我需要以最有效的方式替换字符串中的许多不同子字符串。除了使用string.replace替换每个字段的强力方法以外，还有其他方法吗？

如果您要处理的字符串很长，或者您要处理许多字符串，那么使用java.util.regex.Matcher可能是值得的（这需要花很长时间进行编译，因此效率不高） （如果您的输入很小或搜索模式经常更改）。

以下是一个完整的示例，基于从地图中获取的令牌列表。（使用来自Apache Commons Lang的StringUtils）。

Map<String,String> tokens = new HashMap<String,String>();
tokens.put("cat", "Garfield");
tokens.put("beverage", "coffee");

String template = "%cat% really needs some %beverage%.";

// Create pattern of the format "%(cat|beverage)%"
String patternString = "%(" + StringUtils.join(tokens.keySet(), "|") + ")%";
Pattern pattern = Pattern.compile(patternString);
Matcher matcher = pattern.matcher(template);

StringBuffer sb = new StringBuffer();
while(matcher.find()) {
    matcher.appendReplacement(sb, tokens.get(matcher.group(1)));
}
matcher.appendTail(sb);

System.out.println(sb.toString());

编译正则表达式后，扫描输入字符串通常会非常快（尽管如果您的正则表达式很复杂或涉及回溯，那么您仍然需要进行基准测试以确认这一点！）

算法

替换匹配字符串（不使用正则表达式）的最有效方法之一是将Aho-Corasick算法与高性能Trie（发音为“ try”）一起使用，使用快速哈希算法并实现有效的集合实现。

简单代码

一个简单的解决方案利用了Apache的StringUtils.replaceEach以下功能：

  private String testStringUtils(
    final String text, final Map<String, String> definitions ) {
    final String[] keys = keys( definitions );
    final String[] values = values( definitions );

    return StringUtils.replaceEach( text, keys, values );
  }

这会减慢大文本的速度。

快速代码

Bor对Aho-Corasick算法的实现引入了更多的复杂性，这通过使用具有相同方法签名的外观来实现细节：

  private String testBorAhoCorasick(
    final String text, final Map<String, String> definitions ) {
    // Create a buffer sufficiently large that re-allocations are minimized.
    final StringBuilder sb = new StringBuilder( text.length() << 1 );

    final TrieBuilder builder = Trie.builder();
    builder.onlyWholeWords();
    builder.removeOverlaps();

    final String[] keys = keys( definitions );

    for( final String key : keys ) {
      builder.addKeyword( key );
    }

    final Trie trie = builder.build();
    final Collection<Emit> emits = trie.parseText( text );

    int prevIndex = 0;

    for( final Emit emit : emits ) {
      final int matchIndex = emit.getStart();

      sb.append( text.substring( prevIndex, matchIndex ) );
      sb.append( definitions.get( emit.getKeyword() ) );
      prevIndex = emit.getEnd() + 1;
    }

    // Add the remainder of the string (contains no more matches).
    sb.append( text.substring( prevIndex ) );

    return sb.toString();
  }

基准测试

对于基准测试，缓冲区是使用randomNumeric创建的，如下所示：

  private final static int TEXT_SIZE = 1000;
  private final static int MATCHES_DIVISOR = 10;

  private final static StringBuilder SOURCE
    = new StringBuilder( randomNumeric( TEXT_SIZE ) );

其中MATCHES_DIVISOR指示要注入的变量数：

  private void injectVariables( final Map<String, String> definitions ) {
    for( int i = (SOURCE.length() / MATCHES_DIVISOR) + 1; i > 0; i-- ) {
      final int r = current().nextInt( 1, SOURCE.length() );
      SOURCE.insert( r, randomKey( definitions ) );
    }
  }

基准代码本身（JMH似乎有些过分）：

long duration = System.nanoTime();
final String result = testBorAhoCorasick( text, definitions );
duration = System.nanoTime() - duration;
System.out.println( elapsed( duration ) );

