java使用influxDB时序数据库

<!-- 引入influxdb依赖 -->
 <dependency>
 <groupId>org.influxdb</groupId>
 <artifactId>influxdb-java</artifactId>
 <version>2.8</version>
 </dependency>

package com.mt.core.util;
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;
import lombok.Data;

/**
 * InfluxDB数据库连接操作类
 *
 * @author Simon
 */

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());
 }

 /**
 * 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;
 }

}

public static void main(String[] args) {
 InfluxDBConnection influxDBConnection = new InfluxDBConnection("root", "Password01", "localhost", "devops", "tk_test");
 QueryResult results = influxDBConnection
 .query("SELECT * FROM mt order by time desc limit 1000");
 //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。
 Result oneResult = results.getResults().get(0);
 if (oneResult.getSeries() != null) {
 List<List<Object>> valueList = oneResult.getSeries().stream().map(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……
 }
 }
 }
 }

public static void main(String[] args) {
 InfluxDBConnection influxDBConnection = new InfluxDBConnection("root", "Password01", "localhost", "devops", "tk_test");
 Map<String, String> tags = new HashMap<String, String>();
 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
 influxDBConnection.insert("表名", tags, fields, System.currentTimeMillis(), TimeUnit.MILLISECONDS);
 }