所以，我有这项工作要做：“从位于S3上的图像数据集中，使用弹性地图缩小（EMR）将图像转换为灰度，并将它们全部写入PDF文件”。
从那时起，我一直在寻找方法，我发现Hadoop没有默认的图像文件输入格式。所以我发现了两种方法：
问题：
我尝试了两种方法，但由于两次尝试都出错，我无法得到我想要的东西。
对于第一种方法，我得到了这个：
2016-06-22 11:54:34,894 INFO org.apache.hadoop.yarn.client.RMProxy (main): Connecting to ResourceManager at ip-172-31-2-62.us-west-2.compute.internal/172.31.2.62:8032
2016-06-22 11:54:39,387 INFO org.apache.hadoop.mapreduce.lib.input.FileInputFormat (main): Total input paths to process : 170
2016-06-22 11:54:39,494 INFO com.hadoop.compression.lzo.GPLNativeCodeLoader (main): Loaded native gpl library
2016-06-22 11:54:39,508 INFO com.hadoop.compression.lzo.LzoCodec (main): Successfully loaded & initialized native-lzo library [hadoop-lzo rev 3454067872d644fcdf99dbacccc3e0acfcd41bc0]
2016-06-22 11:54:39,740 INFO org.apache.hadoop.mapreduce.JobSubmitter (main): number of splits:170
2016-06-22 11:54:40,366 INFO org.apache.hadoop.mapreduce.JobSubmitter (main): Submitting tokens for job: job_1466077468134_0004
2016-06-22 11:54:40,767 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl (main): Submitted application application_1466077468134_0004
2016-06-22 11:54:40,970 INFO org.apache.hadoop.mapreduce.Job (main): The url to track the job: http://ip-172-31-2-62.us-west-2.compute.internal:20888/proxy/application_1466077468134_0004/
2016-06-22 11:54:40,971 INFO org.apache.hadoop.mapreduce.Job (main): Running job: job_1466077468134_0004
2016-06-22 11:55:00,456 INFO org.apache.hadoop.mapreduce.Job (main): Job job_1466077468134_0004 running in uber mode : false
2016-06-22 11:55:00,458 INFO org.apache.hadoop.mapreduce.Job (main): map 0% reduce 0%
2016-06-22 11:55:17,726 INFO org.apache.hadoop.mapreduce.Job (main): map 1% reduce 0%
2016-06-22 11:55:17,745 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000000_0, Status : FAILED
2016-06-22 11:55:18,783 INFO org.apache.hadoop.mapreduce.Job (main): map 0% reduce 0%
2016-06-22 11:55:31,906 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000001_0, Status : FAILED
2016-06-22 11:55:31,908 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000002_0, Status : FAILED
2016-06-22 11:55:33,932 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000003_0, Status : FAILED
2016-06-22 11:55:49,079 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000002_1, Status : FAILED
2016-06-22 11:55:59,166 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000000_1, Status : FAILED
2016-06-22 11:56:01,184 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000001_1, Status : FAILED
2016-06-22 11:56:04,209 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000003_1, Status : FAILED
2016-06-22 11:56:19,372 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000001_2, Status : FAILED
2016-06-22 11:56:27,438 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000002_2, Status : FAILED
2016-06-22 11:56:29,457 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000000_2, Status : FAILED
2016-06-22 11:56:34,497 INFO org.apache.hadoop.mapreduce.Job (main): Task Id : attempt_1466077468134_0004_m_000003_2, Status : FAILED
2016-06-22 11:56:49,613 INFO org.apache.hadoop.mapreduce.Job (main): map 2% reduce 0%
2016-06-22 11:56:50,620 INFO org.apache.hadoop.mapreduce.Job (main): map 100% reduce 100%
2016-06-22 11:56:51,644 INFO org.apache.hadoop.mapreduce.Job (main): Job job_1466077468134_0004 failed with state FAILED due to: Task failed task_1466077468134_0004_m_000000
Job failed as tasks failed. failedMaps:1 failedReduces:0
2016-06-22 11:56:51,909 INFO org.apache.hadoop.mapreduce.Job (main): Counters: 17
Job Counters
Failed map tasks=13
Killed map tasks=169
Killed reduce tasks=3
Launched map tasks=15
Other local map tasks=11
Data-local map tasks=4
Total time spent by all maps in occupied slots (ms)=7254456
Total time spent by all reduces in occupied slots (ms)=0
Total time spent by all map tasks (ms)=302269
Total time spent by all reduce tasks (ms)=0
Total vcore-milliseconds taken by all map tasks=302269
Total vcore-milliseconds taken by all reduce tasks=0
Total megabyte-milliseconds taken by all map tasks=232142592
Total megabyte-milliseconds taken by all reduce tasks=0
Map-Reduce Framework
CPU time spent (ms)=0
Physical memory (bytes) snapshot=0
Virtual memory (bytes) snapshot=0
对于第二种方法，我刚刚得到了这个（就像它没有找到路径一样）：
Input image directory: s3://tarefahadoop/input
Input FS: local FS
Output HIB: s3://tarefahadoop/images.hib
Overwrite HIB if it exists: false
对我来说，最好的解决方案是将文件转换为SequenceFile，因为我已经完成了我必须完成的工作的第2部分（打开SequenceFile，转换为图像，将图像转换为灰度（地图）并写入在pdf（减少））。但我感谢任何其他有用的想法。