1,000,000：1,000

一个简单的微基准测试，包含1,000,000个字符和1,000个随机放置的字符串以进行替换。

• testStringUtils： 25秒，25533毫秒
• testBorAhoCorasick： 0秒，68毫秒

没有比赛。

10,000：1,000

使用10,000个字符和1,000个匹配字符串替换：

• testStringUtils： 1秒，1402毫秒
• testBorAhoCorasick： 0秒，37毫秒

鸿沟关闭。

1,000：10

使用1,000个字符和10个匹配的字符串替换：

• testStringUtils： 0秒，7毫秒
• testBorAhoCorasick： 0秒，19毫秒

对于短字符串，设置Aho-Corasick的开销使的蛮力方法黯然失色StringUtils.replaceEach。

基于文本长度的混合方法是可能的，以便获得两种实现的最佳效果。

实作

考虑比较文本长度大于1 MB的其他实现，包括：

• https://github.com/RokLenarcic/AhoCorasick
• https://github.com/hankcs/AhoCorasickDoubleArrayTrie
• https://github.com/raymanrt/aho-corasick
• https://github.com/ssundaresan/Aho-Corasick
• https://github.com/jmhsieh/aho-corasick
• https://github.com/quest-oss/Mensa

文件

与该算法有关的论文和信息：

• http://www.cs.uku.fi/research/publications/reports/A-2005-2.pdf
• https://pdfs.semanticscholar.org/3547/ac839d02f6efe3f6f76a8289738a22528442.pdf
• http://www.ece.ncsu.edu/asic/ece792A/2009/ECE792A/Readings_files/00989753.pdf
• http://blog.ivank.net/aho-corasick-algorithm-in-as3.html

这对我有用：

String result = input.replaceAll("string1|string2|string3","replacementString");

例：

String input = "applemangobananaarefruits";
String result = input.replaceAll("mango|are|ts","-");
System.out.println(result);

输出： apple-banana-frui-

如果您要多次更改String，那么使用StringBuilder通常会更有效（但要评估您的性能以找出答案）：

String str = "The rain in Spain falls mainly on the plain";
StringBuilder sb = new StringBuilder(str);
// do your replacing in sb - although you'll find this trickier than simply using String
String newStr = sb.toString();

每次对String进行替换时，都会创建一个新的String对象，因为String是不可变的。StringBuilder是可变的，也就是说，可以根据需要进行任意更改。

StringBuilder由于可以将其字符数组缓冲区指定为所需的长度，因此将更有效地执行替换。StringBuilder设计的不仅仅是追加！

当然，真正的问题是这是否太优化了？JVM非常擅长处理多个对象的创建以及后续的垃圾回收，并且像所有优化问题一样，我的第一个问题是您是否已测量并确定这是一个问题。

如何使用replaceAll（）方法？

现在发布的Java模板引擎Rythm具有称为字符串插值模式的新功能，可让您执行以下操作：

String result = Rythm.render("@name is inviting you", "Diana");

上面的案例显示您可以按位置将参数传递给模板。Rythm还允许您按名称传递参数：

Map<String, Object> args = new HashMap<String, Object>();
args.put("title", "Mr.");
args.put("name", "John");
String result = Rythm.render("Hello @title @name", args);

注意Rythm非常快，比String.format和Velocity快2到3倍，因为它将模板编译成Java字节代码，因此运行时性能非常接近StringBuilder。

链接：

• 查看功能齐全的演示
• 阅读节奏简介
• 下载最新软件包或
• 叉子

以下内容基于Todd Owen的答案。该解决方案的问题在于，如果替换包含在正则表达式中具有特殊含义的字符，则可能会得到意外的结果。我还希望能够有选择地进行不区分大小写的搜索。这是我想出的：

/**
 * Performs simultaneous search/replace of multiple strings. Case Sensitive!
 */
public String replaceMultiple(String target, Map<String, String> replacements) {
  return replaceMultiple(target, replacements, true);
}

/**
 * Performs simultaneous search/replace of multiple strings.
 * 
 * @param target        string to perform replacements on.
 * @param replacements  map where key represents value to search for, and value represents replacem
 * @param caseSensitive whether or not the search is case-sensitive.
 * @return replaced string
 */
public String replaceMultiple(String target, Map<String, String> replacements, boolean caseSensitive) {
  if(target == null || "".equals(target) || replacements == null || replacements.size() == 0)
    return target;

