log4j+flume+kafka实现日志收集

1.Zookeeper集群配置

#	hostname	ip	software	notes
1	apollo.dt.com	192.168.56.181	zookeeper	Kafka: broker.id=181
2	artemis.dt.com	192.168.56.182	zookeeper	kafka: borker.id=182
3	uranus.dt.com	192.168.56.183	zookeeper	kafka: broker.id=183
4	pandora.dt.com	192.168.56.184	zookeeper	kafka: broker.id=184

有关zookeeper详细集群搭建请参考：CentOS安装配置Zookeeper集群

2.Kafka集群配置

#	hostname	ip	software	notes
1	apollo.dt.com	192.168.56.181	kafka	Kafka: broker.id=181
2	artemis.dt.com	192.168.56.182	kafka	kafka: borker.id=182
3	uranus.dt.com	192.168.56.183	kafka	kafka: broker.id=183
4	pandora.dt.com	192.168.56.184	kafka	kafka: broker.id=184

有关Kafka详细集群搭建请参考：CentOS7.0安装配置Kafka集群](http://blog.csdn.net/jssg_tzw/article/details/73106299)

3.启动zookeer和kafka集群

3.1.启动zookeeper

[root@apollo ~]# zkServer.sh start
[root@artemis ~]# zkServer.sh start
[root@uranus ~]# zkServer.sh start
[root@pandora ~]# zkServer.sh start

3.2.启动kafka集群

[root@apollo ~]# kafka-server-start.sh /opt/kafka/config/server.properties
[root@artemis ~]# kafka-server-start.sh /opt/kafka/config/server.properties
[root@uranus ~]# kafka-server-start.sh /opt/kafka/config/server.properties
[root@pandora ~]# kafka-server-start.sh /opt/kafka/config/server.properties

4.flume的安装与配置

4.1.把flume解压到/opt/flume目录下

4.2.在$FLUME_HOME/conf/目录下新建配置文件flume2kafka

# 定义agent
a1.sources=r1
a1.channels=c1
a1.sinks=k1

# 定义source
a1.sources.r1.type=avro
a1.sources.r1.bind=localhost
a1.sources.r1.port=44446

# 定义channel
a1.channels.c1.type=memory
a1.channels.c1.capacity=1000
a1.channels.c1.transactionCapacity=1000
a1.channels.c1.keep-alive=30

# 定义sink (Kafka)
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = dt-receipts
a1.sinks.k1.kafka.bootstrap.servers = 192.168.56.181:9092,192.168.56.182:9092,192.168.56.183:9092,192.168.56.184:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
a1.sinks.k1.kafka.producer.compression.type = snappy

# 绑定source, sink到channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

4.3.启动flume

[itlocals-MacBook-Pro:flume david.tian]$  bin/flume-ng agent -n a1 -c conf/ --conf-file conf/flume2kafka.conf -Dflume.root.logger=DEBUG,console

5. log4j发日志到flume

源码请从我的git上下载：https://github.com/david-louis-tian/dBD

5.1.这里仅给出pom.xml,模拟日志的代码,和log4j.properties

• pom.xml

"http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  4.0.0
  com.dvtn.www
  dBD
  1.0-SNAPSHOT
  jar

  dBD
  http://maven.apache.org

  
    UTF-8
    1.7.25
    1.2.17
  

  
    
      junit
      junit
      3.8.1
      test
    

    

    
      org.slf4j
      slf4j-api
      ${slf4j.version}
    
    
      org.slf4j
      slf4j-log4j12
      ${slf4j.version}
    
    
      log4j
      log4j
      ${log4j.version}
    

    
    
      org.json
      json
      20170516
    

    
    
      org.apache.avro
      avro
      1.8.2
    

    
    
      org.apache.flume
      flume-ng-core
      1.7.0
    

    
    
      org.apache.flume.flume-ng-clients
      flume-ng-log4jappender
      1.7.0
    

    
    
      org.apache.avro
      avro-ipc
      1.8.2
    

  

