log4j+flume+HDFS实现日志存储

1. HDFS配置

1.1.Hadoop集群搭建

有关HDFS的配置，请参考CentOS7.0下Hadoop2.7.3的集群搭建,为了容易操作，本示例采用单机模式, 即解压hadoop到/opt/hadoop/目录下;

1.2.hdfs配置

• $HADOOP_HOME/etc/hadoop/core-site.xml配置

<configuration>        <property>                  <name>fs.defaultFS</name>                  <value>hdfs://localhost:9000</value>        </property></configuration>

• $HADOOP_HOME/etc/hadoop/hdfs-site.xml

<configuration>          <property>                    <name>dfs.replication</name>                    <value>1</value>          </property></configuration>

1.3.启动Hadoop

[itlocals-MacBook-Pro: david.tian]$sh $HADOOP_HOME/sbin/start-all.sh

1.4.HDFS创建/flume目录

itlocals-MacBook-Pro: david.tian$hadoop fs -mkdir /flume

1.5.HDFS修改目录读写权限

itlocals-MacBook-Pro: david.tian$hadoop fs -chmod -R 777 /flume

2.flume的安装与配置

2.1.把flume解压到/opt/flume目录下

2.2.在$FLUME_HOME/conf/目录下新建配置文件flume2hdfs

a1.sources=r1a1.channels=c1a1.sinks=k1a1.sources.r1.type=avroa1.sources.r1.bind=localhosta1.sources.r1.port=44446a1.channels.c1.type=memorya1.channels.c1.capacity=1000a1.channels.c1.transactionCapacity=1000a1.channels.c1.keep-alive=30a1.sinks.k1.type=hdfsa1.sinks.k1.hdfs.path=hdfs://localhost:9000/flumea1.sinks.k1.hdfs.fileType=DataStreama1.sinks.k1.hdfs.writeFormat=Texta1.sinks.k1.hdfs.rollInterval=100a1.sinks.k1.hdfs.rollSize=10240a1.sinks.k1.hdfs.rollCount=0a1.sinks.k1.hdfs.idleTimeout=600a1.sources.r1.channels = c1a1.sinks.k1.channel = c1

2.3.Flume HDFS Sink重要参数说明

• type: 指flume输出的类型为hdfs
• path: 写入hdfs的路径，需要包含文件系统的标识，如hdfs://localhost:9000/flume
• filePrefix: 默认值为FlumeData,写入hdfs的文件名前缀，可以使用flume提供的日期及%{host}表达式；
• fileSuffix: 写入hdfs文件后名后缀，比如：.lzo, .log等；
• inUsePrefix: 临时文件的文件名前缀，hdfs sink会先往目标目录中写临时文件，再根据相关规则重命名成最终目录文件；
• inUseSuffix: 默认值.tmp，临时文件的文件名后缀；
• rollInterval: 默认值30, 指hdfs sink间隔多长将临时文件滚动成最终上标文件，单位：秒；如果设置为，则表示不根据时间来滚动文件；
• rollSize: 默认值1024,当临时文件达到该大小（单位：bytes）时，滚动成目标文件；如果设置为0,则表示不根据临时文件大小来滚动文件；
• rollCount: 默认值为10, 当events数据达到该数量时，将临时文件滚动成目标文件；如果设置为0,表示不根据events数据来滚动文件；
• idleTimeout: 默认值为0, 当目前被打开的临时文件在该参数指定的时间（秒）内，没有任何数据写入，则将该临时文件关闭并重命名成目标文件；
• batchSize: 默认值为100,每个批次刷新到HDFS上的events数量；
• codeC: 文件压缩格式，包括：gzip, bzip2, lzo, lzop, snappy;
• fileType: 默认值为SequenceFile，文件格式主要包括：SequenceFile, DataStream, CompressedStream；当使用DataStream时，文件不会被压缩，则不需要设置hdfs.codeC; 当使用CompressedStream时，则必须设置一个正确的hdfs.codeC值；
• maxOpenFiles: 默认值5000,最大允许打开的HDFS文件数，当打开的文件数达到该值，最早打开的文件将会被关闭；
• minBlockReplicas: 默认值为HDFS副本数；写入HDFS文件块的最小副本数，该参数会影响文件的滚动配置，一般将该参数配置成1,才可以按照配置正确滚动文件；
• writeFormat: 写sequence文件的格式，包含：Text, Writable(默认）；
• callTimeout: 默认值为10000,执行HDFS操作的超时时间（单位为毫秒）；
• threadsPoolSize: 默认值为10, 指hdfs sink启动的操作HDFS的线程数；
• rollTimerPoolSize: 默认值为1, hdfs sink启动国的根据时间滚动文件的线程数；
• kerberosPrincipal: HDFS安全认证kerberos配置；
• kerberosKeytab: HDFS安全认证kerberos配置；
• proxyUser: 代理用户；
• round: 默认值为false， 指是否启用时间上的“舍弃”，这里的舍弃类似于“四舍五入”，如果启用，则会影响除了%t的其它所有时间有达式；
• roundValue: 默认值为1, 时间上进行“舍弃”的值；
• roundUnit: 默认值seconds, 时间上进行“舍弃”的单位，包含second, minute, hour，例如：

a1.sinks.k1.hdfs.round = truea1.sinks.k1.hdfs.roundValue = 10a1.sinks.k1.hdfs.roundUnit = minute

