初始化
This commit is contained in:
@@ -0,0 +1,34 @@
|
||||
package com.njcn.influxdb.config;
|
||||
|
||||
import com.njcn.influxdb.utils.InfluxDbUtils;
|
||||
import org.springframework.beans.factory.annotation.Value;
|
||||
import org.springframework.context.annotation.Bean;
|
||||
import org.springframework.context.annotation.Configuration;
|
||||
|
||||
/**
|
||||
* 类的介绍：
|
||||
*
|
||||
* @author xuyang
|
||||
* @version 1.0.0
|
||||
* @createTime 2021/12/10 10:48
|
||||
*/
|
||||
@Configuration
|
||||
public class InfluxDbConfig {
|
||||
|
||||
@Value("${spring.influx.url:''}")
|
||||
private String influxDBUrl;
|
||||
|
||||
@Value("${spring.influx.user:''}")
|
||||
private String userName;
|
||||
|
||||
@Value("${spring.influx.password:''}")
|
||||
private String password;
|
||||
|
||||
@Value("${spring.influx.database:''}")
|
||||
private String database;
|
||||
|
||||
@Bean
|
||||
public InfluxDbUtils influxDbUtils() {
|
||||
return new InfluxDbUtils(userName, password, influxDBUrl, database, "autogen");
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,324 @@
|
||||
package com.njcn.influxdb.utils;
|
||||
|
||||
|
||||
import cn.hutool.core.util.StrUtil;
|
||||
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.influxdb.dto.Point.Builder;
|
||||
|
||||
import java.time.Instant;
|
||||
import java.time.LocalDateTime;
|
||||
import java.time.ZoneId;
|
||||
import java.time.format.DateTimeFormatter;
|
||||
import java.util.ArrayList;
|
||||
import java.util.HashMap;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.concurrent.TimeUnit;
|
||||
|
||||
/**
|
||||
* 类的介绍：
|
||||
*
|
||||
* @author xuyang
|
||||
* @version 1.0.0
|
||||
* @createTime 2021/11/16 10:20
|
||||
*/
|
||||
@Slf4j
|
||||
@Data
|
||||
public class InfluxDbUtils {
|
||||
|
||||
/**用户名*/
|
||||
private String username;
|
||||
/**密码*/
|
||||
private String password;
|
||||
/**链接地址*/
|
||||
private String openurl;
|
||||
/**数据库*/
|
||||
private String dbName;
|
||||
/**保留策略*/
|
||||
private String retentionPolicy;
|
||||
|
||||
private InfluxDB influxDB;
|
||||
|
||||
public InfluxDbUtils(String username, String password, String url, String dbName, String retentionPolicy) {
|
||||
this.username = username;
|
||||
this.password = password;
|
||||
this.openurl = url;
|
||||
this.dbName = dbName;
|
||||
this.retentionPolicy = retentionPolicy == null || retentionPolicy.equals("") ? "autogen" : retentionPolicy;
|
||||
influxDbBuild();
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* 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;
|
||||
}
|
||||
|
||||
/**
|
||||
* 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);
|
||||
}
|
||||
|
||||
/**
|
||||
* 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) {
|
||||
time = time + 28800000;
|
||||
builder.time(time, timeUnit);
|
||||
}
|
||||
influxDB.write(dbName, retentionPolicy, builder.build());
|
||||
}
|
||||
|
||||
/**
|
||||
* 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, records);
|
||||
}
|
||||
|
||||
/**
|
||||
* 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, dbName));
|
||||
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, 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;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
//单条查询语句封装
|
||||
/**
|
||||
* 查询结果封装到map
|
||||
* @param commond 单条sql语句
|
||||
* @return 查询结果
|
||||
*/
|
||||
public List<Map<String, Object>> getResult(String commond){
|
||||
List<Map<String, Object>> retList = new ArrayList<>();
|
||||
QueryResult queryResult = influxDB.query(new Query(commond,dbName));
|
||||
List<QueryResult.Result> results = queryResult.getResults();
