海量日志中统计次数最多的100个IP

由于标题长度限制,原题是这样:某系统QPS100万,每十分钟统计一下请求次数最多的100个IP。ip请求写到日志的话,其实就是超大文件中统计top k问题。10分钟6亿条记录,大约是10G级别,所以对于一般单机处理来讲不能一次性加载到内存计算。所以分治算法是处理这类问题的基本思想。

思路

前面说了分治思想。那么具体如何分解问题呢。

思路就是把大文件分割成多个可以内存处理的小文件,对每个小文件统计top k问题,最后再对所有统计结果合并得到最终的top k。

注意,这里的分割并不是随意分割的,那样最终结果显然是不对的,必须保证相同的ip记录都分割到同一个文件。那么hash算法最合适不过了,可以把相同的ip哈希到同一文件。

关于top k问题,效率高的解法是使用构造最小堆或者借助快速排序的思想,复杂度为O(nlogk)。这里更适合用最小堆,具体来说,就是先利用前k个数据构建一个固定大小k的最小堆,对之后的数据,小于堆顶不做处理,大于则替换堆顶并调整。这样,对每个文件顺序处理完之后就得到最终结果,而不需要保留每个文件的top k再归并。

实现

博主偷懒,借助TreeSet代替最小堆来维护top k数据,TreeSet的话底层是借助红黑树排序,比最小堆复杂些,实际上对每个小文件用红黑树全排序再截取前k个。复杂度O(nlogm),这里m是每个小文件中的数量, m>>k。再有时间的话再用最小堆优化一下,复杂度应为O(nlogk)。

ps:已实现最小堆版本,见实现2,并做了对比实验

定时任务使用quartz实现。

下面是代码。

IP类,封装ip计数,使用TreeSet存放须实现comparable接口。注意这里重写compare方法不要return 0,否则会被TreeSet视为相同对象而放不进去。这个可以看一下TreeSet的实现,它实际上内部还是一个TreeMap,只是把对象作为key,而value没有使用。add添加元素时,会调用TreeMap的put方法,put内部又会调用compare方法,如果compare返回结果为0,只是重新setValue,对TreeSet相当于什么也没做。

package com.hellolvs;

import org.apache.commons.lang3.builder.ToStringBuilder;

/**
 * IP计数POJO
 *
 * @author lvs
 * @date 2017/12/08.
 */
public class IP implements Comparable<IP> {

    private String ip;
    private int count;

    public IP() {
    }

    public IP(String ip, int count) {
        this.ip = ip;
        this.count = count;
    }

    public String getIp() {
        return ip;
    }

    public void setIp(String ip) {
        this.ip = ip;
    }

    public int getCount() {
        return count;
    }

    public void setCount(int count) {
        this.count = count;
    }

    @Override
    public int compareTo(IP o) {
        return o.count < this.count ? -1 : 1;
    }

    @Override
    public String toString() {
        return ToStringBuilder.reflectionToString(this);
    }
}

IPCountJob类,定时统计日志文件中top k个ip。

注意其中的分割文件,这里的分割需要对文件边读边写,不能一次性读入内存再分割。guava io的readLines是直接装入内存的,所以不能用。可以使用java原生的io类,或使用commons io的LineIterator更优雅一些。

package com.hellolvs;

import com.google.common.base.Charsets;
import com.google.common.base.Objects;
import com.google.common.base.StandardSystemProperty;
import com.google.common.collect.Maps;
import com.google.common.collect.Sets;
import com.google.common.io.Files;
import com.google.common.io.LineProcessor;
import org.apache.commons.io.FileUtils;
import org.apache.commons.io.LineIterator;
import org.quartz.Job;
import org.quartz.JobExecutionContext;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.BufferedWriter;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.nio.charset.Charset;
import java.security.SecureRandom;
import java.util.HashMap;
import java.util.Map;
import java.util.TreeSet;
import java.util.concurrent.atomic.AtomicInteger;

/**
 * 定时Job,每十分钟统计请求次数前k的ip
 *
 * @author lvs
 * @date 2017/12/08.
 */
public class IPCountJob implements Job {

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

    private static final String LINE_SEPARATOR = StandardSystemProperty.LINE_SEPARATOR.value();
    private static final Charset UTF_8 = Charsets.UTF_8;

    private static final String INPUT_PATH = "/home/lvs/logs/ip.log";
    private static final String OUTPUT_PATH = "/home/lvs/logs/split/";

    private static final int SPLIT_NUM = 1024;
    private static final int TOP_K = 100;

