以下为测试代码,完成读取一张hbase上记录url和用户id的表,对其创建索引并进行简单的基于url的索引的代码。当取到search的结果后,就可以拿到想要的数据了。由于分词后将原始内容进行了反向索引,所以匹配就转化为了查询,速度相当快。
其中getDocumentFromHTable为读取一张hbase上己有的表,将url字段提取出来创建content索引。
创建索引的实质是用了HBaseIndexWriter和HBaseIndexReader两个分别继承自IndexWriter和IndexReader的类来做索引的读取和写入。同时使用了HBaseIndexStore来做存储。
而创建索引使用的分词等仍然是使用标准的lucene API。
注意hbasene使用的是hbase-0.20.5,需要修改少量源代码才能运行在0.90.x以上的版本中。
这里对创建索引表使用到的结构做下简单的说明,因为是lucene入门级水平,所以各位请尽管拍砖讨论。
索引表由以下几个CF构成:
- fm.sequence: 记录sequenceId,在执行createLuceneIndexTable时需要写死该CF的row为sequenceId,qulifier为qual.sequence,值为-1。可以不用理会
- fm.doc2int: DocumentId,每个document都会有一个这样的id,如果Field.Store设置为YES,则能在索引表中查询到该id并得到完整的内容。
- fm.termVector: 向量偏移,用于模糊查找,记录偏移量等信息
- fm.termFrequency:分词后的关键词在每个document中出现的频率,qulifier为documentId,value为出现次数
- fm.fields:记录了content内容,row为documentId,value为document的全文内容,它和fm.docint是相反的,后者是反向索引。
- fm.payloads:扩展CF,目前还没有用到
- import java.io.IOException;
- import org.apache.hadoop.conf.Configuration;
- import org.apache.hadoop.hbase.HBaseConfiguration;
- import org.apache.hadoop.hbase.client.HTable;
- import org.apache.hadoop.hbase.client.HTablePool;
- import org.apache.hadoop.hbase.client.Result;
- import org.apache.hadoop.hbase.client.ResultScanner;
- import org.apache.hadoop.hbase.client.Scan;
- import org.apache.lucene.analysis.standard.StandardAnalyzer;
- import org.apache.lucene.document.Document;
- import org.apache.lucene.document.Field;
- import org.apache.lucene.document.Fieldable;
- import org.apache.lucene.index.IndexReader;
- import org.apache.lucene.index.Term;
- import org.apache.lucene.search.IndexSearcher;
- import org.apache.lucene.search.ScoreDoc;
- import org.apache.lucene.search.TermQuery;
- import org.apache.lucene.search.TopDocs;
- import org.apache.lucene.util.Version;
- import org.hbasene.index.HBaseIndexReader;
- import org.hbasene.index.HBaseIndexStore;
- import org.hbasene.index.HBaseIndexWriter;
- public class test{
- static final String indexName = "myindex";
- static final String dataName = "t1";
- public static void main(String[] args) throws IOException {
- try{
- Configuration conf = HBaseConfiguration.create(); //hbase-site.xml in the classpath
- conf.set("hbase.rootdir", "hdfs://192.168.0.1:9000/hbase");
- conf.set("hbase.zookeeper.quorum", "192.168.0.1,192.168.0.2,192.168.0.3");
- HTablePool tablePool = new HTablePool(conf, 10);
- HBaseIndexStore.createLuceneIndexTable(indexName, conf, true);
- //Write
- HBaseIndexStore hbaseIndex = new HBaseIndexStore(tablePool, conf, indexName);
- HBaseIndexWriter writer = new HBaseIndexWriter(hbaseIndex, "content"); //Name of the primary key field.
- getDocument(writer);
- writer.close();
- //Read/Search
- IndexReader reader = new HBaseIndexReader(tablePool, indexName, "f");
- IndexSearcher searcher = new IndexSearcher(reader);
- Term term = new Term("content", "item.taobao.com");
- TermQuery termQuery = new TermQuery(term);
- TopDocs docs = searcher.search(termQuery, 3);
- searcher.close();
- }catch(IOException e){
- e.printStackTrace();
- throw e;
- }
- }
- private static void getDocument(HBaseIndexWriter writer) throws IOException{
- Document doc = new Document();
- doc.add(new Field("content", "some content some dog", Field.Store.YES,
- Field.Index.ANALYZED));
- writer.addDocument(doc, new StandardAnalyzer(Version.LUCENE_30));
- doc = new Document();
- doc.add(new Field("content", "some id", Field.Store.NO, Field.Index.ANALYZED));
- writer.addDocument(doc, new StandardAnalyzer(Version.LUCENE_30));
- doc = new Document();
- doc.add(new Field("content", "hot dog", Field.Store.YES, Field.Index.ANALYZED, Field.TermVector.WITH_POSITIONS));
- writer.addDocument(doc, new StandardAnalyzer(Version.LUCENE_30));
- }
- private static void getDocumentFromHTable(HTablePool tablePool, HBaseIndexWriter writer) throws IOException {
- Document doc = new Document();
- Scan scan = new Scan();
- HTable htable = (HTable)tablePool.getTable(dataName);
- ResultScanner results = htable.getScanner(scan);
- Result row;
- while((row = results.next()) != null){
- doc = new Document();
- String value = new String(row.getValue("test".getBytes(), null));
- String url = value.split(""")[2];
- doc.add(new Field("content", url, Field.Store.YES, Field.Index.ANALYZED, Field.TermVector.WITH_OFFSETS));
- writer.addDocument(doc, new StandardAnalyzer(Version.LUCENE_30));
- }
- }
- }
以下为运行后查看表的中情况: