数据mock大数据Mock商城数据
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前言
为方便大家学习大数据过程中，需要数据进行练习与调试，本次给大家分享几篇mock数据的脚本
可适用于kafka;hive;spark;flink;presto;clickhouse等等框架的操作练习
- kafka 数据mock
- hive 数据mock
- presto 数据mock
- spark 数据mock
- flink 数据mock
- clickhouse 数据mock
- doris 数据mock
- …
mock数据脚本-基础版
private static void mock(String brokers, String topic)
String[] versions = new String[]"V1.2.0", "V1.2.1", "V1.2.2";
String[] channels = new String[]"小米商城", "华为商城", "AppStore";
String[] netTypes = new String[]"WiFi", "4G", "5G";
String[] var10000 = new String[]"cart", "browse", "pay";
String[] deviceTypes = new String[]"小米11 Ultra", "iPhone 11", "iPhone 10", "iPhone 9", "华为V65";
Map<String, String> devices = new HashMap();
devices.put("小米11 Ultra", "android");
devices.put("iPhone 11", "ios");
devices.put("iPhone 10", "iOS");
devices.put("iPhone 9", "iOS");
devices.put("华为V65", "Android");
List<String> categories = new ArrayList();
categories.add("Hadoop系统入门核心精讲 大数据实战");
categories.add("SparkSQL极速入门整合Kudu实现广告业务数据分析 大数据实战");
categories.add("Spark进阶大数据离线与实时项目实战 大数据实战");
categories.add("学习Scala进击大数据Spark生态圈 大数据实战");
categories.add("实战Spark3实时处理掌握两套企业级处理方案 大数据实战");
categories.add("辣条 食品饮料");
categories.add("矿泉水 食品饮料");
categories.add("咖啡 食品饮料");
categories.add("茅子 食品饮料");
categories.add("五子 食品饮料");
categories.add("宝马 车");
categories.add("奔驰 车");
categories.add("奥迪 车");
categories.add("保时捷 车");
categories.add("法拉利 车");
categories.add("冲锋衣 户外");
categories.add("帆布鞋 户外");
categories.add("跑步鞋 户外");
categories.add("山地车 户外");
categories.add("运动包 户外");
for (int i = 100; i <= 1000; ++i)
Access access = new Access();
access.setUid("user_" + i);
access.setVersion(versions[(new Random()).nextInt(versions.length)]);
access.setDevice(UUID.randomUUID().toString());
access.setEvent("startup");
String deviceType = deviceTypes[(new Random()).nextInt(deviceTypes.length)];
access.setDeviceType(deviceType);
access.setOs((String) devices.get(deviceType));
access.setNet(netTypes[(new Random()).nextInt(netTypes.length)]);
String ip = getRandomIp();
access.setIp(ip);
access.setChannel(channels[(new Random()).nextInt(channels.length)]);
access.setTime(System.currentTimeMillis() + 107200000000L + 86400000L);
if (i % 3 != 0)
access.setNu(1);
else
access.setNu(0);
String info = JSON.toJSON(access).toString();
System.out.println(info);
Thread.sleep(1000L);
private static String getRandomIp()
int[][] range = new int[][]607649792, 608174079, 1038614528, 1039007743, 1783627776, 1784676351, 2035023872, 2035154943, 2078801920, 2079064063, -1950089216, -1948778497, -1425539072, -1425014785, -1236271104, -1235419137, -770113536, -768606209, -569376768, -564133889;
Random rdint = new Random();
int index = rdint.nextInt(10);
String ip = num2ip(range[index][0] + (new Random()).nextInt(range[index][1] - range[index][0]));
return ip;
private static String num2ip(int ip)
int[] b = new int[4];
String x = "";
b[0] = ip >> 24 & 255;
b[1] = ip >> 16 & 255;
b[2] = ip >> 8 & 255;
b[3] = ip & 255;
x = Integer.toString(b[0]) + "." + Integer.toString(b[1]) + "." + Integer.toString(b[2]) + "." + Integer.toString(b[3]);
return x;
mock 数据截取如下：
"deviceType":"iPhone 10","uid":"user_1","product":"name":"矿泉水","category":"食品饮料","os":"iOS","ip":"106.82.37.76","nu":1,"channel":"小米商城","time":1754026686804,"event":"cart","net":"4G","device":"4e0b3735-9f86-4b6b-a8e6-bc328a4135b8","version":"V1.2.1"