    /**
     * 利用TreeSet存储请求次数前k的IP
     */
    private TreeSet<IP> resultSet = Sets.newTreeSet();

    /**
     * 分割文件用,保存每个文件的写入流对象
     */
    private final Map<Integer, BufferedWriter> bufferMap = Maps.newHashMapWithExpectedSize(SPLIT_NUM);

    /**
     * 定时任务,每十分钟统计请求次数前k的IP
     */
    @Override
    public void execute(JobExecutionContext jobExecutionContext) {
        // 捕获异常,防止定时任务中断
        try {
            execute();
        } catch (Exception e) {
            LOG.error("定时任务出错:{}", e.getMessage(), e);
        }
    }

    /**
     * 统计大文件中请求次数前k的IP
     * 
     * @throws IOException I/O error
     */
    public void execute() throws IOException {
        // 这里应该每10分钟获取当前轮替日志文件路径,此处用常量路径模拟
        File ipLogFile = new File(INPUT_PATH);

        splitLog(ipLogFile, SPLIT_NUM);

        File logSplits = new File(OUTPUT_PATH);
        for (File logSplit : logSplits.listFiles()) {
            countTopK(logSplit, TOP_K);
        }

        LOG.info("结果集:{}", resultSet.size());
        for (IP ip : resultSet) {
            LOG.info("{}", ip);
        }
    }

    /**
     * 生成模拟日志文件
     * 
     * @param logNum 生成日志条数
     * @throws IOException I/O error
     */
    public static void generateLog(long logNum) throws IOException {

        /* 创建文件 */
        File log = new File(INPUT_PATH);
        File parentDir = log.getParentFile();
        if (!parentDir.exists()) {
            parentDir.mkdirs();
        }
        log.createNewFile();

        /* 生成随机ip写入文件 */
        SecureRandom random = new SecureRandom();
        try (BufferedWriter bw = new BufferedWriter(new FileWriter(log))) {
            for (int i = 0; i < logNum; i++) {
                StringBuilder sb = new StringBuilder();
                sb.append("192.").append(random.nextInt(255)).append(".").append(random.nextInt(255)).append(".")
                        .append(random.nextInt(255)).append(LINE_SEPARATOR);
                bw.write(sb.toString());
            }
            bw.flush();
        }
    }

    /**
     * 分割日志文件
     *
     * @param logFile 待分割文件
     * @param fileNum 分割文件数量
     * @throws IOException I/O error
     */
    private void splitLog(File logFile, int fileNum) throws IOException {

        /* 为每个分割文件创建写入流对象 */
        for (int i = 0; i < fileNum; i++) {
            File file = new File(OUTPUT_PATH + i);
            File parentDir = file.getParentFile();
            if (!parentDir.exists()) {
                parentDir.mkdirs();
            }
            bufferMap.put(i, new BufferedWriter(new FileWriter(file)));
        }

        /* 根据ip的hashcode将数据分割到不同文件中 */
        LineIterator it = null;
        try {
            it = FileUtils.lineIterator(logFile, "UTF-8");
            while (it.hasNext()) {
                String ip = it.nextLine();
                int hashCode = Objects.hashCode(ip);
                hashCode = hashCode < 0 ? -hashCode : hashCode;
                BufferedWriter writer = bufferMap.get(hashCode % fileNum);
                writer.write(ip + LINE_SEPARATOR);
            }
        } finally {
            /* 释放资源 */
            LineIterator.closeQuietly(it);
            for (Map.Entry<Integer, BufferedWriter> buffer : bufferMap.entrySet()) {
                BufferedWriter writer = buffer.getValue();
                writer.flush();
                writer.close();
            }
            bufferMap.clear();
        }
    }

    /**
     * 统计请求次数前k的IP
     *
     * @param logSplit 当前分割文件
     * @param k top k
     * @throws IOException I/O error
     */
    private void countTopK(File logSplit, int k) throws IOException {

        /* 读取文件对ip计数 */
        HashMap<String, AtomicInteger> ipCountMap = Files.readLines(logSplit, UTF_8,
                new LineProcessor<HashMap<String, AtomicInteger>>() {
                    private HashMap<String, AtomicInteger> ipCountMap = Maps.newHashMap();

                    @Override
                    public boolean processLine(String line) throws IOException {
                        AtomicInteger ipCount = ipCountMap.get(line.trim());
                        if (ipCount != null) {
                            ipCount.getAndIncrement();
                        } else {
                            ipCountMap.put(line.trim(), new AtomicInteger(1));
                        }
                        return true;
                    }

