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package com.hbase.index; import java.io.IOException; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.hbase.HBaseConfiguration; import org.apache.hadoop.mapreduce.Counter; import org.apache.hadoop.mapreduce.Job; import org.slf4j.Logger; import org.slf4j.LoggerFactory; public class RebuildHbaseIndex { public static final Logger LOG = LoggerFactory .getLogger(RebuildHbaseIndex.class); public static void main(String[] args) throws IOException,ClassNotFoundException, InterruptedException { Configuration conf = HBaseConfiguration.create(); conf.setBoolean("mapred.map.tasks.speculative.execution", false); //每次读取100条数据 conf.setInt("hbase.client.scanner.caching", 100); String[] tbNames={"Suggest"}; for(int i=0;i package com.hbase.index; import java.io.IOException; import java.util.ArrayList; import java.util.List; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.hbase.KeyValue; import org.apache.hadoop.hbase.client.Result; import org.apache.hadoop.hbase.client.Scan; import org.apache.hadoop.hbase.io.ImmutableBytesWritable; import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil; import org.apache.hadoop.hbase.mapreduce.TableMapper; import org.apache.hadoop.hbase.util.Bytes; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.lib.output.NullOutputFormat; import org.apache.solr.client.solrj.SolrServer; import org.apache.solr.client.solrj.SolrServerException; import org.apache.solr.client.solrj.impl.HttpSolrServer; import org.apache.solr.common.SolrInputDocument; import org.slf4j.Logger; import org.slf4j.LoggerFactory; public class SolrIndexerMapper extends TableMapper{ public static final Logger LOG = LoggerFactory.getLogger(SolrIndexerMapper.class); //计数器 public static enum Counters {ROWS}; //只创建一个SolrServer实例 private SolrServer solr; public String solrURL="http://192.168.1.79:8983/solr/IK_shard1_replica1"; private int commitSize; private final List docs=new ArrayList (); //任务开始调用 protected void setup(Context context){ Configuration conf=context.getConfiguration(); solr=new HttpSolrServer(solrURL); //一次性添加文档数 commitSize=conf.getInt("solr.commit.size", 1000); } @Override protected void map(ImmutableBytesWritable row, Result values,Context context)throws IOException, InterruptedException { SolrInputDocument solrDoc = new SolrInputDocument(); String rowkey=Bytes.toString(values.getRow()); String id=Bytes.toString(values.getRow()); String tableName="Suggest"; solrDoc.addField("id", id); solrDoc.addField("rowkey", rowkey); //hbase里面需要增加tableName字段 solrDoc.addField("tableName", tableName); for (KeyValue kv : values.list()) { String fieldName = Bytes.toString(kv.getQualifier()); String fieldValue = Bytes.toString(kv.getValue()); solrDoc.addField(fieldName, fieldValue); } docs.add(solrDoc); if (docs.size() >= commitSize) { try { LOG.info("添加文档:Adding " + Integer.toString(docs.size()) + " documents"); solr.add(docs); // 索引文档 } catch (final SolrServerException e) { final IOException ioe = new IOException(); ioe.initCause(e); throw ioe; } docs.clear(); } context.getCounter(Counters.ROWS).increment(1); } //任务结束时候调用 @Override protected void cleanup(org.apache.hadoop.mapreduce.Mapper.Context context) throws IOException, InterruptedException { try { if(!docs.isEmpty()){ LOG.info("清空队列:Adding " + Integer.toString(docs.size()) + " documents"); solr.add(docs); docs.clear(); } } catch (final SolrServerException e) { final IOException ioe=new IOException(); ioe.initCause(e); throw ioe; } } public static Job createSubmittableJob(Configuration conf, String tableName) throws IOException { Job job=Job.getInstance(conf,"SolrIndex_" + tableName); job.setJarByClass(SolrIndexerMapper.class); Scan scan=new Scan(); //scan的数据不放在缓存中,一次性的 scan.setCacheBlocks(false); job.setOutputFormatClass(NullOutputFormat.class); TableMapReduceUtil.initTableMapperJob(tableName, scan, SolrIndexerMapper.class, null, null, job); // 不需要输出,键、值类型为null job.setNumReduceTasks(0); // 无reduce任务 return job; } } 看完了这篇文章,相信你对“Mapreduce如何扫描hbase表建立solr索引”有了一定的了解,如果想了解更多相关知识,欢迎关注创新互联行业资讯频道,感谢各位的阅读!
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