Storm+Hbase广告实时统计

本文主要讲述使用Kafka+Strom+Hbase搭建的一套广告实时计算系统。其中服务器显示使用的是SpringBoot+Vue+ElementUI+EChats.

主要内容：

• 1.需求
• 2.日志格式
• 3.Hbase表格设计
• 4.编写Storm程序
• 5.Kafka接收消息
• 6.Hbase数据查询
• 7.参考

1.需求

• 1、某个广告在某个省的当前投放量
• 2、某个广告在某个市的当前投放量
• 3、某个广告在某个用户客户端上的当前投放量
• 4、某个广告在累加一段时间内的某个省额历史投放趋势
• 5、某个广告在累加一段时间内的某个市额历史投放趋势
• 6、某个广告在累加一段时间内的某个客户端历史投放趋势
• 7、某个广告的当前的点击量
• 8、某个广告在累加一段时间内的点击趋势

效果预览1

效果预览2

2.日志格式

2014-01-13\t19:11:55\t{"adid":"31789","uid":"9871","action":"view"}\t63.237.239.3\t北京\t北京

日期：2014-01-13
时间：19:11:55
Json：方便扩展
  adid：广告ID
  uid：用户ID
  action：用户行为click、view
IP：63.237.239.3
省：北京
市：北京

3.Hbase建表

表名	realtime_ad_stat
行键	ADID_Province_20181212 ADID_City_20181212 ADID_UID_20181212
列簇	stat
列	view_cnt、click_cnt

# 创建表
create 'realtime_ad_stat',{NAME => 'stat',VERSIONS => 2147483647}

# 查看表
list

# 清空数据
truncate 'realtime_ad_stat'

# 删除表
disable 'realtime_ad_stat'
drop 'realtime_ad_stat'

4.编写Storm程序

4.1.AdTopology

public class AdTopology {
    public static void main(String[] args) throws Exception {
        TopologyBuilder topologyBuilder = new TopologyBuilder();

        KafkaSpoutConfig kafkaSpoutConfig =
                KafkaSpoutConfig.builder("hadoop1:9092,hadoop2:9092,hadoop3:9092", "AD")
                        .setProp(ConsumerConfig.GROUP_ID_CONFIG, "STORM_AD_GROUP")
                        .setFirstPollOffsetStrategy(KafkaSpoutConfig.FirstPollOffsetStrategy.LATEST)
                        .build();
        topologyBuilder.setSpout("KafkaSpout", new KafkaSpout(kafkaSpoutConfig), 2);
        topologyBuilder.setBolt("me.jinkun.ad.storm.LogToModelBolt", new LogToModelBolt(), 2).localOrShuffleGrouping("KafkaSpout");
        topologyBuilder.setBolt("me.jinkun.ad.storm.ToHbaseBolt", new ToHbaseBolt(), 4).localOrShuffleGrouping("me.jinkun.ad.storm.LogToModelBolt");

        StormTopology topology = topologyBuilder.createTopology();
        Config config = new Config();
        config.setDebug(false);

        if (args != null && args.length > 0) {
            //运行集群模式
            config.setNumWorkers(4);
            StormSubmitter.submitTopology(args[0], config, topologyBuilder.createTopology());
        } else {
            LocalCluster localCluster = new LocalCluster();
            localCluster.submitTopology("AdTopology", config, topology);
        }
    }
}

从Kafka里读取Topic为AD的最新的日志消息并发送个LogToModelBolt

4.2.LogToModelBolt

public class LogToModelBolt extends BaseBasicBolt {

    private static final Logger LOG = LoggerFactory.getLogger(LogToModelBolt.class);

    public void execute(Tuple input, BasicOutputCollector collector) {
        // 2014-01-13   19:11:55    {"adid":"31789","uid":"9871","action":"view"}    63.237.239.3    北京 北京
        String line = input.getStringByField("value");
        if (LOG.isInfoEnabled()) {
            LOG.info("line:[{}]", line);
        }
        String[] arr = line.split("\t", -1);
        if (arr.length == 6) {
            String date = arr[0].trim().replace("-", "");
            String time = arr[1].trim();
            String json = arr[2].trim();
            String ip = arr[3].trim();
            String province = arr[4].trim();
            String city = arr[5].trim();

            if (StringUtils.isNotEmpty(json)) {
                Ad ad = new Gson().fromJson(json, Ad.class);
                if (null != ad && StringUtils.isNotEmpty(ad.getAdid())) {
                    // 省
                    if (StringUtils.isNotEmpty(province)) {
                        String rowkey = ad.getAdid() + "_" + province + "_" + date;
                        collector.emit(new Values(ad.getAction(), rowkey, 1L));
                    }