                    @Override
                    public HashMap<String, AtomicInteger> getResult() {
                        return ipCountMap;
                    }
                });

        /* 统计结果添加到TreeSet */
        for (Map.Entry<String, AtomicInteger> entry : ipCountMap.entrySet()) {
            resultSet.add(new IP(entry.getKey(), entry.getValue().get()));
        }

        /* TreeSet只保留前k个ip */
        TreeSet<IP> temp = Sets.newTreeSet();
        int i = 0;
        for (IP o : resultSet) {
            temp.add(o);
            i++;
            if (i >= k) {
                break;
            }
        }
        resultSet = temp;
    }

    /**
     * 返回统计结果
     *
     * @return 结果集合
     */
    public TreeSet<IP> getResult() {
        return resultSet;
    }
}

Main,定时任务启动

package com.hellolvs;

import org.quartz.JobBuilder;
import org.quartz.JobDetail;
import org.quartz.Scheduler;
import org.quartz.SimpleScheduleBuilder;
import org.quartz.Trigger;
import org.quartz.TriggerBuilder;
import org.quartz.impl.StdSchedulerFactory;

/**
 * 定时任务启动器
 * 
 * @author lvs
 * @date 2017/12/11.
 */
public class Main {
    public static void main(String[] args) throws Exception {
        // 生成模拟日志文件
        IPCountJob.generateLog(600000000);

        JobDetail job = JobBuilder.newJob(IPCountJob.class)
                .withIdentity("ipCountJob", "group1").build();

        Trigger trigger = TriggerBuilder
                .newTrigger()
                .withIdentity("ipCountTrigger", "group1")
                .withSchedule(
                        SimpleScheduleBuilder.simpleSchedule()
                                .withIntervalInMinutes(10).repeatForever())
                .build();

        Scheduler scheduler = new StdSchedulerFactory().getScheduler();
        scheduler.start();
        scheduler.scheduleJob(job, trigger);
    }
}

实现2

IP类

package com.hellolvs;

import org.apache.commons.lang3.builder.ToStringBuilder;

/**
 * IP计数POJO
 *
 * @author lvs
 * @date 2017/12/08.
 */
public class IP implements Comparable<IP> {

    private String ip;
    private int count;

    public IP() {
    }

    public IP(String ip, int count) {
        this.ip = ip;
        this.count = count;
    }

    public String getIp() {
        return ip;
    }

    public void setIp(String ip) {
        this.ip = ip;
    }

    public int getCount() {
        return count;
    }

    public void setCount(int count) {
        this.count = count;
    }

    @Override
    public int compareTo(IP o) {
        return Integer.compare(this.count, o.count);
    }

    @Override
    public String toString() {
        return ToStringBuilder.reflectionToString(this);
    }
}

IPCountJob类,最小堆版本统计top k

package com.hellolvs;

import com.google.common.base.Charsets;
import com.google.common.base.Objects;
import com.google.common.base.StandardSystemProperty;
import com.google.common.collect.Lists;
import com.google.common.collect.Maps;
import com.google.common.io.Files;
import com.google.common.io.LineProcessor;
import org.apache.commons.io.FileUtils;
import org.apache.commons.io.LineIterator;
import org.quartz.Job;
import org.quartz.JobExecutionContext;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.BufferedWriter;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.nio.charset.Charset;
import java.security.SecureRandom;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.atomic.AtomicInteger;

/**
 * 定时Job,每十分钟统计请求次数前k的ip
 *
 * @author lvs
 * @date 2017/12/08.
 */
public class IPCountJob implements Job {

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

    private static final String LINE_SEPARATOR = StandardSystemProperty.LINE_SEPARATOR.value();
    private static final Charset UTF_8 = Charsets.UTF_8;

    private static final String INPUT_PATH = "/home/lvs/logs/ip.log";
    private static final String OUTPUT_PATH = "/home/lvs/logs/split/";

    private static final int SPLIT_NUM = 1024;
    private static final int TOP_K = 100;

    /**
     * 利用最小堆结构存储请求次数前k的IP
     */
    private List<IP> result = Lists.newArrayListWithExpectedSize(TOP_K);

    /**
     * 分割文件用,保存每个文件的写入流对象
     */
    private final Map<Integer, BufferedWriter> bufferMap = Maps.newHashMapWithExpectedSize(SPLIT_NUM);

