我用Java几分钟处理完30亿个数据...
肉眼品世界
共 18870字，需浏览 38分钟
·
2022-05-18 19:14
来源: https://c1n.cn/GM8hb
目录
场景说明
模拟数据
场景分析
读取数据
处理数据
遇到的问题
场景说明
23,31,42,19,60,30,36,........
模拟数据
package bigdata;
import java.io.*;
import java.util.Random;
/**
* @Desc:
* @Author: bingbing
* @Date: 2022/5/4 0004 19:05
*/
public class GenerateData {
private static Random random = new Random();
public static int generateRandomData(int start, int end) {
return random.nextInt(end - start + 1) + start;
}
/**
* 产生10G的 1-1000的数据在D盘
*/
public void generateData() throws IOException {
File file = new File("D:\ User.dat");
if (!file.exists()) {
try {
file.createNewFile();
} catch (IOException e) {
e.printStackTrace();
}
}
int start = 18;
int end = 70;
long startTime = System.currentTimeMillis();
BufferedWriter bos = new BufferedWriter(new OutputStreamWriter(new FileOutputStream(file, true)));
for (long i = 1; i < Integer.MAX_VALUE * 1.7; i++) {
String data = generateRandomData(start, end) + ",";
bos.write(data);
// 每100万条记录成一行，100万条数据大概4M
if (i % 1000000 == 0) {
bos.write("\n");
}
}
System.out.println("写入完成! 共花费时间:" + (System.currentTimeMillis() - startTime) / 1000 + " s");
bos.close();
}
public static void main(String[] args) {
GenerateData generateData = new GenerateData();
try {
generateData.generateData();
} catch (IOException e) {
e.printStackTrace();
}
}
}
准备好 10G 数据后，接着写如何处理这些数据。
场景分析
10G 的数据比当前拥有的运行内存大的多，不能全量加载到内存中读取，如果采用全量加载，那么内存会直接爆掉，只能按行读取，Java 中的 bufferedReader 的 readLine() 按行读取文件里的内容。
读取数据
private static void readData() throws IOException {
BufferedReader br = new BufferedReader(new InputStreamReader(new FileInputStream(FILE_NAME), "utf-8"));
String line;
long start = System.currentTimeMillis();
int count = 1;
while ((line = br.readLine()) != null) {
// 按行读取
// SplitData.splitLine(line);
if (count % 100 == 0) {
System.out.println("读取100行,总耗时间: " + (System.currentTimeMillis() - start) / 1000 + " s");
System.gc();
}
count++;
}
running = false;
br.close();
}
处理数据
| 思路一：通过单线程处理
for (int i = start; i <= end; i++) {
try {
File subFile = new File(dir + "\" + i + ".dat");
if (!file.exists()) {
subFile.createNewFile();
}
countMap.computeIfAbsent(i + "", integer -> new AtomicInteger(0));
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
public static void splitLine(String lineData) {
String[] arr = lineData.split(",");
for (String str : arr) {
if (StringUtils.isEmpty(str)) {
continue;
}
countMap.computeIfAbsent(str, s -> new AtomicInteger(0)).getAndIncrement();
}
}
private static void findMostAge() {
Integer targetValue = 0;
String targetKey = null;
Iterator<Map.Entry<String, AtomicInteger>> entrySetIterator = countMap.entrySet().iterator();
while (entrySetIterator.hasNext()) {
Map.Entry<String, AtomicInteger> entry = entrySetIterator.next();
Integer value = entry.getValue().get();
String key = entry.getKey();
if (value > targetValue) {
targetValue = value;
targetKey = key;
}
}
System.out.println("数量最多的年龄为:" + targetKey + "数量为：" + targetValue);
}
完整代码：
package bigdata;
import org.apache.commons.lang3.StringUtils;
import java.io.*;
import java.util.*;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;
/**
* @Desc:
* @Author: bingbing
* @Date: 2022/5/4 0004 19:19
* 单线程处理
*/
public class HandleMaxRepeatProblem_v0 {
public static final int start = 18;
public static final int end = 70;
public static final String dir = "D:\dataDir";
