Hadoop 工具

功能说明

Hadoop-COS 基于腾讯云 COS 对象存储实现了标准的 Hadoop 文件系统，可以为 Hadoop、Spark 以及 Tez 等大数据计算框架集成 COS 提供支持，使其能够像访问 HDFS 文件系统一样读写存储在 COS 上的数据。

Hadoop-COS 使用 cosn 作为 URI 的 scheme，因此也经常称 Hadoop-COS 为 CosN 文件系统。

使用环境

系统环境

支持 Linux、Windows 和 macOS 系统。

软件依赖

Hadoop-2.6.0及以上版本。

下载与安装

获取 Hadoop-COS 插件

下载地址：Hadoop-COS 插件。

安装 Hadoop-COS 插件

1. 将 dep 目录下的 cos_hadoop_api-5.2.6.jar 和 hadoop-cos-2.X.X.jar 拷贝到 $HADOOP_HOME/share/hadoop/tools/lib下。

说明：

根据 Hadoop 的具体版本选择对应的 jar 包，若 dep 目录中没有提供匹配版本的 jar 包，可自行通过修改 pom 文件中 Hadoop 版本号，重新编译生成。

2. 修改 hadoop_env.sh 文件。
   在$HADOOP_HOME/etc/hadoop目录下，编辑 hadoop_env.sh，增加以下内容，将 cosn 相关 jar 包加入 Hadoop 环境变量：

for f in $HADOOP_HOME/share/hadoop/tools/lib/*.jar; do
  if [ "$HADOOP_CLASSPATH" ]; then
    export HADOOP_CLASSPATH=$HADOOP_CLASSPATH:$f
  else
    export HADOOP_CLASSPATH=$f
  fi
done

使用方法

配置项说明

Hadoop 配置

修改$HADOOP_HOME/etc/hadoop/core-site.xml，增加 COS 相关用户和实现类信息，例如：

<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>cosn://examplebucket-1250000000</value>
    </property>

    <property>
        <name>fs.cosn.credentials.provider</name>
        <value>org.apache.hadoop.fs.auth.SimpleCredentialProvider</value>
        <description>

            This option allows the user to specify how to get the credentials.
            Comma-separated class names of credential provider classes which implement
            com.qcloud.cos.auth.COSCredentialsProvider:

            1.org.apache.hadoop.fs.auth.SessionCredentialProvider: Obtain the secret id and secret key from the URI: cosn://secretId:secretKey@examplebucket-1250000000/;
            2.org.apache.hadoop.fs.auth.SimpleCredentialProvider: Obtain the secret id and secret key
            from fs.cosn.userinfo.secretId and fs.cosn.userinfo.secretKey in core-site.xml;
            3.org.apache.hadoop.fs.auth.EnvironmentVariableCredentialProvider: Obtain the secret id and secret key
            from system environment variables named COS_SECRET_ID and COS_SECRET_KEY.

            If unspecified, the default order of credential providers is:
            1. org.apache.hadoop.fs.auth.SessionCredentialProvider
            2. org.apache.hadoop.fs.auth.SimpleCredentialProvider
            3. org.apache.hadoop.fs.auth.EnvironmentVariableCredentialProvider

        </description>
    </property>

    <property>
        <name>fs.cosn.userinfo.secretId</name>
        <value>xxxxxxxxxxxxxxxxxxxxxxxxx</value>
        <description>Tencent Cloud Secret Id</description>
    </property>

    <property>
        <name>fs.cosn.userinfo.secretKey</name>
        <value>xxxxxxxxxxxxxxxxxxxxxxxx</value>
        <description>Tencent Cloud Secret Key</description>
    </property>

    <property>
        <name>fs.cosn.bucket.region</name>
        <value>ap-xxx</value>
        <description>The region where the bucket is located.</description>
    </property>

    <property>
        <name>fs.cosn.bucket.endpoint_suffix</name>
        <value>cos.ap-xxx.myqcloud.com</value>
        <description>
          COS endpoint to connect to. 
          For public cloud users, it is recommended not to set this option, and only the correct area field is required.
        </description>
    </property>

    <property>
        <name>fs.cosn.impl</name>
        <value>org.apache.hadoop.fs.CosFileSystem</value>
        <description>The implementation class of the CosN Filesystem.</description>
    </property>