    /**
     * 定时任务,每十分钟统计请求次数前k的IP
     */
    @Override
    public void execute(JobExecutionContext jobExecutionContext) {
        // 捕获异常,防止定时任务中断
        try {
            execute();
        } catch (Exception e) {
            LOG.error("定时任务出错:{}", e.getMessage(), e);
        }
    }

    /**
     * 统计大文件中请求次数前k的IP
     * 
     * @throws IOException I/O error
     */
    public void execute() throws IOException {
        // 这里应该每10分钟获取当前轮替日志文件路径,此处用常量路径模拟
        File ipLogFile = new File(INPUT_PATH);

        splitLog(ipLogFile, SPLIT_NUM);
        File logSplits = new File(OUTPUT_PATH);
        for (File logSplit : logSplits.listFiles()) {
            countTopK(logSplit, TOP_K);
        }

        MinHeap.sort(result);
        LOG.info("结果集:{}", result.size());
        for (int i = result.size() - 1; i >= 0; i--) {
            LOG.info("{}", result.get(i));
        }
    }

    /**
     * 生成模拟日志文件
     * 
     * @param logNum 生成日志条数
     * @throws IOException I/O error
     */
    public static void generateLog(long logNum) throws IOException {

        /* 创建文件 */
        File log = new File(INPUT_PATH);
        File parentDir = log.getParentFile();
        if (!parentDir.exists()) {
            parentDir.mkdirs();
        }
        log.createNewFile();

        /* 生成随机ip写入文件 */
        SecureRandom random = new SecureRandom();
        try (BufferedWriter bw = new BufferedWriter(new FileWriter(log))) {
            for (int i = 0; i < logNum; i++) {
                StringBuilder sb = new StringBuilder();
                sb.append("192.").append(random.nextInt(255)).append(".").append(random.nextInt(255)).append(".")
                        .append(random.nextInt(255)).append(LINE_SEPARATOR);
                bw.write(sb.toString());
            }
            bw.flush();
        }
    }

    /**
     * 分割日志文件
     *
     * @param logFile 待分割文件
     * @param fileNum 分割文件数量
     * @throws IOException I/O error
     */
    private void splitLog(File logFile, int fileNum) throws IOException {

        /* 为每个分割文件创建写入流对象 */
        for (int i = 0; i < fileNum; i++) {
            File file = new File(OUTPUT_PATH + i);
            File parentDir = file.getParentFile();
            if (!parentDir.exists()) {
                parentDir.mkdirs();
            }
            bufferMap.put(i, new BufferedWriter(new FileWriter(file)));
        }

        /* 根据ip的hashcode将数据分割到不同文件中 */
        LineIterator it = null;
        try {
            it = FileUtils.lineIterator(logFile, "UTF-8");
            while (it.hasNext()) {
                String ip = it.nextLine();
                int hashCode = Objects.hashCode(ip);
                hashCode = hashCode < 0 ? -hashCode : hashCode;
                BufferedWriter writer = bufferMap.get(hashCode % fileNum);
                writer.write(ip + LINE_SEPARATOR);
            }
        } finally {
            /* 释放资源 */
            LineIterator.closeQuietly(it);
            for (Map.Entry<Integer, BufferedWriter> buffer : bufferMap.entrySet()) {
                BufferedWriter writer = buffer.getValue();
                writer.flush();
                writer.close();
            }
            bufferMap.clear();
        }
    }

    /**
     * 统计请求次数前k的IP
     *
     * @param logSplit 当前分割文件
     * @param k top k
     * @throws IOException I/O error
     */
    private void countTopK(File logSplit, int k) throws IOException {

        /* 读取文件对ip计数 */
        HashMap<String, AtomicInteger> ipCountMap = Files.readLines(logSplit, UTF_8,
                new LineProcessor<HashMap<String, AtomicInteger>>() {
                    private HashMap<String, AtomicInteger> ipCountMap = Maps.newHashMap();

                    @Override
                    public boolean processLine(String line) throws IOException {
                        AtomicInteger ipCount = ipCountMap.get(line.trim());
                        if (ipCount != null) {
                            ipCount.getAndIncrement();
                        } else {
                            ipCountMap.put(line.trim(), new AtomicInteger(1));
                        }
                        return true;
                    }

                    @Override
                    public HashMap<String, AtomicInteger> getResult() {
                        return ipCountMap;
                    }
                });

