ES IK词库热更新简介
在实际工作中，我们经常需要更新ElasticSearch中IKAnalyzer插件的自定义词库，以获得更好的中文分词和搜索效果。在默认情况下，每次更新之后都需要重启ES集群才能生效，极其不方便。因此IKAnalyzer官方也提供了一种热更新的方法，在其GitHub主页上写道：
在其源码内部对应的是Monitor类，实现了Runnable接口。我们采用的ES版本是2.3.2，对应IK插件版本为1.9.2。
public class Monitor implements Runnable {
public static ESLogger logger= Loggers.getLogger("ik-analyzer");
private static CloseableHttpClient httpclient = HttpClients.createDefault();
private String last_modified;
private String eTags;
private String location;
public Monitor(String location) {
this.location = location;
this.last_modified = null;
this.eTags = null;
}
/**
* 监控流程：
* ①向词库服务器发送Head请求
* ②从响应中获取Last-Modify、ETags字段值，判断是否变化
* ③如果未变化，休眠1min，返回第①步
* ④如果有变化，重新加载词典
* ⑤休眠1min，返回第①步
*/
public void run() {
RequestConfig rc = RequestConfig.custom().setConnectionRequestTimeout(10*1000)
.setConnectTimeout(10*1000).setSocketTimeout(15*1000).build();
HttpHead head = new HttpHead(location);
head.setConfig(rc);
if (last_modified != null) {
head.setHeader("If-Modified-Since", last_modified);
}
if (eTags != null) {
head.setHeader("If-None-Match", eTags);
}
CloseableHttpResponse response = null;
try {
response = httpclient.execute(head);
if(response.getStatusLine().getStatusCode()==200){
if (!response.getLastHeader("Last-Modified").getValue().equalsIgnoreCase(last_modified)
||!response.getLastHeader("ETag").getValue().equalsIgnoreCase(eTags)) {
Dictionary.getSingleton().reLoadMainDict();
last_modified = response.getLastHeader("Last-Modified")==null?null:response.getLastHeader("Last-Modified").getValue();
eTags = response.getLastHeader("ETag")==null?null:response.getLastHeader("ETag").getValue();
}
}else if (response.getStatusLine().getStatusCode()==304) {
//noop
}else{
Dictionary.logger.info("remote_ext_dict {} return bad code {}" , location , response.getStatusLine().getStatusCode() );
}
} catch (Exception e) {
Dictionary.logger.error("remote_ext_dict {} error!",e , location);
}finally{
try {
if (response != null) {
response.close();
}
} catch (IOException e) {
logger.error(e.getMessage(), e);
}
}
}
}
原理很容易理解，但是我们按照它的标准实现起来就要颇费一番周折，并且还是得手动编辑词库文件。如果今后词库变大变多，或者想让运营人员也参与词库的管理，这种方式就有些僵硬了。因此，我们决定直接修改ES IK插件的源码，使之能够从MySQL表中定时拉取词库的更新，再通过MySQL设计一个简易的管理工具，一劳永逸。
在MySQL建表
建表语句如下：
create table es_dynamic_dict (
id int(11) primary key not null auto_increment,
word varchar(50) not null default '' comment '词条',
is_stopword tinyint(1) not null default '0' comment '是否为停止词, 1为是',
is_deleted tinyint(1) not null default '0' comment '删除状态, 1为删除',
last_update int(11) not null default '0' comment '最后更新时间',
key is_stopword_idx(is_stopword),
key is_deleted_idx(is_deleted),
key update_time_idx(last_update)
) engine=InnoDB default charset=utf8 comment='ES热更新词库表';
修改IK插件源码
将源码clone下来，先在pom文件中加入MySQL驱动的依赖：
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.30</version>
</dependency>
再在maven-assembly-plugin的描述符文件中，将MySQL驱动添加到依赖集合中。直接上图比较好说明一些：
然后找到源码中管理词典的类Dictionary，它位于org.wltea.analyzer.dic包。在相同的包下新建DatabaseDictionary类，代码如下：
public class DatabaseDictionary {