                    // 市
                    if (StringUtils.isNotEmpty(city)) {
                        String rowkey = ad.getAdid() + "_" + city + "_" + date;
                        collector.emit(new Values(ad.getAction(), rowkey, 1L));
                    }

                    // 客户端
                    if (StringUtils.isNotEmpty(province)) {
                        String rowkey = ad.getAdid() + "_" + ad.getUid() + "_" + date;
                        collector.emit(new Values(ad.getAction(), rowkey, 1L));
                    }
                }
            }
        }
    }

    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        declarer.declare(new Fields("action", "rowkey", "cnt"));
    }
}

解析Log并转化为Model，发送给ToHbaseBolt

4.3.ToHbaseBolt

public class ToHbaseBolt extends BaseBasicBolt {

    private static final Logger LOG = LoggerFactory.getLogger(ToHbaseBolt.class);

    private Table table;

    @Override
    public void prepare(Map stormConf, TopologyContext context) {
        try {
            Configuration conf = HBaseConfiguration.create();
            conf.set("hbase.zookeeper.quorum", "hadoop1:2181,hadoop2:2181,hadoop3:2181");
            Connection conn = ConnectionFactory.createConnection(conf);
            table = conn.getTable(TableName.valueOf("realtime_ad_stat"));
        } catch (IOException e) {
            e.printStackTrace();
        }
    }

    public void execute(Tuple input, BasicOutputCollector collector) {
        String action = input.getStringByField("action");
        String rowkey = input.getStringByField("rowkey");
        Long pv = input.getLongByField("cnt");

        try {
            if ("view".equals(action)) {
                table.incrementColumnValue(Bytes.toBytes(rowkey), Bytes.toBytes("stat"), Bytes.toBytes("view_cnt"), pv);
            }
            if ("click".equals(action)) {
                table.incrementColumnValue(Bytes.toBytes(rowkey), Bytes.toBytes("stat"), Bytes.toBytes("click_cnt"), pv);
            }
        } catch (IOException e) {
            e.printStackTrace();
        }
    }

    public void declareOutputFields(OutputFieldsDeclarer declarer) {

    }
}

ToHbaseBolt 将处理后的数据写入到Hbase表里

5.Kafka

5.1.创建名为AD的Topic

#查看
kafka-topics.sh --describe \
--zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181/kafka

#创建AD
kafka-topics.sh --create \
--zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181/kafka \
--topic AD \
--partitions 3 \
--replication-factor 3

#消费者AD
kafka-console-consumer.sh \
--zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181/kafka \
--topic AD \
--from-beginning

#删除
kafka-topics.sh --delete \
--zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181/kafka \
--topic AD

5.2.模拟发送消息

public class ProducerClient {

    private static final Logger LOG = LoggerFactory.getLogger(ProducerClient.class);
    private static final String[] PROVINCES_CITIES = new String[]{
            "山东\t济南",
            "河北\t石家庄",
            "吉林\t长春",
            "黑龙江\t哈尔滨",
            "辽宁\t沈阳",
            "内蒙古\t呼和浩特",
            "新疆\t乌鲁木齐",
            "甘肃\t兰州",
            "宁夏\t银川",
            "山西\t太原",
            "陕西\t西安",
            "河南\t郑州",
            "安徽\t合肥",
            "江苏\t南京",
            "浙江\t杭州",
            "福建\t福州",
            "广东\t广州",
            "江西\t南昌",
            "海南\t海口",
            "广西\t南宁",
            "贵州\t贵阳",
            "湖南\t长沙",
            "湖北\t武汉",
            "四川\t成都",
            "云南\t昆明",
            "西藏\t拉萨",
            "青海\t西宁",
            "天津\t天津",
            "上海\t上海",
            "重庆\t重庆",
            "北京\t北京",
            "台湾\t台北",
            "香港\t香港",
            "澳门\t澳门"
    };
    private static final String[] ACTIONS = new String[]{
            "view", "click"
    };
    private static final String[] ADIDS = new String[]{
            "1", "2", "3", "4", "5"
    };

