利用Python随机生成一个1000行的csv文件

import csv
import random
from datetime import datetime, timedelta
from random import randint, choice

# 定义监控对象列表和指标名称列表
monitor_objects = ['Server1', 'Server2', 'Server3', 'DB1']
metric_names = ['CPUUsage', 'MemoryUsage', 'DiskSpace', 'NetworkTraffic']

# 生成随机日期范围，例如从今天开始往回计算一年的数据
start_date = datetime.now() - timedelta(days=365)
end_date = datetime.now()

# 打开一个文件，准备写入
filename = 'random_data.csv'
with open(filename, mode='w', newline='', encoding='utf-8') as csvfile:
    fieldnames = ['dates', 'monitorObject', 'timeStamp', 'metricName', 'value']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    # 写入表头
    writer.writeheader()

    # 生成并写入1000行数据
    for _ in range(10000000):
        # 随机日期
        random_date = start_date + (end_date - start_date) * random.random()
        date_str = random_date.strftime('%Y-%m-%d')
        time_stamp = int(random_date.timestamp())
        
        # 随机选择监控对象和指标名称
        monitor_object = choice(monitor_objects)
        metric_name = choice(metric_names)
        
        # 随机值，根据实际情况调整范围
        value = round(random.uniform(0, 100), 2)  # 假设值在0到100之间，保留两位小数
        
        # 写入一行数据
        writer.writerow({
            'dates': date_str,
            'monitorObject': monitor_object,
            'timeStamp': time_stamp,
            'metricName': metric_name,
            'value': value
        })

print(f"CSV文件已成功生成，文件名为: {filename}")

利用Java写入inluxdb

package org.example;

import com.csvreader.CsvReader;
import com.influxdb.client.InfluxDBClient;
import com.influxdb.client.InfluxDBClientFactory;
import com.influxdb.client.WriteApiBlocking;
import com.influxdb.client.domain.WritePrecision;
import com.influxdb.client.write.Point;

import java.nio.charset.StandardCharsets;
import java.util.ArrayList;
import java.util.List;

public class Main {
    static String token = "ZgpSCp3H_9liDB6v5POacJ8MOqnKOUR9YUlJjkIvLtFbYVyZr5Rkn-YKpUNdPqWpRKY_7Fqdwv6GN9r4A8BwcQ==";
    static String bucket = "data";
    static String org = "test";

    static InfluxDBClient client = InfluxDBClientFactory.create("http://localhost:8086", token.toCharArray());

    public static void main(String[] args) throws Exception {
        String CSV_FILE_PATH = "D:\\JAVA_dataAnalyze\\dataAnalyze\\src\\main\\java\\org\\example\\data\\random_data.csv";

        long startTime = System.currentTimeMillis();
        readCsv(CSV_FILE_PATH); // 方法1 串行写入
        long endTime = System.currentTimeMillis();
        System.out.println("excute time: " + (endTime - startTime) + "ms");

        startTime = System.currentTimeMillis();
        readCSVByMemory(CSV_FILE_PATH); // 方法2 stream流并行写入
        endTime = System.currentTimeMillis();
        System.out.println("excute time: " + (endTime - startTime) + "ms");
    }

    public static void readCsv(String CSV_FILE_PATH) throws Exception {
        CsvReader CSVReader = new CsvReader(CSV_FILE_PATH, ',', StandardCharsets.UTF_8);

        CSVReader.readHeaders();
        int rowNumber = 0;
        long startTime = System.currentTimeMillis();
        while (CSVReader.readRecord()) {

            // 安装mysql并引入Mapping
            String content = CSVReader.getRawRecord();
            // 按照 dates,monitorObject,timeStamp,metricName,value 解析内容
            Point lineProtocol = row2InfluxPoint(content);
            //System.out.println(lineProtocol.toLineProtocol());
            point2InluxDB(lineProtocol);
            rowNumber++;
            if(rowNumber % 10000 == 0){
                long endTime = System.currentTimeMillis();
                System.out.println("rowNumber: " + rowNumber + "excute time: " + (endTime - startTime) + "ms");
                startTime = endTime;
            }
        }
        CSVReader.close();
    }
    public static  void readCSVByMemory(String CSV_FILE_PATH) throws Exception {
        CsvReader CSVReader = new CsvReader(CSV_FILE_PATH, ',', StandardCharsets.UTF_8);

        CSVReader.readHeaders();
        int rowNumber = 0;
        long startTime = System.currentTimeMillis();
        List<String> contentList =  new ArrayList<String>();
        while (CSVReader.readRecord()) {
            contentList.add(CSVReader.getRawRecord());
        }
        // 并行将contentList中的元素写入influxdb
        contentList.stream().parallel().forEach(content -> {
            point2InluxDB(row2InfluxPoint(content));
        });
}

    public static Point row2InfluxPoint(String content) {
        String[] contentArray = content.split(",");
        Point point = Point
                .measurement("mem_data1T")
                .addTag("monitorObject", contentArray[1])
                .addField(contentArray[3], Float.parseFloat(contentArray[4]))
                .time(Long.parseLong(contentArray[2]), WritePrecision.S);

        return point;
    }

    public static void point2InluxDB(Point point){
        WriteApiBlocking writeApi = client.getWriteApiBlocking();
        writeApi.writePoint(bucket, org, point);
    }

}

    <dependencies>
        <dependency>
            <groupId>net.sourceforge.javacsv</groupId>
            <artifactId>javacsv</artifactId>
            <version>2.0</version>
        </dependency>
        <dependency>
            <groupId>com.influxdb</groupId>
            <artifactId>influxdb-client-java</artifactId>
            <version>6.6.0</version>
        </dependency>
    </dependencies>