|
||||
if (results==null||results.isEmpty()){
|
||||
return retList;
|
||||
}
|
||||
QueryResult.Result result = results.get(0);
|
||||
List<QueryResult.Series> seriess = result.getSeries();
|
||||
if (seriess==null||seriess.isEmpty()){
|
||||
return retList;
|
||||
}
|
||||
QueryResult.Series series = seriess.get(0);
|
||||
List<String> columns = series.getColumns();
|
||||
List<List<Object>> values = series.getValues();
|
||||
for (List<Object> columnValue :values){
|
||||
Map<String, Object> map = new HashMap<>(1);
|
||||
for (int i=0;i<columnValue.size();i++){
|
||||
if(columns.get(i).equals("time")){
|
||||
long aa = Instant.parse(columnValue.get(i).toString()).minusMillis(TimeUnit.HOURS.toMillis(8)).getEpochSecond();
|
||||
map.put(columns.get(i), aa);
|
||||
}else {
|
||||
map.put(columns.get(i),columnValue.get(i));
|
||||
}
|
||||
}
|
||||
retList.add(map);
|
||||
}
|
||||
return retList;
|
||||
}
|
||||
|
||||
public List<Map<String, Object>> getResult(String commond, String type){
|
||||
|
||||
List<Map<String, Object>> retList = new ArrayList<>();
|
||||
QueryResult queryResult = influxDB.query(new Query(commond,dbName));
|
||||
List<QueryResult.Result> results = queryResult.getResults();
|
||||
if (results==null||results.isEmpty()){
|
||||
return retList;
|
||||
}
|
||||
QueryResult.Result result = results.get(0);
|
||||
List<QueryResult.Series> seriess = result.getSeries();
|
||||
if (seriess==null||seriess.isEmpty()){
|
||||
return retList;
|
||||
}
|
||||
QueryResult.Series series = seriess.get(0);
|
||||
List<String> columns = series.getColumns();
|
||||
List<List<Object>> values = series.getValues();
|
||||
for (List<Object> columnValue :values){
|
||||
Map<String, Object> map = new HashMap<>(1);
|
||||
for (int i=0;i<columnValue.size();i++){
|
||||
if(columns.get(i).equals("time")){
|
||||
Instant aa = Instant.parse(columnValue.get(i).toString()).minusMillis(TimeUnit.HOURS.toMillis(8));
|
||||
LocalDateTime localDateTime =LocalDateTime.ofInstant(aa,ZoneId.systemDefault());
|
||||
String time = localDateTime.format(DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"));
|
||||
map.put(columns.get(i), time);
|
||||
}else {
|
||||
map.put(columns.get(i),columnValue.get(i));
|
||||
}
|
||||
}
|
||||
retList.add(map);
|
||||
}
|
||||
return retList;
|
||||
}
|
||||
|
||||
|
||||
|
||||
}
|
||||
204
pqs-common/common-influxdb/src/test/java/test.java
Normal file
204
pqs-common/common-influxdb/src/test/java/test.java
Normal file
@@ -0,0 +1,204 @@
|
||||
import com.njcn.influxdb.utils.InfluxDbUtils;
|
||||
import org.influxdb.InfluxDB.ConsistencyLevel;
|
||||
import org.influxdb.dto.BatchPoints;
|
||||
import org.influxdb.dto.Point;
|
||||
import org.influxdb.dto.QueryResult;
|
||||
|
||||
import java.util.*;
|
||||
import java.util.concurrent.TimeUnit;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
/**
|
||||
* 类的介绍：
|
||||
*
|
||||
* @author xuyang
|
||||
* @version 1.0.0
|
||||
* @createTime 2021/11/16 11:07
|
||||
*/
|
||||
|
||||
public class test {
|
||||
|
||||
//查询
|
||||
public static QueryResult select(InfluxDbUtils influxDBUtil) {
|
||||
long startTime = System.currentTimeMillis();
|
||||
QueryResult result = influxDBUtil.query("select * from data_V where phasic_type='A'");
|
||||
long endTime = System.currentTimeMillis();
|
||||
System.out.println(endTime - startTime);
|
||||
return result;
|
||||
}
|
||||
|
||||
//处理结果集
|
||||
public static void chanelResult(QueryResult result) {
|
||||
QueryResult.Result result1 = result.getResults().get(0);
|
||||
if (result1.getSeries() != null) {
|
||||
List<List<Object>> valueList = result1.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();