        /* 前k条数据用来构建初始最小堆,之后的数据比堆顶大则替换堆顶并调堆 */
        for (Map.Entry<String, AtomicInteger> entry : ipCountMap.entrySet()) {
            IP ip = new IP(entry.getKey(), entry.getValue().get());
            if (result.size() != k) {
                result.add(ip);
                if (result.size() == k) {
                    MinHeap.initMinHeap(result);
                }
            } else {
                if (ip.compareTo(result.get(0)) > 0) {
                    result.set(0, ip);
                    MinHeap.adjust(result, 0, k);
                }
            }
        }
    }

    /**
     * 返回统计结果
     *
     * @return 结果集合
     */
    public List<IP> getResult() {
        return result;
    }
}

MinHeap类,最小堆工具

package com.hellolvs;

import java.util.List;

/**
 * 最小堆
 *
 * @author lvs
 * @date 2017-12-12
 */
public class MinHeap {

    /**
     * 对最小堆排序
     * 
     * @param list 已经为最小堆结构的列表
     * @param <T> 元素须实现Comparable接口
     */
    public static <T extends Comparable<? super T>> void sort(List<T> list) {
        for (int i = list.size() - 1; i > 0; i--) {
            swap(list, 0, i);
            adjust(list, 0, i);
        }
    }

    /**
     * 初始化最小堆
     *
     * @param list 待初始化为最小堆的列表
     * @param <T> 元素须实现Comparable接口
     */
    public static <T extends Comparable<? super T>> void initMinHeap(List<T> list) {
        /* 从最后一个非叶节点开始至根节点依次调整 */
        for (int i = list.size() / 2 - 1; i >= 0; i--) {
            adjust(list, i, list.size());
        }
    }

    /**
     * 调堆
     *
     * @param list 当前堆
     * @param <T> 元素须实现Comparable接口
     * @param cur 待调整位置
     * @param length 当前堆大小
     */
    public static <T extends Comparable<? super T>> void adjust(List<T> list, int cur, int length) {
        T tmp = list.get(cur);
        for (int i = 2 * cur + 1; i < length; i = 2 * i + 1) {
            if (i + 1 < length && list.get(i).compareTo(list.get(i + 1)) > 0) {
                i++; // i指向孩子节点中最小的节点
            }
            if (tmp.compareTo(list.get(i)) > 0) {
                list.set(cur, list.get(i)); // 最小孩子节点调整到其父节点
                cur = i; // 当前节点置为最小孩子节点,继续调整
            } else {
                break; // 没有调整时退出循环
            }
        }
        list.set(cur, tmp); // 被调整节点最终存放位置
    }

    /**
     * 交换List中的元素
     * 
     * @param list 待交换列表
     * @param i 第一个元素位置
     * @param j 第二个元素位置
     */
    private static <T extends Comparable<? super T>> void swap(List<T> list, int i, int j) {
        T tmp = list.get(i);
        list.set(i, list.get(j));
        list.set(j, tmp);
    }
}

Main类,无改动

package com.hellolvs;

import org.quartz.JobBuilder;
import org.quartz.JobDetail;
import org.quartz.Scheduler;
import org.quartz.SimpleScheduleBuilder;
import org.quartz.Trigger;
import org.quartz.TriggerBuilder;
import org.quartz.impl.StdSchedulerFactory;

/**
 * 定时任务启动器
 * 
 * @author lvs
 * @date 2017/12/11.
 */
public class Main {
    public static void main(String[] args) throws Exception {
        // 生成模拟日志文件
        IPCountJob.generateLog(600000000);

        JobDetail job = JobBuilder.newJob(IPCountJob.class)
                .withIdentity("ipCountJob", "group1").build();

        Trigger trigger = TriggerBuilder
                .newTrigger()
                .withIdentity("ipCountTrigger", "group1")
                .withSchedule(
                        SimpleScheduleBuilder.simpleSchedule()
                                .withIntervalInMinutes(10).repeatForever())
                .build();

        Scheduler scheduler = new StdSchedulerFactory().getScheduler();
        scheduler.start();
        scheduler.scheduleJob(job, trigger);
    }
}

附一下pom文件:

<?xml version="1.0" encoding="UTF-8"?>
<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.hellolvs</groupId>
    <artifactId>ipCount</artifactId>
    <version>1.0.0</version>
    <packaging>jar</packaging>

    <properties>
        <guava.version>20.0</guava.version>
        <commons-lang3.version>3.1</commons-lang3.version>
        <commons-io.version>2.4</commons-io.version>
        <joda-time.version>2.6</joda-time.version>
        <org.quartz-scheduler.version>2.1.7</org.quartz-scheduler.version>
        <org.slf4j.version>1.7.5</org.slf4j.version>
        <logback.version>1.0.13</logback.version>
        <junit.version>4.10</junit.version>
        <java.version>1.8</java.version>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>

