.currentTimeMillis());
fields.put("value",System.currentTimeMillis());
fields.put("f1","0.8118");
fields.put("f2","0.8118");
influxDBConnection.insert("cpu",targs,fields);
}
QueryResult results = influxDBConnection
.query("SELECT count(1) FROM cpu");
//results.getResults()是同时查询多条SQL语句的返回值，此处我们只有一条SQL，所以只取第一个结果集即可。
QueryResult.Result oneResult = results.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 && 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……
}
}
}
}
}
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