|
||||
System.out.println(field1);
|
||||
// 数据库中字段2取值
|
||||
String field2 = value.get(1) == null ? null : value.get(1).toString();
|
||||
System.out.println(field2);
|
||||
// TODO 用取出的字段做你自己的业务逻辑……
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public static void main(String[] args) {
|
||||
InfluxDbUtils influxDBUtil = new InfluxDbUtils("root", "123456789", "http://192.168.1.16:8086", "pqsbase", "");
|
||||
insert(influxDBUtil);
|
||||
}
|
||||
//单条数据插入
|
||||
public static void insert(InfluxDbUtils influxDBUtil) {
|
||||
Map<String, String> tags = new HashMap<>();
|
||||
tags.put("lineid", "1e3b8531483b2a8cbee6747f1f641cf9");
|
||||
Map<String, Object> fields = new HashMap<>();
|
||||
fields.put("phasic_type","T");
|
||||
fields.put("value_type","MAX");
|
||||
fields.put("Freq_Dev", 48.6 );
|
||||
fields.put("Voltage_Dev", 8.3 );
|
||||
fields.put("UBalance", 7.6 );
|
||||
fields.put("Flicker", 4.6 );
|
||||
fields.put("UAberrance", 6.5 );
|
||||
fields.put("I_Neg", 5.6 );
|
||||
fields.put("UHarm_2", 6.8 );
|
||||
fields.put("UHarm_3", 5.5 );
|
||||
fields.put("UHarm_4", 5.4 );
|
||||
fields.put("UHarm_5", 7.8 );
|
||||
fields.put("UHarm_6", 6.2 );
|
||||
fields.put("UHarm_7", 2.5 );
|
||||
fields.put("UHarm_8", 8.3 );
|
||||
fields.put("UHarm_9", 6.2 );
|
||||
fields.put("UHarm_10", 12.8 );
|
||||
fields.put("UHarm_11", 2.8 );
|
||||
fields.put("UHarm_12", 8.4 );
|
||||
fields.put("UHarm_13", 5.6 );
|
||||
fields.put("UHarm_14", 5.2 );
|
||||
fields.put("UHarm_15", 9.5 );
|
||||
fields.put("UHarm_16", 8.3 );
|
||||
fields.put("UHarm_17", 7.8 );
|
||||
fields.put("UHarm_18", 6.2 );
|
||||
fields.put("UHarm_19", 2.5);
|
||||
fields.put("UHarm_20", 4.5 );
|
||||
fields.put("UHarm_21", 4.5 );
|
||||
fields.put("UHarm_22", 6.5 );
|
||||
fields.put("UHarm_23", 5.9 );
|
||||
fields.put("UHarm_24", 9.2 );
|
||||
fields.put("UHarm_25", 5.8 );
|
||||
fields.put("IHarm_2", 12.8 );
|
||||
fields.put("IHarm_3", 5.4 );
|
||||
fields.put("IHarm_4", 6.2 );
|
||||
fields.put("IHarm_5", 3.2 );
|
||||
fields.put("IHarm_6", 5.2 );
|
||||
fields.put("IHarm_7", 5.2 );
|
||||
fields.put("IHarm_8", 5.5 );
|
||||
fields.put("IHarm_9", 4.8 );
|
||||
fields.put("IHarm_10", 8.2 );
|
||||
fields.put("IHarm_11", 2.5 );
|
||||
fields.put("IHarm_12", 8.6 );
|
||||
fields.put("IHarm_13", 5.8 );
|
||||
fields.put("IHarm_14", 3.5 );
|
||||
fields.put("IHarm_15", 2.4 );
|
||||
fields.put("IHarm_16", 5.2 );
|
||||
fields.put("IHarm_17", 2.5 );
|
||||
fields.put("IHarm_18", 9.2 );
|
||||
fields.put("IHarm_19", 8.5);
|
||||
fields.put("IHarm_20", 8.5 );
|
||||
fields.put("IHarm_21", 6.2 );
|
||||
fields.put("IHarm_22", 5.2 );
|
||||
fields.put("IHarm_23", 8.5 );
|
||||
fields.put("IHarm_24", 5.2 );
|
||||
fields.put("IHarm_25", 8.4 );
|
||||
fields.put("InUHARM_1", 8.2 );
|
||||
fields.put("InUHARM_2", 5.2 );
|
||||
fields.put("InUHARM_3", 6.2 );
|
||||
fields.put("InUHARM_4", 4.2 );
|
||||
fields.put("InUHARM_5", 2.3 );
|
||||
fields.put("InUHARM_6", 6.2 );
|
||||
fields.put("InUHARM_7", 5.2 );
|
||||
fields.put("InUHARM_8", 10.2 );
|
||||
fields.put("InUHARM_9", 2.3 );
|
||||
fields.put("InUHARM_10", 4.2 );
|
||||
fields.put("InUHARM_11", 3.5 );
|
||||
fields.put("InUHARM_12", 3.6 );
|
||||
fields.put("InUHARM_13", 2.3 );
|
||||
fields.put("InUHARM_14", 7.2 );
|
||||
fields.put("InUHARM_15", 5.6 );
|
||||
fields.put("InUHARM_16", 5.6 );
|
||||
influxDBUtil.insert("PQS_AbnormalData", tags, fields, System.currentTimeMillis(), TimeUnit.MILLISECONDS);
|
||||
}
|
||||
|
||||
|
||||
//循环写入数据库
|
||||
public static void batchInsertOne(InfluxDbUtils influxDBUtil) {
|
||||
Map<String, String> tags1 = new HashMap<>();
|
||||
tags1.put("LineID", "8");
|
||||
tags1.put("Phasic_Type", "A");
|
||||
Map<String, Object> fields1 = new HashMap<>();
|
||||
fields1.put("RMS", 2);
|
||||
fields1.put("RMS_AB", 2);
|
||||
fields1.put("RMS_BC", 2);
|
||||
fields1.put("RMS_CA", 2);
|
||||
Map<String, String> tags2 = new HashMap<>();
|
||||
tags2.put("LineID", "9");
|
||||
tags2.put("Phasic_Type", "A");
|
||||
Map<String, Object> fields2 = new HashMap<>();
|
||||
fields2.put("RMS", 4);
|
||||
fields2.put("RMS_AB", 4);
|
||||
fields2.put("RMS_BC", 4);
|
||||
fields2.put("RMS_CA", 4);
|
||||
// 一条记录值
|
||||
Point point1 = influxDBUtil.pointBuilder("test", System.currentTimeMillis(), TimeUnit.MILLISECONDS, tags1, fields1);
|
||||
Point point2 = influxDBUtil.pointBuilder("test", System.currentTimeMillis(), TimeUnit.MILLISECONDS, tags2, fields2);
|
||||
// 将两条记录添加到batchPoints中
|
||||
BatchPoints batchPoints1 = BatchPoints.database("test").tag("LineID", "8").tag("Phasic_Type", "A").retentionPolicy("")
|
||||
.consistency(ConsistencyLevel.ALL).build();
|
||||
BatchPoints batchPoints2 = BatchPoints.database("test").tag("LineID", "9").tag("Phasic_Type", "A").retentionPolicy("")
|
||||
.consistency(ConsistencyLevel.ALL).build();
|
||||
batchPoints1.point(point1);
|
||||
batchPoints2.point(point2);
|
||||
// 将两条数据批量插入到数据库中
|
||||
influxDBUtil.batchInsert(batchPoints1, TimeUnit.MILLISECONDS);
|
||||
influxDBUtil.batchInsert(batchPoints2, TimeUnit.MILLISECONDS);
|
||||
}
|
||||
|
||||
|
||||
//批量插入数据
|
||||
public static void batchInsert(InfluxDbUtils influxDBUtil) {
|
||||
Map<String, String> tags1 = new HashMap<>();
|
||||
tags1.put("LineID", "4");
|
||||
tags1.put("Phasic_Type", "A");
|
||||
Map<String, Object> fields1 = new HashMap<>();
|
||||
fields1.put("RMS", 4.1111);
|
||||
fields1.put("RMS_AB", 4.1111);
|
||||
fields1.put("RMS_BC", 4.1111);
|
||||
fields1.put("RMS_CA", 4.1111);
|
||||
Map<String, String> tags2 = new HashMap<>();
|
||||
tags2.put("LineID", "5");
|
||||
tags2.put("Phasic_Type", "A");
|
||||
Map<String, Object> fields2 = new HashMap<>();
|
||||
fields2.put("RMS", 5.1111);
|
||||
fields2.put("RMS_AB", 5.1111);
|
||||
fields2.put("RMS_BC", 5.1111);
|
||||
fields2.put("RMS_CA", 5.1111);
|
||||
// 一条记录值。（注意：生产环境不要用System.currentTimeMillis()，因为数据量大会产生重复时间戳，导致数据丢失，要用数据自己的时间戳，这里只做演示）
|
||||
Point point1 = influxDBUtil.pointBuilder("Data_v", System.currentTimeMillis(), TimeUnit.MILLISECONDS, tags1, fields1);
|
||||
Point point2 = influxDBUtil.pointBuilder("Data_v", System.currentTimeMillis(), TimeUnit.MILLISECONDS, tags2, fields2);
|
||||
// BatchPoints batchPoints1 = BatchPoints.database("Data_v").tag("LineID", "4").tag("Phasic_Type","A").retentionPolicy("").consistency(ConsistencyLevel.ALL).precision(TimeUnit.MILLISECONDS).build();
|
||||
BatchPoints batchPoints1 = BatchPoints.database("test").tag("LineID", "4").tag("Phasic_Type", "A").retentionPolicy("").consistency(ConsistencyLevel.ALL).build();
|
||||
batchPoints1.point(point1);
|
||||
BatchPoints batchPoints2 = BatchPoints.database("test").tag("LineID", "5").tag("Phasic_Type", "A").retentionPolicy("").consistency(ConsistencyLevel.ALL).build();
|
||||
// 将两条记录添加到batchPoints中
|
||||
batchPoints2.point(point2);
|
||||
// 将不同的batchPoints序列化后，一次性写入数据库，提高写入速度
|
||||
List<String> records = new ArrayList<String>();
|
||||
records.add(batchPoints1.lineProtocol());
|
||||
records.add(batchPoints2.lineProtocol());
|
||||
// 将两条数据批量插入到数据库中
|
||||
influxDBUtil.batchInsert("test", "", ConsistencyLevel.ALL, TimeUnit.MILLISECONDS, records);
|
||||
}
|
||||
|
||||
}
|
||||
Reference in New Issue
Block a user