public static final String FILE_NAME = "D:\ User.dat";
/**
* 统计数量
*/
private static Map countMap = new ConcurrentHashMap<>();
/**
* 开启消费的标志
*/
private static volatile boolean startConsumer = false;
/**
* 消费者运行保证
*/
private static volatile boolean consumerRunning = true;
/**
* 按照 "," 分割数据，并写入到countMap里
*/
static class SplitData {
public static void splitLine(String lineData) {
String[] arr = lineData.split(",");
for (String str : arr) {
if (StringUtils.isEmpty(str)) {
continue;
}
countMap.computeIfAbsent(str, s -> new AtomicInteger(0)).getAndIncrement();
}
}
}
/**
* init map
*/
static {
File file = new File(dir);
if (!file.exists()) {
file.mkdir();
}
for (int i = start; i <= end; i++) {
try {
File subFile = new File(dir + "\" + i + ".dat");
if (!file.exists()) {
subFile.createNewFile();
}
countMap.computeIfAbsent(i + "", integer -> new AtomicInteger(0));
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
}
public static void main(String[] args) {
new Thread(() -> {
try {
readData();
} catch (IOException e) {
e.printStackTrace();
}
}).start();
}
private static void readData() throws IOException {
BufferedReader br = new BufferedReader(new InputStreamReader(new FileInputStream(FILE_NAME), "utf-8"));
String line;
long start = System.currentTimeMillis();
int count = 1;
while ((line = br.readLine()) != null) {
// 按行读取，并向map里写入数据
SplitData.splitLine(line);
if (count % 100 == 0) {
System.out.println("读取100行,总耗时间: " + (System.currentTimeMillis() - start) / 1000 + " s");
try {
Thread.sleep(1000L);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
count++;
}
findMostAge();
br.close();
}
private static void findMostAge() {
Integer targetValue = 0;
String targetKey = null;
Iterator> entrySetIterator = countMap.entrySet().iterator();
while (entrySetIterator.hasNext()) {
Map.Entry entry = entrySetIterator.next();
Integer value = entry.getValue().get();
String key = entry.getKey();
if (value > targetValue) {
targetValue = value;
targetKey = key;
}
}
System.out.println(" 数量最多的年龄为:" + targetKey + "数量为：" + targetValue);
}
private static void clearTask() {
// 清理，同时找出出现字符最大的数
findMostAge();
System.exit(-1);
}
}
测试结果：总共花了 3 分钟读取完并统计完所有数据。
要想提高 CPU 的利用率，那么可以使用多线程去处理。下面我们使用多线程去解决这个 CPU 利用率低的问题。
| 思路二：分治法
使用多线程去消费读取到的数据。采用生产者、消费者模式去消费数据，因为在读取的时候是比较快的，单线程的数据处理能力比较差，因此思路一的性能阻塞在取数据方，又是同步的，所以导致整个链路的性能会变的很差。
所谓分治法就是分而治之，也就是说将海量数据分割处理。根据 CPU 的能力初始化 n 个线程，每一个线程去消费一个队列，这样线程在消费的时候不会出现抢占队列的问题。
①初始化阻塞队列
private static List> blockQueueLists = new LinkedList<>();
//每个队列容量为256
for (int i = 0; i < threadNums; i++) {
blockQueueLists.add(new LinkedBlockingQueue<>(256));
}
②生产者
private static AtomicLong count = new AtomicLong(0);
按照行数来计算队列的下标：long index=count.get()%threadNums。
static class SplitData {
public static void splitLine(String lineData) {
// System.out.println(lineData.length());
String[] arr = lineData.split("\n");
for (String str : arr) {
if (StringUtils.isEmpty(str)) {
continue;
}
long index = count.get() % threadNums;
try {
// 如果满了就阻塞
blockQueueLists.get((int) index).put(str);
} catch (InterruptedException e) {
e.printStackTrace();
}
count.getAndIncrement();
}
}
③消费者
队列线程私有化：消费方在启动线程的时候根据 index 去获取到指定的队列，这样就实现了队列的线程私有化。
private static void startConsumer() throws FileNotFoundException, UnsupportedEncodingException {
//如果共用一个队列，那么线程不宜过多，容易出现抢占现象
System.out.println("开始消费...");