"deviceType":"iPhone 10","uid":"user_1","product":"name":"实战Spark3实时处理掌握两套企业级处理方案","category":"大数据实战","os":"iOS","ip":"106.82.37.76","nu":1,"channel":"小米商城","time":1754026686804,"event":"browse","net":"4G","device":"4e0b3735-9f86-4b6b-a8e6-bc328a4135b8","version":"V1.2.1"
"deviceType":"iPhone 10","uid":"user_1","product":"name":"宝马","category":"车","os":"iOS","ip":"106.82.37.76","nu":1,"channel":"小米商城","time":1754026686804,"event":"pay","net":"4G","device":"4e0b3735-9f86-4b6b-a8e6-bc328a4135b8","version":"V1.2.1"
"deviceType":"iPhone 10","uid":"user_1","product":"name":"法拉利","category":"车","os":"iOS","ip":"106.82.37.76","nu":1,"channel":"小米商城","time":1754026686804,"event":"browse","net":"4G","device":"4e0b3735-9f86-4b6b-a8e6-bc328a4135b8","version":"V1.2.1"
mock数据-集成到kafka
private static KafkaProducer sendKafka(String brokers)
Properties properties = new Properties();
properties.put("bootstrap.servers", brokers);
properties.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
properties.put("acks", "1");
properties.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
return new KafkaProducer(properties);
private static void mock(String brokers, String topic)
KafkaProducer producer = sendKafka("broker");
String[] versions = new String[]"V1.2.0", "V1.2.1", "V1.2.2";
String[] channels = new String[]"小米商城", "华为商城", "AppStore";
String[] netTypes = new String[]"WiFi", "4G", "5G";
String[] var10000 = new String[]"cart", "browse", "pay";
String[] deviceTypes = new String[]"小米11 Ultra", "iPhone 11", "iPhone 10", "iPhone 9", "华为V65";
Map<String, String> devices = new HashMap();
devices.put("小米11 Ultra", "Android");
devices.put("iPhone 11", "iOS");
devices.put("iPhone 10", "iOS");
devices.put("iPhone 9", "iOS");
devices.put("华为V65", "Android");
List<String> categories = new ArrayList();
categories.add("Hadoop系统入门核心精讲 大数据实战");
categories.add("SparkSQL极速入门整合Kudu实现广告业务数据分析 大数据实战");
categories.add("Spark进阶大数据离线与实时项目实战 大数据实战");
categories.add("学习Scala进击大数据Spark生态圈 大数据实战");
categories.add("实战Spark3实时处理掌握两套企业级处理方案 大数据实战");
categories.add("辣条 食品饮料");
categories.add("矿泉水 食品饮料");
categories.add("咖啡 食品饮料");
categories.add("茅子 食品饮料");
categories.add("五子 食品饮料");
categories.add("宝马 车");
categories.add("奔驰 车");
categories.add("奥迪 车");
categories.add("保时捷 车");
categories.add("法拉利 车");
categories.add("冲锋衣 户外");
categories.add("帆布鞋 户外");
categories.add("跑步鞋 户外");
categories.add("山地车 户外");
categories.add("运动包 户外");
for (int i = 100; i <= 1000; ++i)
Access access = new Access();
access.setUid("user_" + i);
access.setVersion(versions[(new Random()).nextInt(versions.length)]);
access.setDevice(UUID.randomUUID().toString());
access.setEvent("startup");
String deviceType = deviceTypes[(new Random()).nextInt(deviceTypes.length)];
access.setDeviceType(deviceType);
access.setOs((String) devices.get(deviceType));
access.setNet(netTypes[(new Random()).nextInt(netTypes.length)]);
String ip = getRandomIp();
access.setIp(ip);
access.setChannel(channels[(new Random()).nextInt(channels.length)]);
access.setTime(System.currentTimeMillis() + 107200000000L + 86400000L);
if (i % 3 != 0)
access.setNu(1);
else
access.setNu(0);
String info = JSON.toJSON(access).toString();
System.out.println(info);
producer.send(new ProducerRecord(topic, info));
Thread.sleep(1000L);
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