private static final ESLogger LOGGER = Loggers.getLogger("ik-analyzer");
private static final String DB_PROP_PATH = "ik/db-ext-dict.properties";
private static DatabaseDictionary instance;
private Properties dbProperties;
private Connection connection;
private String getDictRoot() {
return PathUtils.get(new File(
AnalysisIkPlugin.class.getProtectionDomain().getCodeSource().getLocation().getPath()
).getParent(), "config").toAbsolutePath().toString();
}
private DatabaseDictionary() {
try {
Class.forName("com.mysql.jdbc.Driver");
dbProperties = new Properties();
dbProperties.load(new FileInputStream(PathUtils.get(getDictRoot(), DB_PROP_PATH).toFile()));
// LOGGER.info("Loaded MySQL driver and " + DB_PROP_PATH);
} catch (ClassNotFoundException e) {
LOGGER.error("MySQL driver not found");
} catch (IOException e) {
LOGGER.error("Error reading file " + DB_PROP_PATH);
}
}
public static DatabaseDictionary getInstance() {
if (instance == null) {
synchronized (DatabaseDictionary.class) {
if (instance == null) {
instance = new DatabaseDictionary();
}
}
}
return instance;
}
private void initConnection() {
try {
connection = DriverManager.getConnection(
dbProperties.getProperty("jdbc.url"),
dbProperties.getProperty("jdbc.user"),
dbProperties.getProperty("jdbc.password")
);
// LOGGER.info("Created JDBC connnection");
} catch (SQLException e) {
LOGGER.error("Error creating JDBC connection: " + e.getMessage());
}
}
private void closeConnection(ResultSet resultSet, PreparedStatement statement) {
try {
if (resultSet != null) {
resultSet.close();
resultSet = null;
}
if (statement != null) {
statement.close();
statement = null;
}
if (connection != null) {
connection.close();
connection = null;
}
// LOGGER.info("Closed JDBC connnection");
} catch (SQLException e) {
LOGGER.error("Error closing connection: " + e.getMessage());
}
}
public Set<String> fetchWords(long lastUpdate, boolean isStopword, boolean isDeleted) {
initConnection();
Set<String> result = new HashSet<>();
PreparedStatement statement = null;
ResultSet resultSet = null;
try {
StringBuilder sql = new StringBuilder("select word from ");
sql.append(dbProperties.getProperty("ext_dict.table.name"));
sql.append(isDeleted ? " where is_deleted = 1 " : " where is_deleted = 0 ");
sql.append(isStopword ? "and is_stopword = 1 " : "and is_stopword = 0 ");
sql.append("and last_update >= ");
sql.append(lastUpdate);
statement = connection.prepareStatement(sql.toString());
resultSet = statement.executeQuery();
while (resultSet.next()) {
String word = resultSet.getString("word");
if (word != null && word.length() > 0) {
result.add(word);
}
}
LOGGER.info("Executed query: " + sql.toString() + ", return count: " + result.size());
} catch (SQLException e) {
LOGGER.error("Error executing query of words: " + e.getMessage());
} finally {
closeConnection(resultSet, statement);
}
return result;
}
}
就是一个标准的JDBC连接单例。为了提供基本的可配置性，数据库的连接地址、用户名、密码，以及热更新词库表的表名都通过一个.properties文件来获取。
回到词典类Dictionary，可以看到已经有了用于批量加载和卸载新词条的方法addWords()和disableWords()，但没有批量加载和卸载新停止词的方法，所以需要在它里面新写两个。singleton则是Dictionary的单例。