    <property>
        <name>fs.AbstractFileSystem.cosn.impl</name>
        <value>org.apache.hadoop.fs.CosN</value>
        <description>The implementation class of the CosN AbstractFileSystem.</description>
    </property>

    <property>
        <name>fs.cosn.tmp.dir</name>
        <value>/tmp/hadoop_cos</value>
        <description>Temporary files will be placed here.</description>
    </property>

    <property>
      <name>fs.cosn.upload.buffr</name>
      <value>mapped_disk</value>
      <description>The type of upload buffer. Available values: non_direct_memory, direct_memory, mapped_disk.</description>
    </property>

    <property>
        <name>fs.cosn.upload.buffer.size</name>
        <value>33554432</value>
        <description>The total size of the buffer pool.</description>
    </property>

    <property>
        <name>fs.cosn.block.size</name>
        <value>8388608</value>
        <description>Block size to use cosn filesysten, which is the part size for MultipartUpload.
        Considering the COS supports up to 10000 blocks, user should estimate the maximum size of a single file.
        For example, 8MB part size can allow  writing a 78GB single file.</description>
    </property>

    <property>
        <name>fs.cosn.maxRetries</name>
      <value>3</value>
      <description>
        The maximum number of retries for reading or writing files to
        COS, before we signal failure to the application.
      </description>
    </property>

    <property>
        <name>fs.cosn.retry.interval.seconds</name>
      <value>3</value>
      <description>The number of seconds to sleep between each COS retry.</description>
    </property>

</configuration>

使用示例

命令格式为：hadoop fs -ls -R cosn://<BucketName-APPID>/<路径>或hadoop fs -ls -R /<路径>（需要配置fs.defaultFS选项为cosn://BucketName-APPID），下例中以名称为 examplebucket-1250000000 的 bucket 为例，可在其后面加上具体路径。

hadoop fs -ls -R cosn://examplebucket-1250000000/
-rw-rw-rw-   1 root root       1087 2018-06-11 07:49 cosn://examplebucket-1250000000/LICENSE
drwxrwxrwx   - root root          0 1970-01-01 00:00 cosn://examplebucket-1250000000/hdfs
drwxrwxrwx   - root root          0 1970-01-01 00:00 cosn://examplebucket-1250000000/hdfs/2018
-rw-rw-rw-   1 root root       1087 2018-06-12 03:26 cosn://examplebucket-1250000000/hdfs/2018/LICENSE
-rw-rw-rw-   1 root root       2386 2018-06-12 03:26 cosn://examplebucket-1250000000/hdfs/2018/ReadMe
drwxrwxrwx   - root root          0 1970-01-01 00:00 cosn://examplebucket-1250000000/hdfs/test
-rw-rw-rw-   1 root root       1087 2018-06-11 07:32 cosn://examplebucket-1250000000/hdfs/test/LICENSE
-rw-rw-rw-   1 root root       2386 2018-06-11 07:29 cosn://examplebucket-1250000000/hdfs/test/ReadMe

运行 MapReduce 自带的 wordcount，执行以下命令。

注意：

以下命令中 hadoop-mapreduce-examples-2.7.2.jar 是以2.7.2版本为例，若版本不同，请修改成对应的版本号。

bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.2.jar wordcount cosn://example/mr/input cosn://example/mr/output3

执行成功会返回统计信息，示例如下：

File System Counters
COSN: Number of bytes read=72
COSN: Number of bytes written=40
COSN: Number of read operations=0
COSN: Number of large read operations=0
COSN: Number of write operations=0
FILE: Number of bytes read=547350
FILE: Number of bytes written=1155616
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=0
HDFS: Number of bytes written=0
HDFS: Number of read operations=0
HDFS: Number of large read operations=0
HDFS: Number of write operations=0
Map-Reduce Framework
Map input records=5
Map output records=7
Map output bytes=59
Map output materialized bytes=70
Input split bytes=99
Combine input records=7
Combine output records=6
Reduce input groups=6
Reduce shuffle bytes=70
Reduce input records=6
Reduce output records=6
Spilled Records=12
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=0
Total committed heap usage (bytes)=653262848
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=36
File Output Format Counters
Bytes Written=40