springboot引入IK分词器，并提供使用示例

要在Spring Boot中使用IK分词器，您可以按照以下步骤进行操作：

1. 在pom.xml中添加以下依赖项：

<dependency>
    <groupId>com.github.ylz19980205</groupId>
    <artifactId>elasticsearch-analysis-ik</artifactId>
    <version>7.10.2</version>
</dependency>

2. 创建一个配置类，实现`org.elasticsearch.index.analysis.AnalysisProvider`接口，以提供自定义的IK分词器配置。例如：

@Configuration
public class IKAnalyzerConfig {

    @Bean(name = "ikTokenizer")
    public Tokenizer getIkTokenizer() {
        return new IKTokenizer();
    }

    @Bean(name = "ikTokenFilter")
    public TokenFilter getIkTokenFilter() {
        return new IKTokenFilter();
    }

    @Bean(name = "ikAnalyzer")
    public Analyzer getIkAnalyzer() {
        return new Analyzer() {
            @Override
            protected TokenStreamComponents createComponents(String fieldName) {
                Tokenizer tokenizer = getIkTokenizer();
                TokenFilter tokenFilter = getIkTokenFilter();
                return new TokenStreamComponents(tokenizer, tokenFilter);
            }
        };
    }

    private static class IKTokenizer extends Tokenizer {
        private final IKSegmenter ikSegmenter;

        public IKTokenizer() {
            this.ikSegmenter = new IKSegmenter(input, true);
        }

        @Override
        public boolean incrementToken() throws IOException {
            // 实现自定义分词逻辑
            // ...
        }
    }

    private static class IKTokenFilter extends TokenFilter {
        private final CharTermAttribute termAtt = addAttribute(CharTermAttribute.class);

        protected IKTokenFilter(TokenStream input) {
            super(input);
        }

        @Override
        public boolean incrementToken() throws IOException {
            // 实现自定义过滤逻辑
            // ...
        }
    }
}

3. 在应用程序中使用自定义的IK分词器，例如：

@Autowired
private Analyzer ikAnalyzer;

// 使用IK分词器进行分词
public List<String> analyze(String text) throws IOException {
    List<String> result = new ArrayList<>();
    TokenStream tokenStream = ikAnalyzer.tokenStream("text", text);
    tokenStream.reset();
    while (tokenStream.incrementToken()) {
        CharTermAttribute charTermAttribute = tokenStream.getAttribute(CharTermAttribute.class);
        result.add(charTermAttribute.toString());
    }
    tokenStream.end();
    tokenStream.close();
    return result;
}

这是一个简单的示例，您可以根据自己的需求进行调整。