    public static void main(String[] args) throws Exception {
        Properties props = new Properties();
        props.put("bootstrap.servers", "hadoop1:9092,hadoop2:9092,hadoop3:9092");
        props.put("acks", "all");
        props.put("retries", 0);
        props.put("batch.size", 16384);
        props.put("linger.ms", 1);
        props.put("buffer.memory", 33554432);
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        org.apache.kafka.clients.producer.KafkaProducer kafkaProducer = new org.apache.kafka.clients.producer.KafkaProducer(props);
        boolean flag = true;
        if (flag) {
            for (int i = 0; i < 2000; i++) {
                //3、发送数据
                //2014-01-13   19:11:55    {"adid":"31789","uid":"9871"}    63.237.239.3    北京市 北京市
                StringBuilder sb = new StringBuilder();
                //sb.append(new SimpleDateFormat("yyyy-MM-dd").format(date));
                sb.append("2018-08-10");
                sb.append("\t");
                sb.append("12:00:00");
                sb.append("\t");
                sb.append("{\"adid\":\"" + ADIDS[new Random().nextInt(ADIDS.length)] + "\",\"uid\":\"" + new Random().nextInt(200) + "\",\"action\":\"" + ACTIONS[new Random().nextInt(ACTIONS.length)] + "\"}");
                sb.append("\t");
                sb.append(new Random().nextInt(255) + "." + new Random().nextInt(255) + "." + new Random().nextInt(255) + "." + new Random().nextInt(255));
                sb.append("\t");
                sb.append(PROVINCES_CITIES[new Random().nextInt(PROVINCES_CITIES.length)]);
                kafkaProducer.send(new ProducerRecord("AD", sb.toString()));
            }
            Thread.sleep(1000);
            kafkaProducer.flush();

            if (LOG.isInfoEnabled()) {
                LOG.info("{}", "发送消息完成");
            }
        }

        kafkaProducer.close();
    }
}

部分日志截图

6.Hbase数据查询

public Map get(Table table, String adid, String date, String province) {
  try {
    if (StringUtils.isNotEmpty(date)) {
      date = date.replace("-", "");
    }

    Map map = Maps.newHashMapWithExpectedSize(5);
    map.put("adid", adid);
    map.put("date", date);
    map.put("province", province);

    // adid_province_date or adid_city_date
    String rowKey = adid + "_" + province + "_" + date;

    Get get = new Get(Bytes.toBytes(rowKey));
    Result result = table.get(get);

    //获取stat:view_cnt
    long viewCnt = 0L;
    byte[] viewBytes = result.getValue(Bytes.toBytes("stat"), Bytes.toBytes("view_cnt"));
    if (viewBytes != null) {
      viewCnt = Bytes.toLong(viewBytes);
    }
    map.put("view", viewCnt);

    //获取stat:click_cnt
    long clickCnt = 0L;
    byte[] clickBytes = result.getValue(Bytes.toBytes("stat"), Bytes.toBytes("click_cnt"));
    if (clickBytes != null) {
      clickCnt = Bytes.toLong(clickBytes);
    }
    map.put("click", clickCnt);
    return map;
  } catch (IOException e) {
    e.printStackTrace();
    throw new ServiceException("查询列表失败");
  }
}