  //if we are doing case-insensitive replacements, we need to make the map case-insensitive--make a new map with all-lower-case keys
  if(!caseSensitive) {
    Map<String, String> altReplacements = new HashMap<String, String>(replacements.size());
    for(String key : replacements.keySet())
      altReplacements.put(key.toLowerCase(), replacements.get(key));

    replacements = altReplacements;
  }

  StringBuilder patternString = new StringBuilder();
  if(!caseSensitive)
    patternString.append("(?i)");

  patternString.append('(');
  boolean first = true;
  for(String key : replacements.keySet()) {
    if(first)
      first = false;
    else
      patternString.append('|');

    patternString.append(Pattern.quote(key));
  }
  patternString.append(')');

  Pattern pattern = Pattern.compile(patternString.toString());
  Matcher matcher = pattern.matcher(target);

  StringBuffer res = new StringBuffer();
  while(matcher.find()) {
    String match = matcher.group(1);
    if(!caseSensitive)
      match = match.toLowerCase();
    matcher.appendReplacement(res, replacements.get(match));
  }
  matcher.appendTail(res);

  return res.toString();
}

这是我的单元测试用例：

@Test
public void replaceMultipleTest() {
  assertNull(ExtStringUtils.replaceMultiple(null, null));
  assertNull(ExtStringUtils.replaceMultiple(null, Collections.<String, String>emptyMap()));
  assertEquals("", ExtStringUtils.replaceMultiple("", null));
  assertEquals("", ExtStringUtils.replaceMultiple("", Collections.<String, String>emptyMap()));

  assertEquals("folks, we are not sane anymore. with me, i promise you, we will burn in flames", ExtStringUtils.replaceMultiple("folks, we are not winning anymore. with me, i promise you, we will win big league", makeMap("win big league", "burn in flames", "winning", "sane")));

  assertEquals("bcaacbbcaacb", ExtStringUtils.replaceMultiple("abccbaabccba", makeMap("a", "b", "b", "c", "c", "a")));
  assertEquals("bcaCBAbcCCBb", ExtStringUtils.replaceMultiple("abcCBAabCCBa", makeMap("a", "b", "b", "c", "c", "a")));
  assertEquals("bcaacbbcaacb", ExtStringUtils.replaceMultiple("abcCBAabCCBa", makeMap("a", "b", "b", "c", "c", "a"), false));

  assertEquals("c colon  backslash temp backslash  star  dot  star ", ExtStringUtils.replaceMultiple("c:\\temp\\*.*", makeMap(".", " dot ", ":", " colon ", "\\", " backslash ", "*", " star "), false));
}

private Map<String, String> makeMap(String ... vals) {
  Map<String, String> map = new HashMap<String, String>(vals.length / 2);
  for(int i = 1; i < vals.length; i+= 2)
    map.put(vals[i-1], vals[i]);
  return map;
}

public String replace(String input, Map<String, String> pairs) {
  // Reverse lexic-order of keys is good enough for most cases,
  // as it puts longer words before their prefixes ("tool" before "too").
  // However, there are corner cases, which this algorithm doesn't handle
  // no matter what order of keys you choose, eg. it fails to match "edit"
  // before "bed" in "..bedit.." because "bed" appears first in the input,
  // but "edit" may be the desired longer match. Depends which you prefer.
  final Map<String, String> sorted = 
      new TreeMap<String, String>(Collections.reverseOrder());
  sorted.putAll(pairs);
  final String[] keys = sorted.keySet().toArray(new String[sorted.size()]);
  final String[] vals = sorted.values().toArray(new String[sorted.size()]);
  final int lo = 0, hi = input.length();
  final StringBuilder result = new StringBuilder();
  int s = lo;
  for (int i = s; i < hi; i++) {
    for (int p = 0; p < keys.length; p++) {
      if (input.regionMatches(i, keys[p], 0, keys[p].length())) {
        /* TODO: check for "edit", if this is "bed" in "..bedit.." case,
         * i.e. look ahead for all prioritized/longer keys starting within
         * the current match region; iff found, then ignore match ("bed")
         * and continue search (find "edit" later), else handle match. */
        // if (better-match-overlaps-right-ahead)
        //   continue;
        result.append(input, s, i).append(vals[p]);
        i += keys[p].length();
        s = i--;
      }
    }
  }
  if (s == lo) // no matches? no changes!
    return input;
  return result.append(input, s, hi).toString();
}