for (int i = 0; i < threadNums; i++) {
final int index = i;
// 每一个线程负责一个queue，这样不会出现线程抢占队列的情况。
new Thread(() -> {
while (consumerRunning) {
startConsumer = true;
try {
String str = blockQueueLists.get(index).take();
countNum(str);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}).start();
}
}
多子线程分割字符串：由于从队列中多到的字符串非常的庞大，如果又是用单线程调用 split(",") 去分割，那么性能同样会阻塞在这个地方。
// 按照arr的大小，运用多线程分割字符串
private static void countNum(String str) {
int[] arr = new int[2];
arr[1] = str.length() / 3;
// System.out.println("分割的字符串为start位置为:" + arr[0] + ",end位置为:" + arr[1]);
for (int i = 0; i < 3; i++) {
final String innerStr = SplitData.splitStr(str, arr);
// System.out.println("分割的字符串为start位置为:" + arr[0] + ",end位置为:" + arr[1]);
new Thread(() -> {
String[] strArray = innerStr.split(",");
for (String s : strArray) {
countMap.computeIfAbsent(s, s1 -> new AtomicInteger(0)).getAndIncrement();
}
}).start();
}
}
分割字符串算法：分割时从 0 开始，按照等分的原则，将字符串 n 等份，每一个线程分到一份。
用一个 arr 数组的 arr[0] 记录每次的分割开始位置，arr[1] 记录每次分割的结束位置，如果遇到的开始的字符不为 ","，那么就 startIndex-1，如果结束的位置不为 ","，那么将 endIndex 向后移一位。
如果 endIndex 超过了字符串的最大长度，那么就把最后一个字符赋值给 arr[1]。
/**
* 按照 x坐标 来分割 字符串，如果切到的字符不为“，”， 那么把坐标向前或者向后移动一位。
*
* @param line
* @param arr 存放x1,x2坐标
* @return
*/
public static String splitStr(String line, int[] arr) {
int startIndex = arr[0];
int endIndex = arr[1];
char start = line.charAt(startIndex);
char end = line.charAt(endIndex);
if ((startIndex == 0 || start == ',') && end == ',') {
arr[0] = endIndex + 1;
arr[1] = arr[0] + line.length() / 3;
if (arr[1] >= line.length()) {
arr[1] = line.length() - 1;
}
return line.substring(startIndex, endIndex);
}
if (startIndex != 0 && start != ',') {
startIndex = startIndex - 1;
}
if (end != ',') {
endIndex = endIndex + 1;
}
arr[0] = startIndex;
arr[1] = endIndex;
if (arr[1] >= line.length()) {
arr[1] = line.length() - 1;
}
return splitStr(line, arr);
}
完整代码：
package bigdata;
import cn.hutool.core.collection.CollectionUtil;
import org.apache.commons.lang3.StringUtils;
import java.io.*;
import java.util.*;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.locks.ReentrantLock;
/**
* @Desc:
* @Author: bingbing
* @Date: 2022/5/4 0004 19:19
* 多线程处理
*/
public class HandleMaxRepeatProblem {
public static final int start = 18;
public static final int end = 70;
public static final String dir = "D:\dataDir";
public static final String FILE_NAME = "D:\ User.dat";
private static final int threadNums = 20;
/**
* key 为年龄， value为所有的行列表，使用队列
*/
private static Map> valueMap = new ConcurrentHashMap<>();
/**
* 存放数据的队列
*/
private static List> blockQueueLists = new LinkedList<>();
/**
* 统计数量
*/
private static Map countMap = new ConcurrentHashMap<>();
private static Map lockMap = new ConcurrentHashMap<>();
// 队列负载均衡
private static AtomicLong count = new AtomicLong(0);
/**
* 开启消费的标志
*/
private static volatile boolean startConsumer = false;
/**
* 消费者运行保证
*/
private static volatile boolean consumerRunning = true;
/**
* 按照 "," 分割数据，并写入到文件里
*/
static class SplitData {
public static void splitLine(String lineData) {
// System.out.println(lineData.length());
String[] arr = lineData.split("\n");
for (String str : arr) {
if (StringUtils.isEmpty(str)) {
continue;
}
long index = count.get() % threadNums;
try {
// 如果满了就阻塞
blockQueueLists.get((int) index).put(str);
} catch (InterruptedException e) {
e.printStackTrace();
}
count.getAndIncrement();
