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Hadoop之——HBASE结合MapReduce批量导入数据
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废话不多说。直接上代码,你懂得
package hbase; import java.text.SimpleDateFormat; import java.util.Date; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.hbase.client.Put; import org.apache.hadoop.hbase.mapreduce.TableOutputFormat; import org.apache.hadoop.hbase.mapreduce.TableReducer; import org.apache.hadoop.hbase.util.Bytes; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Counter; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; /** * HBASE结合MapReduce批量导入 * @author liuyazhuang */ public class BatchImport { static class BatchImportMapper extends Mapper<LongWritable, Text, LongWritable, Text>{ SimpleDateFormat dateformat1=new SimpleDateFormat("yyyyMMddHHmmss"); Text v2 = new Text(); protected void map(LongWritable key, Text value, Context context) throws java.io.IOException ,InterruptedException { final String[] splited = value.toString().split("\t"); try { final Date date = new Date(Long.parseLong(splited[0].trim())); final String dateFormat = dateformat1.format(date); String rowKey = splited[1]+":"+dateFormat; v2.set(rowKey+"\t"+value.toString()); context.write(key, v2); } catch (NumberFormatException e) { final Counter counter = context.getCounter("BatchImport", "ErrorFormat"); counter.increment(1L); System.out.println("出错了"+splited[0]+" "+e.getMessage()); } }; } static class BatchImportReducer extends TableReducer<LongWritable, Text, NullWritable>{ protected void reduce(LongWritable key, java.lang.Iterable<Text> values, Context context) throws java.io.IOException ,InterruptedException { for (Text text : values) { final String[] splited = text.toString().split("\t"); final Put put = new Put(Bytes.toBytes(splited[0])); put.add(Bytes.toBytes("cf"), Bytes.toBytes("date"), Bytes.toBytes(splited[1])); put.add(Bytes.toBytes("cf"), Bytes.toBytes("msisdn"), Bytes.toBytes(splited[2])); //省略其它字段,调用put.add(....)就可以 context.write(NullWritable.get(), put); } }; } public static void main(String[] args) throws Exception { final Configuration configuration = new Configuration(); //设置zookeeper configuration.set("hbase.zookeeper.quorum", "hadoop0"); //设置hbase表名称 configuration.set(TableOutputFormat.OUTPUT_TABLE, "wlan_log"); //将该值改大,防止hbase超时退出 configuration.set("dfs.socket.timeout", "180000"); final Job job = new Job(configuration, "HBaseBatchImport"); job.setMapperClass(BatchImportMapper.class); job.setReducerClass(BatchImportReducer.class); //设置map的输出,不设置reduce的输出类型 job.setMapOutputKeyClass(LongWritable.class); job.setMapOutputValueClass(Text.class); job.setInputFormatClass(TextInputFormat.class); //不再设置输出路径,而是设置输出格式类型 job.setOutputFormatClass(TableOutputFormat.class); FileInputFormat.setInputPaths(job, "hdfs://hadoop0:9000/input"); job.waitForCompletion(true); } }
Hadoop之——HBASE结合MapReduce批量导入数据
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