检查一下：

String.format(str,STR[])

例如：

String.format( "Put your %s where your %s is", "money", "mouth" );

简介：Dave答案的单类实现，可以自动选择两种算法中最有效的一种。

这是一个完整的单类实现，基于Dave Jarvis的上述出色回答。该类自动在提供的两种不同算法之间进行选择，以实现最高效率。（此答案适用于希望快速复制和粘贴的人。）

ReplaceStrings类：

package somepackage

import java.util.ArrayList;
import java.util.Collection;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;
import org.ahocorasick.trie.Emit;
import org.ahocorasick.trie.Trie;
import org.ahocorasick.trie.Trie.TrieBuilder;
import org.apache.commons.lang3.StringUtils;

/**
 * ReplaceStrings, This class is used to replace multiple strings in a section of text, with high
 * time efficiency. The chosen algorithms were adapted from: https://stackoverflow.com/a/40836618
 */
public final class ReplaceStrings {

    /**
     * replace, This replaces multiple strings in a section of text, according to the supplied
     * search and replace definitions. For maximum efficiency, this will automatically choose
     * between two possible replacement algorithms.
     *
     * Performance note: If it is known in advance that the source text is long, then this method
     * signature has a very small additional performance advantage over the other method signature.
     * (Although either method signature will still choose the best algorithm.)
     */
    public static String replace(
        final String sourceText, final Map<String, String> searchReplaceDefinitions) {
        final boolean useLongAlgorithm
            = (sourceText.length() > 1000 || searchReplaceDefinitions.size() > 25);
        if (useLongAlgorithm) {
            // No parameter adaptations are needed for the long algorithm.
            return replaceUsing_AhoCorasickAlgorithm(sourceText, searchReplaceDefinitions);
        } else {
            // Create search and replace arrays, which are needed by the short algorithm.
            final ArrayList<String> searchList = new ArrayList<>();
            final ArrayList<String> replaceList = new ArrayList<>();
            final Set<Map.Entry<String, String>> allEntries = searchReplaceDefinitions.entrySet();
            for (Map.Entry<String, String> entry : allEntries) {
                searchList.add(entry.getKey());
                replaceList.add(entry.getValue());
            }
            return replaceUsing_StringUtilsAlgorithm(sourceText, searchList, replaceList);
        }
    }

    /**
     * replace, This replaces multiple strings in a section of text, according to the supplied
     * search strings and replacement strings. For maximum efficiency, this will automatically
     * choose between two possible replacement algorithms.
     *
     * Performance note: If it is known in advance that the source text is short, then this method
     * signature has a very small additional performance advantage over the other method signature.
     * (Although either method signature will still choose the best algorithm.)
     */
    public static String replace(final String sourceText,
        final ArrayList<String> searchList, final ArrayList<String> replacementList) {
        if (searchList.size() != replacementList.size()) {
            throw new RuntimeException("ReplaceStrings.replace(), "
                + "The search list and the replacement list must be the same size.");
        }
        final boolean useLongAlgorithm = (sourceText.length() > 1000 || searchList.size() > 25);
        if (useLongAlgorithm) {
            // Create a definitions map, which is needed by the long algorithm.
            HashMap<String, String> definitions = new HashMap<>();
            final int searchListLength = searchList.size();
            for (int index = 0; index < searchListLength; ++index) {
                definitions.put(searchList.get(index), replacementList.get(index));
            }
            return replaceUsing_AhoCorasickAlgorithm(sourceText, definitions);
        } else {
            // No parameter adaptations are needed for the short algorithm.
            return replaceUsing_StringUtilsAlgorithm(sourceText, searchList, replacementList);
        }
    }