    <dependencyManagement>
        <dependencies>
            <!-- guava -->
            <dependency>
                <groupId>com.google.guava</groupId>
                <artifactId>guava</artifactId>
                <version>${guava.version}</version>
            </dependency>

            <!-- commons lang3-->
            <dependency>
                <groupId>org.apache.commons</groupId>
                <artifactId>commons-lang3</artifactId>
                <version>${commons-lang3.version}</version>
            </dependency>

            <!-- commons io -->
            <dependency>
                <groupId>commons-io</groupId>
                <artifactId>commons-io</artifactId>
                <version>${commons-io.version}</version>
            </dependency>

            <!-- joda-time -->
            <dependency>
                <groupId>joda-time</groupId>
                <artifactId>joda-time</artifactId>
                <version>${joda-time.version}</version>
            </dependency>

            <!-- quartz -->
            <dependency>
                <groupId>org.quartz-scheduler</groupId>
                <artifactId>quartz</artifactId>
                <version>${org.quartz-scheduler.version}</version>
            </dependency>

            <!-- slf4j -->
            <dependency>
                <groupId>org.slf4j</groupId>
                <artifactId>slf4j-api</artifactId>
                <version>${org.slf4j.version}</version>
            </dependency>

            <!-- logback -->
            <dependency>
                <groupId>ch.qos.logback</groupId>
                <artifactId>logback-classic</artifactId>
                <version>${logback.version}</version>
                <scope>runtime</scope>
            </dependency>
            <dependency>
                <groupId>ch.qos.logback</groupId>
                <artifactId>logback-core</artifactId>
                <version>${logback.version}</version>
                <scope>runtime</scope>
            </dependency>

            <!-- junit -->
            <dependency>
                <groupId>junit</groupId>
                <artifactId>junit-dep</artifactId>
                <version>${junit.version}</version>
                <scope>test</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>

    <dependencies>
        <!-- guava -->
        <dependency>
            <groupId>com.google.guava</groupId>
            <artifactId>guava</artifactId>
        </dependency>

        <!-- commons lang3-->
        <dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-lang3</artifactId>
        </dependency>

        <!-- commons io -->
        <dependency>
            <groupId>commons-io</groupId>
            <artifactId>commons-io</artifactId>
        </dependency>

        <!-- joda-time -->
        <dependency>
            <groupId>joda-time</groupId>
            <artifactId>joda-time</artifactId>
        </dependency>

        <!-- quartz -->
        <dependency>
            <groupId>org.quartz-scheduler</groupId>
            <artifactId>quartz</artifactId>
        </dependency>

        <!-- slf4j -->
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
        </dependency>

        <!-- logback -->
        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-classic</artifactId>
        </dependency>
        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-core</artifactId>
        </dependency>

        <!-- junit -->
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit-dep</artifactId>
        </dependency>
    </dependencies>

    <build>
        <finalName>ROOT</finalName>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>${java.version}</source>
                    <target>${java.version}</target>
                    <encoding>${project.build.sourceEncoding}</encoding>
                </configuration>
            </plugin>
        </plugins>
    </build>

</project>

对比实验

生成了6亿条数据的日志。

TreeSet版本:

生成6亿条日志时间:521582
分割文件时间:173219
分割后统计top k时间:195037
定时任务执行时间:368294

注:定时任务执行时间指的是对大文件的总统计时间,主要是分割文件+分割后统计top k。

cpu和堆使用情况:

可以看到堆变化明显分为三阶段:对应了生成日志、分割日志、分割后统计top k。

图片描述

最小堆版本:

生成6亿条日志时间:513840
分割文件时间:148861
分割后统计top k时间:190966
定时任务执行时间:339870

cpu和堆使用情况:

图片描述

总结:

生成日志和分割文件是没有改动的,运行时间不一样,可能有一定误差。

倒是两个版本统计top k时间没有明显的变化,按上面分析O(nlogm)和O(nlogk)应该有比较明显的差距才对,这里n=600000000,m约600000,k=100,各位可以帮忙分析一下效率差距不大的原因。

不过可以看到堆内存使用明显降低了约100MB,因为TreeSet需要添加m个元素再截取k个,而MinHeap只需要添加k个元素。

个人博客:www.hellolvs.cn

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