}
}
/**
* 按照 x坐标 来分割 字符串，如果切到的字符不为“，”， 那么把坐标向前或者向后移动一位。
*
* @param line
* @param arr 存放x1,x2坐标
* @return
*/
public static String splitStr(String line, int[] arr) {
int startIndex = arr[0];
int endIndex = arr[1];
char start = line.charAt(startIndex);
char end = line.charAt(endIndex);
if ((startIndex == 0 || start == ',') && end == ',') {
arr[0] = endIndex + 1;
arr[1] = arr[0] + line.length() / 3;
if (arr[1] >= line.length()) {
arr[1] = line.length() - 1;
}
return line.substring(startIndex, endIndex);
}
if (startIndex != 0 && start != ',') {
startIndex = startIndex - 1;
}
if (end != ',') {
endIndex = endIndex + 1;
}
arr[0] = startIndex;
arr[1] = endIndex;
if (arr[1] >= line.length()) {
arr[1] = line.length() - 1;
}
return splitStr(line, arr);
}
public static void splitLine0(String lineData) {
String[] arr = lineData.split(",");
for (String str : arr) {
if (StringUtils.isEmpty(str)) {
continue;
}
int keyIndex = Integer.parseInt(str);
ReentrantLock lock = lockMap.computeIfAbsent(keyIndex, lockMap -> new ReentrantLock());
lock.lock();
try {
valueMap.get(keyIndex).add(str);
} finally {
lock.unlock();
}
// boolean wait = true;
// for (; ; ) {
// if (!lockMap.get(Integer.parseInt(str)).isLocked()) {
// wait = false;
// valueMap.computeIfAbsent(Integer.parseInt(str), integer -> new Vector<>()).add(str);
// }
// // 当前阻塞，直到释放锁
// if (!wait) {
// break;
// }
// }
}
}
}
/**
* init map
*/
static {
File file = new File(dir);
if (!file.exists()) {
file.mkdir();
}
//每个队列容量为256
for (int i = 0; i < threadNums; i++) {
blockQueueLists.add(new LinkedBlockingQueue<>(256));
}
for (int i = start; i <= end; i++) {
try {
File subFile = new File(dir + "\" + i + ".dat");
if (!file.exists()) {
subFile.createNewFile();
}
countMap.computeIfAbsent(i + "", integer -> new AtomicInteger(0));
// lockMap.computeIfAbsent(i, lock -> new ReentrantLock());
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
}
public static void main(String[] args) {
new Thread(() -> {
try {
// 读取数据
readData();
} catch (IOException e) {
e.printStackTrace();
}
}).start();
new Thread(() -> {
try {
// 开始消费
startConsumer();
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (UnsupportedEncodingException e) {
e.printStackTrace();
}
}).start();
new Thread(() -> {
// 监控
monitor();
}).start();
}
/**
* 每隔60s去检查栈是否为空
*/
private static void monitor() {
AtomicInteger emptyNum = new AtomicInteger(0);
while (consumerRunning) {
try {
Thread.sleep(10 * 1000);
} catch (InterruptedException e) {
e.printStackTrace();
}
if (startConsumer) {
// 如果所有栈的大小都为0，那么终止进程
AtomicInteger emptyCount = new AtomicInteger(0);
for (int i = 0; i < threadNums; i++) {
if (blockQueueLists.get(i).size() == 0) {
emptyCount.getAndIncrement();
}
}
if (emptyCount.get() == threadNums) {
emptyNum.getAndIncrement();
// 如果连续检查指定次数都为空，那么就停止消费
if (emptyNum.get() > 12) {
consumerRunning = false;
System.out.println("消费结束...");
try {
clearTask();
} catch (Exception e) {
System.out.println(e.getCause());
} finally {
System.exit(-1);
}
}
}
}
}
}
private static void readData() throws IOException {
BufferedReader br = new BufferedReader(new InputStreamReader(new FileInputStream(FILE_NAME), "utf-8"));
String line;
long start = System.currentTimeMillis();
int count = 1;
while ((line = br.readLine()) != null) {
// 按行读取，并向队列写入数据
SplitData.splitLine(line);
if (count % 100 == 0) {