    /**
     * replaceUsing_StringUtilsAlgorithm, This is a string replacement algorithm that is most
     * efficient for sourceText under 1000 characters, and less than 25 search strings.
     */
    private static String replaceUsing_StringUtilsAlgorithm(final String sourceText,
        final ArrayList<String> searchList, final ArrayList<String> replacementList) {
        final String[] searchArray = searchList.toArray(new String[]{});
        final String[] replacementArray = replacementList.toArray(new String[]{});
        return StringUtils.replaceEach(sourceText, searchArray, replacementArray);
    }

    /**
     * replaceUsing_AhoCorasickAlgorithm, This is a string replacement algorithm that is most
     * efficient for sourceText over 1000 characters, or large lists of search strings.
     */
    private static String replaceUsing_AhoCorasickAlgorithm(final String sourceText,
        final Map<String, String> searchReplaceDefinitions) {
        // Create a buffer sufficiently large that re-allocations are minimized.
        final StringBuilder sb = new StringBuilder(sourceText.length() << 1);
        final TrieBuilder builder = Trie.builder();
        builder.onlyWholeWords();
        builder.ignoreOverlaps();
        for (final String key : searchReplaceDefinitions.keySet()) {
            builder.addKeyword(key);
        }
        final Trie trie = builder.build();
        final Collection<Emit> emits = trie.parseText(sourceText);
        int prevIndex = 0;
        for (final Emit emit : emits) {
            final int matchIndex = emit.getStart();

            sb.append(sourceText.substring(prevIndex, matchIndex));
            sb.append(searchReplaceDefinitions.get(emit.getKeyword()));
            prevIndex = emit.getEnd() + 1;
        }
        // Add the remainder of the string (contains no more matches).
        sb.append(sourceText.substring(prevIndex));
        return sb.toString();
    }

    /**
     * main, This contains some test and example code.
     */
    public static void main(String[] args) {
        String shortSource = "The quick brown fox jumped over something. ";
        StringBuilder longSourceBuilder = new StringBuilder();
        for (int i = 0; i < 50; ++i) {
            longSourceBuilder.append(shortSource);
        }
        String longSource = longSourceBuilder.toString();
        HashMap<String, String> searchReplaceMap = new HashMap<>();
        ArrayList<String> searchList = new ArrayList<>();
        ArrayList<String> replaceList = new ArrayList<>();
        searchReplaceMap.put("fox", "grasshopper");
        searchReplaceMap.put("something", "the mountain");
        searchList.add("fox");
        replaceList.add("grasshopper");
        searchList.add("something");
        replaceList.add("the mountain");
        String shortResultUsingArrays = replace(shortSource, searchList, replaceList);
        String shortResultUsingMap = replace(shortSource, searchReplaceMap);
        String longResultUsingArrays = replace(longSource, searchList, replaceList);
        String longResultUsingMap = replace(longSource, searchReplaceMap);
        System.out.println(shortResultUsingArrays);
        System.out.println("----------------------------------------------");
        System.out.println(shortResultUsingMap);
        System.out.println("----------------------------------------------");
        System.out.println(longResultUsingArrays);
        System.out.println("----------------------------------------------");
        System.out.println(longResultUsingMap);
        System.out.println("----------------------------------------------");
    }
}

所需的Maven依赖项：

（如果需要，将它们添加到您的pom文件中。）

    <!-- Apache Commons utilities. Super commonly used utilities.
    https://mvnrepository.com/artifact/org.apache.commons/commons-lang3 -->
    <dependency>
        <groupId>org.apache.commons</groupId>
        <artifactId>commons-lang3</artifactId>
        <version>3.10</version>
    </dependency>

    <!-- ahocorasick, An algorithm used for efficient searching and 
    replacing of multiple strings.
    https://mvnrepository.com/artifact/org.ahocorasick/ahocorasick -->
    <dependency>
        <groupId>org.ahocorasick</groupId>
        <artifactId>ahocorasick</artifactId>
        <version>0.4.0</version>
    </dependency>