hbase批量删除

2wnc66cl  于 2021-06-03  发布在  Hadoop
关注(0)|答案(2)|浏览(352)

使用mapreduce作业,我试图从hbase表中删除行。
我得到以下错误。

java.lang.ClassCastException: org.apache.hadoop.hbase.client.Delete cannot be cast to org.apache.hadoop.hbase.KeyValue
        at org.apache.hadoop.hbase.mapreduce.HFileOutputFormat$1.write(HFileOutputFormat.java:124)
        at org.apache.hadoop.mapred.ReduceTask$NewTrackingRecordWriter.write(ReduceTask.java:551)
        at org.apache.hadoop.mapreduce.task.TaskInputOutputContextImpl.write(TaskInputOutputContextImpl.java:85)
        at org.apache.hadoop.mapreduce.lib.reduce.WrappedReducer$Context.write(WrappedReducer.java:99)
        at org.apache.hadoop.mapreduce.Reducer.reduce(Reducer.java:144)
        at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:164)
        at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:610)
        at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:444)
        at org.apache.hadoop.mapred.Child$4.run(Child.java:268)
        at java.security.AccessController.doPrivileged(Native Method)
        at javax.security.auth.Subject.doAs(Subject.java:396)
        at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.

看起来这是由configureincrementalload将输出设置为keyvalue引起的。它只有putsortreducer和keyvaluessortreducer,但没有deletesortreducer。
我的代码:

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Delete;
import org.apache.hadoop.hbase.client.HTable;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.HFileOutputFormat;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
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;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class DeleteRows extends Configured implements Tool {

    public static class Map extends
            Mapper<LongWritable, Text, ImmutableBytesWritable, Delete> {

        ImmutableBytesWritable hKey = new ImmutableBytesWritable();
        Delete delRow;

        @Override
        protected void map(LongWritable key, Text value, Context context)
                throws IOException, InterruptedException {
            hKey.set(value.getBytes());
            delRow = new Delete(hKey.get());
            context.write(hKey, delRow);
            // Update counters
            context.getCounter("RowsDeleted", "Success").increment(1);
        }
    }

    @SuppressWarnings("deprecation")
    public int run(String[] args) throws Exception {
        Configuration conf = new Configuration();
        args = new GenericOptionsParser(conf, args).getRemainingArgs();
        HBaseConfiguration.addHbaseResources(conf);

        Job job = new Job(conf, "Delete stuff!");
        job.setJarByClass(DeleteRows.class);

        job.setMapperClass(Map.class);
        job.setMapOutputKeyClass(ImmutableBytesWritable.class);
        job.setMapOutputValueClass(Delete.class);

        job.setInputFormatClass(TextInputFormat.class);
        FileInputFormat.addInputPath(job, new Path(args[0]));

        HTable hTable = new HTable(args[2]);
        // Auto configure partitioner and reducer
        HFileOutputFormat.configureIncrementalLoad(job, hTable);
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        job.waitForCompletion(true);
        return (0);
    }

    public static void main(String[] args) throws Exception {
        int exitCode = ToolRunner.run(new DeleteRows(), args);
        System.exit(exitCode);
    }
}

有没有更好/更快的方法使用行键删除大量行?显然,删除Map器中的每一行是可能的,但是我认为这比将删除推送到正确的区域服务器要慢。

3ks5zfa0

3ks5zfa01#

您的目标是使用 Delete 流(实际删除标记为 KeyValue )在里面。标准的方法是 HFileOutputFormat . 事实上你只能把 KeyValue 更改为此格式,有2个标准异径管: PutSortReducer 以及 KeyValueSortReducer . 如果将reduce任务数设置为0,则实际上会传递所有任务 Delete 直接输出格式当然不行。
您最明显的选择:
添加减速机 DeleteSortReducer . 这样的减速机非常简单,你几乎可以复制。您只需要从delete中提取单个keyvalue流并对它们进行排序。 PutSortReducer 是你的好榜样。 Put 更改没有分类,所以这就是为什么需要这样的缩减器。
只是构造而不是流 Delete 但流是适当的 KeyValue 包含删除标记。这也许是提高速度的最好办法。

bfhwhh0e

bfhwhh0e2#

通过使用 TableMapReduceUtil.initTableReducerJob 设置减速器而不是 HFileOutputFormat.configureIncrementalLoad 代码运行良好。

TableMapReduceUtil.initTableReducerJob(tableName, null, job);
job.setNumReduceTasks(0);

但是,这仍然不会为completebulkload实用程序创建删除。它只执行delete rpc。

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