使用Hbase客户端将realtime_ad_stat表里的数据封装成Map对象并转为Json给前端展示

{
    "data":[
        {
            "date":"20180810",
            "view":6,
            "adid":"1",
            "province":"山东",
            "click":4
        },
        {
            "date":"20180810",
            "view":4,
            "adid":"1",
            "province":"河北",
            "click":8
        },
        {
            "date":"20180810",
            "view":2,
            "adid":"1",
            "province":"吉林",
            "click":4
        },
        {
            "date":"20180810",
            "view":4,
            "adid":"1",
            "province":"黑龙江",
            "click":2
        },
        {
            "date":"20180810",
            "view":4,
            "adid":"1",
            "province":"辽宁",
            "click":7
        },
        {
            "date":"20180810",
            "view":6,
            "adid":"1",
            "province":"内蒙古",
            "click":5
        },
        {
            "date":"20180810",
            "view":10,
            "adid":"1",
            "province":"新疆",
            "click":6
        },
        {
            "date":"20180810",
            "view":12,
            "adid":"1",
            "province":"甘肃",
            "click":5
        },
        {
            "date":"20180810",
            "view":11,
            "adid":"1",
            "province":"宁夏",
            "click":5
        },
        {
            "date":"20180810",
            "view":5,
            "adid":"1",
            "province":"山西",
            "click":5
        },
        {
            "date":"20180810",
            "view":7,
            "adid":"1",
            "province":"陕西",
            "click":5
        },
        {
            "date":"20180810",
            "view":3,
            "adid":"1",
            "province":"河南",
            "click":6
        },
        {
            "date":"20180810",
            "view":1,
            "adid":"1",
            "province":"安徽",
            "click":8
        },
        {
            "date":"20180810",
            "view":6,
            "adid":"1",
            "province":"江苏",
            "click":10
        },
        {
            "date":"20180810",
            "view":12,
            "adid":"1",
            "province":"浙江",
            "click":5
        },
        {
            "date":"20180810",
            "view":4,
            "adid":"1",
            "province":"福建",
            "click":2
        },
        {
            "date":"20180810",
            "view":5,
            "adid":"1",
            "province":"广东",
            "click":13
        },
        {
            "date":"20180810",
            "view":8,
            "adid":"1",
            "province":"江西",
            "click":6
        },
        {
            "date":"20180810",
            "view":5,
            "adid":"1",
            "province":"海南",
            "click":1
        },
        {
            "date":"20180810",
            "view":6,
            "adid":"1",
            "province":"广西",
            "click":7
        },
        {
            "date":"20180810",
            "view":5,
            "adid":"1",
            "province":"贵州",
            "click":11
        },
        {
            "date":"20180810",
            "view":8,
            "adid":"1",
            "province":"湖南",
            "click":8
        },
        {
            "date":"20180810",
            "view":9,
            "adid":"1",
            "province":"湖北",
            "click":4
        },
        {
            "date":"20180810",
            "view":6,
            "adid":"1",
            "province":"四川",
            "click":8
        },
        {
            "date":"20180810",
            "view":2,
            "adid":"1",
            "province":"云南",
            "click":7
        },
        {
            "date":"20180810",
            "view":4,
            "adid":"1",
            "province":"西藏",
            "click":4
        },
        {
            "date":"20180810",
            "view":4,
            "adid":"1",
            "province":"青海",
            "click":3
        },
        {
            "date":"20180810",
            "view":16,
            "adid":"1",
            "province":"天津",
            "click":4
        },
        {
            "date":"20180810",
            "view":12,
            "adid":"1",
            "province":"上海",
            "click":12
        },
        {
            "date":"20180810",
            "view":10,
            "adid":"1",
            "province":"重庆",
            "click":16
        },
        {
            "date":"20180810",
            "view":10,
            "adid":"1",
            "province":"北京",
            "click":14
        },
        {
            "date":"20180810",
            "view":5,
            "adid":"1",
            "province":"台湾",
            "click":4
        },
        {
            "date":"20180810",
            "view":18,
            "adid":"1",
            "province":"香港",
            "click":10
        },
        {
            "date":"20180810",
            "view":8,
            "adid":"1",
            "province":"澳门",
            "click":12
        }
    ],
    "message":"操作成功！",
    "resultCode":"00000"
}

7.参考：

EChats
HBase企业应用开发实战 第8章
Hadoop集群环境搭建（三台）
Zookeeper集群安装
Strom之WordCount
Hbase之环境搭建
Kafka之集群安装