hadoop mapreduce：java.lang.UnsatisfiedLinkError：org.apache.hadoop.util.NativeCodeLoader.buildSupportsSappeppy（）Z [英] hadoop mapreduce: java.lang.UnsatisfiedLinkError: org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy()Z

问题描述

我试图从map-reduce作业写出一个活泼的块压缩序列文件。我使用
hadoop 2.0.0-cdh4.5.0和snappy-java 1.0.4.1

I am trying to write a snappy block compressed sequence file from a map-reduce job. I am using hadoop 2.0.0-cdh4.5.0, and snappy-java 1.0.4.1

这是我的代码：

package jinvestor.jhouse.mr;

import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.OutputStream;
import java.util.Arrays;
import java.util.List;

import jinvestor.jhouse.core.House;
import jinvestor.jhouse.core.util.HouseAvroUtil;
import jinvestor.jhouse.download.HBaseHouseDAO;

import org.apache.commons.io.IOUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocatedFileStatus;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.RemoteIterator;
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.LongWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.compress.CompressionCodec;
import org.apache.hadoop.io.compress.SnappyCodec;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
import org.apache.hadoop.mapreduce.Job;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.NamedVector;
import org.apache.mahout.math.VectorWritable;

/**
 * Produces mahout vectors from House entries in HBase.
 * 
 * @author Michael Scott Knapp
 * 
 */
public class HouseVectorizer {

    private final Configuration configuration;
    private final House minimumHouse;
    private final House maximumHouse;

    public HouseVectorizer(final Configuration configuration,
            final House minimumHouse, final House maximumHouse) {
        this.configuration = configuration;
        this.minimumHouse = minimumHouse;
        this.maximumHouse = maximumHouse;
    }

    public void vectorize() throws IOException, ClassNotFoundException, InterruptedException {
        JobConf jobConf = new JobConf();
        jobConf.setMapOutputKeyClass(LongWritable.class);
        jobConf.setMapOutputValueClass(VectorWritable.class);

        // we want the vectors written straight to HDFS,
        // the order does not matter.
        jobConf.setNumReduceTasks(0);

        Path outputDir = new Path("/home/cloudera/house_vectors");
        FileSystem fs = FileSystem.get(configuration);
        if (fs.exists(outputDir)) {
            fs.delete(outputDir, true);
        }

        FileOutputFormat.setOutputPath(jobConf, outputDir);

        // I want the mappers to know the max and min value
        // so they can normalize the data.
        // I will add them as properties in the configuration,
        // by serializing them with avro.
        String minmax = HouseAvroUtil.toBase64String(Arrays.asList(minimumHouse,
                maximumHouse));
        jobConf.set("minmax", minmax);

        Job job = Job.getInstance(jobConf);
        Scan scan = new Scan();
        scan.addFamily(Bytes.toBytes("data"));
        TableMapReduceUtil.initTableMapperJob("homes", scan,
                HouseVectorizingMapper.class, LongWritable.class,
                VectorWritable.class, job);
        job.setOutputFormatClass(SequenceFileOutputFormat.class);
        job.setOutputKeyClass(LongWritable.class);
        job.setOutputValueClass(VectorWritable.class);
        job.setMapOutputKeyClass(LongWritable.class);
        job.setMapOutputValueClass(VectorWritable.class);

        SequenceFileOutputFormat.setOutputCompressionType(job, SequenceFile.CompressionType.BLOCK);
        SequenceFileOutputFormat.setOutputCompressorClass(job, SnappyCodec.class);
        SequenceFileOutputFormat.setOutputPath(job, outputDir);
        job.getConfiguration().setClass("mapreduce.map.output.compress.codec", 
                SnappyCodec.class, 
                CompressionCodec.class);

        job.waitForCompletion(true);
    }

当我运行它时，我得到了这个：

When I run it I get this:

java.lang.Exception: java.lang.UnsatisfiedLinkError: org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy()Z
    at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:401)
Caused by: java.lang.UnsatisfiedLinkError: org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy()Z
    at org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy(Native Method)
    at org.apache.hadoop.io.compress.SnappyCodec.checkNativeCodeLoaded(SnappyCodec.java:62)
    at org.apache.hadoop.io.compress.SnappyCodec.getCompressorType(SnappyCodec.java:127)
    at org.apache.hadoop.io.compress.CodecPool.getCompressor(CodecPool.java:104)
    at org.apache.hadoop.io.compress.CodecPool.getCompressor(CodecPool.java:118)
    at org.apache.hadoop.io.SequenceFile$Writer.init(SequenceFile.java:1169)
    at org.apache.hadoop.io.SequenceFile$Writer.<init>(SequenceFile.java:1080)
    at org.apache.hadoop.io.SequenceFile$BlockCompressWriter.<init>(SequenceFile.java:1400)
    at org.apache.hadoop.io.SequenceFile.createWriter(SequenceFile.java:274)
    at org.apache.hadoop.io.SequenceFile.createWriter(SequenceFile.java:527)
    at org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat.getSequenceWriter(SequenceFileOutputFormat.java:64)
    at org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat.getRecordWriter(SequenceFileOutputFormat.java:75)
    at org.apache.hadoop.mapred.MapTask$NewDirectOutputCollector.<init>(MapTask.java:617)
    at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:737)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:338)
    at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:233)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
    at java.util.concurrent.FutureTask.run(FutureTask.java:262)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:744)

如果我注释掉这些行，那么我的测试通过：

If I comment out these lines then my test passes:

SequenceFileOutputFormat.setOutputCompressionType(job, SequenceFile.CompressionType.BLOCK);
        SequenceFileOutputFormat.setOutputCompressorClass(job, SnappyCodec.class);
        job.getConfiguration().setClass("mapreduce.map.output.compress.coded", 
                SnappyCodec.class, 
                CompressionCodec.class);

然而，我真的想在我的序列文件中使用快速压缩。有人可以请我向我解释我做错了什么？

However, I really want to use snappy compression in my sequence files. Can somebody please explain to me what I am doing wrong?

推荐答案

找到 Cloudera社区

1. 确保 LD_LIBRARY_PATH 和 JAVA_LIBRARY_PATH 包含具有 libsnappy .so **文件。
确保已在SPARK环境中导出LD_LIBRARY_PATH和JAVA_LIBRARY路径（ spark-env.sh ） 。

1. Ensure that LD_LIBRARY_PATH and JAVA_LIBRARY_PATH contains the native directory path having the libsnappy.so** files.
2. Ensure that LD_LIBRARY_PATH and JAVA_LIBRARY path have been exported in the SPARK environment(spark-env.sh).

例如，我使用Hortonworks HDP，并在我的 spark-env.sh

For example I use Hortonworks HDP and I have the following configuration in my spark-env.sh

export JAVA_LIBRARY_PATH=$JAVA_LIBRARY_PATH:/usr/hdp/2.2.0.0-2041/hadoop/lib/native
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/hdp/2.2.0.0-2041/hadoop/lib/native
export SPARK_YARN_USER_ENV="JAVA_LIBRARY_PATH=$JAVA_LIBRARY_PATH,LD_LIBRARY_PATH=$LD_LIBRARY_PATH"

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