System.out.println("读取100行,总耗时间: " + (System.currentTimeMillis() - start) / 1000 + " s");
try {
Thread.sleep(1000L);
System.gc();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
count++;
}
br.close();
}
private static void clearTask() {
// 清理，同时找出出现字符最大的数
Integer targetValue = 0;
String targetKey = null;
Iterator> entrySetIterator = countMap.entrySet().iterator();
while (entrySetIterator.hasNext()) {
Map.Entry entry = entrySetIterator.next();
Integer value = entry.getValue().get();
String key = entry.getKey();
if (value > targetValue) {
targetValue = value;
targetKey = key;
}
}
System.out.println(" 数量最多的年龄为:" + targetKey + "数量为：" + targetValue);
System.exit(-1);
}
/**
* 使用linkedBlockQueue
*
* @throws FileNotFoundException
* @throws UnsupportedEncodingException
*/
private static void startConsumer() throws FileNotFoundException, UnsupportedEncodingException {
//如果共用一个队列，那么线程不宜过多，容易出现抢占现象
System.out.println("开始消费...");
for (int i = 0; i < threadNums; i++) {
final int index = i;
// 每一个线程负责一个queue，这样不会出现线程抢占队列的情况。
new Thread(() -> {
while (consumerRunning) {
startConsumer = true;
try {
String str = blockQueueLists.get(index).take();
countNum(str);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}).start();
}
}
// 按照arr的大小，运用多线程分割字符串
private static void countNum(String str) {
int[] arr = new int[2];
arr[1] = str.length() / 3;
// System.out.println("分割的字符串为start位置为:" + arr[0] + ",end位置为:" + arr[1]);
for (int i = 0; i < 3; i++) {
final String innerStr = SplitData.splitStr(str, arr);
// System.out.println("分割的字符串为start位置为:" + arr[0] + ",end位置为:" + arr[1]);
new Thread(() -> {
String[] strArray = innerStr.split(",");
for (String s : strArray) {
countMap.computeIfAbsent(s, s1 -> new AtomicInteger(0)).getAndIncrement();
}
}).start();
}
}
/**
* 后台线程去消费map里数据写入到各个文件里, 如果不消费，那么会将内存程爆
*/
private static void startConsumer0() throws FileNotFoundException, UnsupportedEncodingException {
for (int i = start; i <= end; i++) {
final int index = i;
BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(new FileOutputStream(dir + "\" + i + ".dat", false), "utf-8"));
new Thread(() -> {
int miss = 0;
int countIndex = 0;
while (true) {
// 每隔100万打印一次
int count = countMap.get(index).get();
if (count > 1000000 * countIndex) {
System.out.println(index + "岁年龄的个数为:" + countMap.get(index).get());
countIndex += 1;
}
if (miss > 1000) {
// 终止线程
try {
Thread.currentThread().interrupt();
bw.close();
} catch (IOException e) {
}
}
if (Thread.currentThread().isInterrupted()) {
break;
}
Vector lines = valueMap.computeIfAbsent(index, vector -> new Vector<>());
// 写入到文件里
try {
if (CollectionUtil.isEmpty(lines)) {
miss++;
Thread.sleep(1000);
} else {
// 100个一批
if (lines.size() < 1000) {
Thread.sleep(1000);
continue;
}
// 1000个的时候开始处理
ReentrantLock lock = lockMap.computeIfAbsent(index, lockIndex -> new ReentrantLock());
lock.lock();
try {
Iterator iterator = lines.iterator();
StringBuilder sb = new StringBuilder();
while (iterator.hasNext()) {
sb.append(iterator.next());
countMap.get(index).addAndGet(1);
}
try {
bw.write(sb.toString());
bw.flush();
} catch (IOException e) {
e.printStackTrace();
}
// 清除掉vector
valueMap.put(index, new Vector<>());
} finally {
lock.unlock();
}
}
} catch (InterruptedException e) {
}
}
}).start();
}
}
}
测试结果：
遇到的问题
解决方法：在读取一定数量后，可以让主线程暂停几秒，手动调用 GC。
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