public void addStopwords(Collection<String> stopwords) {
if(stopwords != null) {
for(String word : stopwords){
if (word != null) {
singleton._StopWords.fillSegment(word.trim().toCharArray());
}
}
}
}
public void disableStopwords(Collection<String> stopwords) {
if (stopwords != null) {
for (String word : stopwords) {
if (word != null) {
singleton._StopWords.disableSegment(word.trim().toCharArray());
}
}
}
}
然后写一个线程用来执行词库的更新。新建一个DatabaseMonitor类，如下：
public class DatabaseMonitor implements Runnable {
private static final ESLogger LOGGER = Loggers.getLogger("ik-analyzer");
private int periodMinutes;
public DatabaseMonitor(int periodMinutes) {
this.periodMinutes = periodMinutes;
LOGGER.info("Constructed DatabaseMonitor");
}
@Override
public void run() {
try {
DatabaseDictionary dbDict = DatabaseDictionary.getInstance();
long lastUpdate = (System.currentTimeMillis() - periodMinutes * 60 * 1000) / 1000;
Set<String> words = dbDict.fetchWords(lastUpdate, false, false);
Set<String> stopwords = dbDict.fetchWords(lastUpdate, true, false);
Set<String> deletedWords = dbDict.fetchWords(lastUpdate, false, true);
Set<String> deletedStopwords = dbDict.fetchWords(lastUpdate, true, true);
Dictionary dict = Dictionary.getSingleton();
dict.addWords(words);
dict.addStopwords(stopwords);
dict.disableWords(deletedWords);
dict.disableStopwords(deletedStopwords);
// LOGGER.info("Updated dictionary from MySQL");
} catch (Throwable t) {
LOGGER.error("Caught throwable in DatabaseMonitor. Message: " + t.getMessage());
LOGGER.error("Stack trace:");
for (StackTraceElement trace : t.getStackTrace()) {
LOGGER.error(trace.toString());
}
}
}
}
最后，利用单线程的调度线程池来定期执行DatabaseMonitor线程。这个逻辑写在initial()方法中原定时逻辑的下面就行。
private static ScheduledExecutorService dbPool = Executors.newSingleThreadScheduledExecutor();
dbPool.scheduleAtFixedRate(new DatabaseMonitor(7), 1, 5, TimeUnit.MINUTES);
logger.info("Scheduled MySQL dictionary update");
调度的初始延时为1分钟，周期为5分钟。每次取得当前时间戳前7分钟（通过periodMinutes参数控制）内的变更进行操作，可以避免有缺漏。当然这个周期可以更短，或者同样做成可配置的，但对我们而言必要性并不大。
打包运行
代码修改的工作完成了，用Maven打包，将其中的elasticsearch-analysis-ik-1.9.2.jar和mysql-connector-java-5.1.30.jar上传到各个ES节点的${ES_HOME}/plugins/ik目录下即可。
然后在${ES_HOME}/plugins/ik/config/ik目录下新建db-ext-dict.properties文件，写入如下内容：
jdbc.url=jdbc\:mysql\://10.11.12.123\:3306/some_db?tinyInt1isBit=false
jdbc.user=some_user
jdbc.password=some_password
ext_dict.table.name=es_dynamic_dict
接下来滚动重启ES集群。这属于ES基操，复习一下步骤吧。
- 禁止分片分配：
curl -s -XPUT es0:9200/_cluster/settings -d '{
"transient" : {
"cluster.routing.allocation.enable" : "none"
}
}'
- 切换到es帐户，杀掉elasticsearch进程：
su - es
ps aux | grep elasticsearch
kill -9 1480
- 执行更新的操作。
- 重启ES进程：
bin/elasticsearch -d
- 重启分片分配：
curl -s -XPUT es0:9200/_cluster/settings -d '{
"transient" : {
"cluster.routing.allocation.enable" : "all"
}
}'
- 等待集群状态变成GREEN之后，重复操作其余的节点即可。
来做个测试。在MySQL表中插入一条记录：
replace into es_dynamic_dict values(1,'除你武器',0,0,unix_timestamp(now()));
等待更新的日志输出之后，尝试分词：
大功告成。
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