• log4j.properties

################### set log levels ###############
log4j.rootLogger = INFO,stdout,file,flume

################### flume ########################
log4j.appender.flume = org.apache.flume.clients.log4jappender.Log4jAppender
log4j.appender.flume.layout = org.apache.log4j.PatternLayout
log4j.appender.flume.Hostname = localhost
log4j.appender.flume.Port = 44446

################## stdout #######################
log4j.appender.stdout = org.apache.log4j.ConsoleAppender
log4j.appender.stdout.Threshold = INFO
log4j.appender.stdout.Target = System.out
log4j.appender.stdout.layout = org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern = %d{yyyy-MM-dd HH:mm:ss} %c{1} [%p] %m%n

################## file ##########################
log4j.appender.file = org.apache.log4j.DailyRollingFileAppender
log4j.appender.file.Threshold = INFO
log4j.appender.file.File = /Users/david.tian/logs/tracker/tracker.log
log4j.appender.file.Append = true
log4j.appender.file.DatePattern = '.'yyyy-MM-dd
log4j.appender.file.layout = org.apache.log4j.PatternLayout
log4j.appender.file.layout.ConversionPattern = %d{yyyy-MM-dd HH:mm:ss} %c{1} [%p] %m%n

• SendReceipts.java

package com.dvtn.www.log4j.jsonlog;

import com.dvtn.www.log4j.logfile.LogProducer;
import com.dvtn.www.model.Area;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.*;
import java.util.*;

/**
 * Created by david.tian on 08/09/2017.
 */
public class SendReceipts {
    private static Logger LOG = LoggerFactory.getLogger(LogProducer.class);
    private static String path = SendReceipts.class.getResource("/").getPath();
    private static String areaJsonString;
    private static String city;
    private static String cityKey;
    private static String province;
    private static String provinceKey;
    private static int separator;

    private static String phonePrefix;
    //private static final Random rnd = new Random();

    private static String[] payers = {"Merchants", "Individuals"};
    private static String[] managers = {"david", "josen", "fab", "simon", "banana", "tom", "scott", "ekrn", "sunshine", "lily", "kudu", "scala", "spark", "flume", "storm", "kafka", "avro", "linux"};
    private static String[] terminalTypes = {"RNM", "CNM", "RNM", "GNM", "CNJ", "GNJ", "RNJ", "GNM", "CNM"};
    private static String[] stores = {"连锁店", "分营店", "工厂店", "会员店", "直销店"};
    private static String[] items = {"面包","酒","油","牛奶","蔬菜","猪肉","牛肉","羊肉","曲奇","手机","耳机","面粉","大米","糖","苹果","茶叶","书","植物","玩具","床","锅","牙膏","洗衣粉","酱油","金鱼","干货"};
    private static String[] itemsType ={"食物","酒水","饮料","日用品","电子","数码","娱乐","家俱"};


    public static void main(String[] args) {

        Timer timer = new Timer();
        timer.schedule(new TimerTask() {
            @Override
            public void run() {

                Random rnd = new Random();

                ProduceReceipts pr = new ProduceReceipts();
                areaJsonString = pr.readJSON(path, "area.json");

                String transactionID = System.currentTimeMillis() + ""+Math.round(Math.random() * 9000 + 1000);
                String transactionDate = System.currentTimeMillis() + "";
                String taxNumber = Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000);
                String invoiceId = System.currentTimeMillis() + "";
                String invoiceNumber = Math.round(Math.random() * 900000000 + 100000000) + "";
                String invoiceDate = System.currentTimeMillis() + "";
                List listArea = pr.listArea(areaJsonString);
                int idx = rnd.nextInt(listArea.size());
                String provinceID = listArea.get(idx).getProvinceID();
                String provinceName = listArea.get(idx).getProvinceName();
                String cityID = listArea.get(idx).getCityID();
                String cityName = listArea.get(idx).getCityName();
                String telephone = provinceID + "-" + Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000);
                int managerSize = managers.length;
                String manger = managers[rnd.nextInt(managerSize)];
                int payerSize = payers.length;
                String payer = payers[rnd.nextInt(payerSize)];
                String operator = "OP" + Math.round(Math.random() * 90000 + 10000);
                int terminalTypeSize = terminalTypes.length;
                String terminalNumber = terminalTypes[rnd.nextInt(terminalTypeSize)] + Math.round(Math.random() * 90000 + 10000);
                String account = pr.StringReplaceWithStar(Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000));
                String tcNumber = Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000) + " " + Math.round(Math.random() * 9000 + 1000) + "";