因为设置的是舍弃10分钟内的时间，因此，该目录每10分钟新生成一个；

• timeZone: 默认值为Local Time时区；
• useLocalTimeStamp: 默认值为false，是否使用当地时间。
• closeTries: 默认值为0,表示hdfs sink关闭文件的尝试次数，当一次关闭失败后，hdfs sink会继续尝试下次关闭，直到成功；如果设置为1,当一次关闭文件失败后，hdfs sink将不会再次尝试关闭文件，这个未关闭的文件将会一直留在那，并且是打开状态；
• retryInterval: 默认值为180秒，hdfs sink尝试关闭文件的时间间隔，如果设置为0,表示不尝试，相当于将hdfs.closeTries设置成1;
• serializer: 默认值为TEXT，指序列化类型，其它的序列化类型还有avro_event或者是所有实现了EventSerializer.Builder的类名；

2.4.启动flume

[itlocals-MacBook-Pro:flume david.tian]$  bin/flume-ng agent -n a1 -c conf/ --conf-file conf/flume2hdfs.conf -Dflume.root.logger=DEBUG,console

3. log4j发日志到flume

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

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

• pom.xml

<project xmlns="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">  <modelVersion>4.0.0</modelVersion>  <groupId>com.dvtn.www</groupId>  <artifactId>dBD</artifactId>  <version>1.0-SNAPSHOT</version>  <packaging>jar</packaging>  <name>dBD</name>  <url>http://maven.apache.org</url>  <properties>    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>    <slf4j.version>1.7.25</slf4j.version>    <log4j.version>1.2.17</log4j.version>  </properties>  <dependencies>    <dependency>      <groupId>junit</groupId>      <artifactId>junit</artifactId>      <version>3.8.1</version>      <scope>test</scope>    </dependency>    <!-- Log Dependency 日志依赖-->    <dependency>      <groupId>org.slf4j</groupId>      <artifactId>slf4j-api</artifactId>      <version>${slf4j.version}</version>    </dependency>    <dependency>      <groupId>org.slf4j</groupId>      <artifactId>slf4j-log4j12</artifactId>      <version>${slf4j.version}</version>    </dependency>    <dependency>      <groupId>log4j</groupId>      <artifactId>log4j</artifactId>      <version>${log4j.version}</version>    </dependency>    <!-- https://mvnrepository.com/artifact/org.json/json -->    <dependency>      <groupId>org.json</groupId>      <artifactId>json</artifactId>      <version>20170516</version>    </dependency>    <!-- https://mvnrepository.com/artifact/org.apache.avro/avro -->    <dependency>      <groupId>org.apache.avro</groupId>      <artifactId>avro</artifactId>      <version>1.8.2</version>    </dependency>    <!-- https://mvnrepository.com/artifact/org.apache.flume/flume-ng-core -->    <dependency>      <groupId>org.apache.flume</groupId>      <artifactId>flume-ng-core</artifactId>      <version>1.7.0</version>    </dependency>    <!-- https://mvnrepository.com/artifact/org.apache.flume.flume-ng-clients/flume-ng-log4jappender -->    <dependency>      <groupId>org.apache.flume.flume-ng-clients</groupId>      <artifactId>flume-ng-log4jappender</artifactId>      <version>1.7.0</version>    </dependency>    <!-- https://mvnrepository.com/artifact/org.apache.avro/avro-ipc -->    <dependency>      <groupId>org.apache.avro</groupId>      <artifactId>avro-ipc</artifactId>      <version>1.8.2</version>    </dependency>  </dependencies></project>

• log4j.properties

################### set log levels ###############log4j.rootLogger = INFO,stdout,file,flume################### flume ########################log4j.appender.flume = org.apache.flume.clients.log4jappender.Log4jAppenderlog4j.appender.flume.layout = org.apache.log4j.PatternLayoutlog4j.appender.flume.Hostname = localhostlog4j.appender.flume.Port = 44446################## stdout #######################log4j.appender.stdout = org.apache.log4j.ConsoleAppenderlog4j.appender.stdout.Threshold = INFOlog4j.appender.stdout.Target = System.outlog4j.appender.stdout.layout = org.apache.log4j.PatternLayoutlog4j.appender.stdout.layout.ConversionPattern = %d{yyyy-MM-dd HH:mm:ss} %c{1} [%p] %m%n################## file ##########################log4j.appender.file = org.apache.log4j.DailyRollingFileAppenderlog4j.appender.file.Threshold = INFOlog4j.appender.file.File = /Users/david.tian/logs/tracker/tracker.loglog4j.appender.file.Append = truelog4j.appender.file.DatePattern = '.'yyyy-MM-ddlog4j.appender.file.layout = org.apache.log4j.PatternLayoutlog4j.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<Area> 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<GenericRecord> productRecordList = new ArrayList<GenericRecord>();                    //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);    }}

3.3.启动log4j程序发日志

4.验证

4.1.查看flume运行情况

4.2.查看HDFS收集的文件

4.3.打开HDFS上任一文件验证内容