                File file = new File(path + "receipts.avsc");

                String line = null;

                BufferedReader reader = null;
                try {
                    reader = new BufferedReader(new FileReader(file));

                    while ((line = reader.readLine()) != null) {
                        // System.out.println("========>" + line);
                    }
                    reader.close();
                } catch (IOException e) {
                    e.printStackTrace();
                } finally {
                    if (reader != null) {
                        try {
                            reader.close();
                        } catch (IOException e1) {
                        }
                    }
                }
                try {
                    //获得整个Schema
                    Schema schema = new Schema.Parser().parse(new File(path + "receipts.avsc"));

                    GenericRecord record = new GenericData.Record(schema);

                    //获取schema中的字段


                    int storesSize = stores.length;

                    //获取店面的Schema
                    Schema.Field  storeField = schema.getField("store");
                    Schema storeSchema =  storeField.schema();
                    GenericRecord storeRecord = new GenericData.Record(storeSchema);

                    String storeNumber = Math.round(Math.random() * 9000 + 1000) + "";
                    String address = provinceName + cityName;
                    String storeName = provinceName + cityName + stores[rnd.nextInt(storesSize)];

                    storeRecord.put("store_number",storeNumber);
                    storeRecord.put("store_name",storeName);
                    storeRecord.put("address",address);


                    int itemsSize = items.length;
                    int itemsTypeSize = itemsType.length;

                    List productRecordList = new ArrayList();
                    //获取product的schema
                    Schema.Field productField = schema.getField("products");
                    Schema productSchema = productField.schema();





                    for (int i=0; i< 10; i++){
                        String itemName = items[rnd.nextInt(1000)%itemsSize];
                        String itemType = itemsType[rnd.nextInt(1000)%itemsTypeSize];
                        String quantity = String.valueOf(rnd.nextInt(100));
                        String price = String.valueOf(rnd.nextFloat()*100);
                        String discount = String.valueOf(rnd.nextFloat());


                        GenericRecord productRecord = new GenericData.Record(productSchema);

                        productRecord.put("item",itemName);
                        productRecord.put("item_type",itemType);
                        productRecord.put("quantity",quantity);
                        productRecord.put("price",price);
                        productRecord.put("discount",discount);
                        productRecordList.add(productRecord);
                    }


                    record.put("transaction_id",transactionID);
                    record.put("transaction_date",transactionDate);
                    record.put("invoice_id",invoiceId);
                    record.put("invoice_number",invoiceNumber);
                    record.put("telephone",telephone);
                    record.put("payer",payer);
                    record.put("store",storeRecord);
                    record.put("operator",operator);
                    record.put("terminal_number",terminalNumber);
                    record.put("products",productRecordList);
                    record.put("account",account);
                    record.put("tc_number",terminalNumber);

                    LOG.info(record.toString());

                } catch (IOException e) {
                    e.printStackTrace();
                }
            }
        }, 0, 1000);
    }
}

6.验证

在kafka机器上执行命令kafka-console-consumer.sh读取topic “dt-receipts”中看是否日志已被kafka收集：

[root@apollo ~]# kafka-console-consumer.sh --bootstrap-server 192.168.56.181:9092,192.168.56.182:9092,192.168.56.183:9092,192.168.56.184:9092 --from-beginning --topic dt-receipts

我们可以看到，数据已经收集到kafka里的dt-receipts的topic里面：