I get
Exception in thread "main" java.lang.IllegalArgumentException: Wrong FS: file:/path/to/my.jar, expected: hdfs://ec2-xx-xx-xx-xxx.compute-1.amazonaws.com
if I try to add a local file to distributed cache in hadoop. When the file is on HDFS, I don't get this error (obviously, since it's using the expected FS). Is there a way to use a local file in distributed cache without first copying it to hdfs? Here is a code snippet:
Configuration conf = job.getConfiguration();
FileSystem fs = FileSystem.getLocal(conf);
Path dependency = fs.makeQualified(new Path("/local/path/to/my.jar");
DistributedCache.addArchiveToClassPath(path, conf);
Thanks
It has to be in HDFS first. I'm going to go out on a limb here, but I think it is because the file is "pulled" to the local distributed cache by the slaves, not pushed. Since they are pulled, they have no way to access that local path.
No, I don't think you can put anything on the distributed cache without it being in HDFS first. All Hadoop jobs use input/output path in relation to HDFS.
File can be either in local system, hdfs, S3 or other cluster also. You need to specify as
-files hdfs:// if the file is in hdfs
by default it assumes local file system.
Related
I want to using Spark Streaming to retrieve data from Kafka. Now, I want to save my data in a remote HDFS. I know that I have to use the function saveAsText. However, I don't know precisely how to specify the path.
Is that correct if I write this:
myDStream.foreachRDD(frm->{
frm.saveAsTextFile("hdfs://ip_addr:9000//home/hadoop/datanode/myNewFolder");
});
where ip_addr is the ip address of my hdfs remote server.
/home/hadoop/datanode/ is the DataNode HDFS directory created when I installed hadoop (I don't know if I have to specify this directory). And,
myNewFolder is the folder where I want to save my data.
Thanks in advance.
Yassir
The path has to be a directory in HDFS.
For example, if you want to save the files inside a folder named myNewFolder under the root / path in HDFS.
The path to use would be hdfs://namenode_ip:port/myNewFolder/
On execution of the spark job this directory myNewFolder will be created.
The datanode data directory which is given for the dfs.datanode.data.dir in hdfs-site.xml is used to store the blocks of the files you store in HDFS, should not be referenced as HDFS directory path.
I have installed both hadoop and spark locally on a windows machine.
I can access HDFS files in hadoop, e.g.,
hdfs dfs -tail hdfs:/out/part-r-00000
works as expected. However, if I try to access the same file from the spark shell, e.g.,
val f = sc.textFile("hdfs:/out/part-r-00000")
I get an error that the file does not exist. Spark can access files in the windows file system using the file:/... syntax, though.
I have set the HADOOP_HOME environment variable to c:\hadoop which is the folder containing the hadoop install (in particular winutils.exe, which seems to be necessary for spark, is in c:\hadoop\bin).
Because it seems that HDFS data is stored in the c:\tmp folder, I was wondering whether there is would be a way to let spark know about this location.
Any help would be greatly appreciated. Thank you.
If you are getting file doesn't exist, that means your spark application(code snippet) is able to connect to HDFS.
The HDFS file path that you are using seems wrong.
This should solve your issue
val f = sc.textFile("hdfs://localhost:8020/out/part-r-00000")
My hadoop cluster is using HDFS as default fs. But on client side, the input file is located on local file system. (for some reason, I don't want to move that into HDFS). If I give mapreduce job a Uri like 'file:///opt/myDoc.txt', I've got a file not exists error. How can I get access to local file system in this case?
This is the place where you give the details of input path
FileInputFormat.setInputPaths(conf, new Path(args[0]));
Instead of args[0], give local path.
possible duplicate
I gave an input to the mapper from a local filesystem.It is running successfully from eclipse,But not running from the cluster as it is unable to find the local input path saying:input path does not exist.Please can anybody help me how to give a local file path to a mapper so that it can run in the cluster and i can get the output in hdfs
This is a very old question. Recently faced the same issue.
I am not aware of how correct this solution is it worked for me though. Please bring to notice if there are any drawbacks of this.Here's what I did.
Reading a solution from the mail-archives, I realised if i modify fs.default.name from hdfs://localhost:8020/ to file:/// it can access the local file system. However, I didnt want this for all my mapreduce jobs. So I made a copy of core-site.xml in a local system folder (same as the one from where I would submit my MR jar to hadoop jar).
and in my Driver class for MR I added,
Configuration conf = new Configuration();
conf.addResource(new Path("/my/local/system/path/to/core-site.xml"));
conf.addResource(new Path("/usr/lib/hadoop-0.20-mapreduce/conf/hdfs-site.xml"));
The MR takes input from local system and writes the output to hdfs:
Running in a cluster requires the data to be loaded into distributed storage (HDFS). Copy the data to HDFS first using hadoop fs -copyFromLocal and then try to trun your job again, giving it the path of the data in HDFS
The question is an interesting one. One can have data on S3 and access this data without an explicit copy to HDFS prior to running the job. In the wordcount example, one would specify this as follows:
hadoop jar example.jar wordcount s3n://bucket/input s3n://bucket/output
What occurs in this is that the mappers read records directly from S3.
If this can be done with S3, why wouldn't hadoop similarly, using this syntax instead of s3n
file:///input file:///output
?
But empirically, this seems to fail in an interesting way -- I see that Hadoop gives a file not found exception for a file that is indeed in the input directory. That is, it seems to be able to list the files in the put directory on my local disk but when it comes time to open them to read the records, the file is not found (or accessible).
The data must be on HDFS for any MapReduce job to process it. So even if you have a source such as local File System or a network path or a web based store (such as Azure Blob Storage or Amazon Block stoage), you would need to copy the data at HDFS first and then run the Job.
The bottom line is that you would need to push the data first to to HDFS and there are several ways depend on data source, you would perform the data transfer from your source to HDFS such as from local file system you would use the following command:
$hadoop -f CopyFromLocal SourceFileOrStoragePath _HDFS__Or_directPathatHDFS_
Try setting the input path like this
FileInputFormat.addInputPath(conf, new Path(file:///the directory on your local filesystem));
if you give the file extension, it can access files from the localsystem
I have tried the following code and got the solution...
Please try it and let me know..
You need to get FileSystem object for local file system and then use makequalified method to return path.. As we need to pass path of local filesystem(no other way to pass this to inputformat), i ve used make qualified, which in deed returns only local file system path..
The code is shown below..
Configuration conf = new Configuration();
FileSystem fs = FileSystem.getLocal(conf);
Path inputPath = fs.makeQualified(new Path("/usr/local/srini/")); // local path
FileInputFormat.setInputPaths(job, inputPath);
I hope this works for your requirement, though it's posted very late.. It worked fine for me.. It does not need any configuration changes i believe..
U might wanna try this by setting the configuration as
Configuration conf=new Configuration();
conf.set("job.mapreduce.tracker","local");
conf.set("fs.default.name","file:///");
After this u can set the fileinputformat with the local path and u r good to go
How do I copy a directory in HDFS to another directory in HDFS?
I found the copyFromLocalFile functions that copy from the local FS to HDFS, but I want both of the source/destination to be in HDFS.
Thanks
Use distcp command.
The canonical use case for distcp is for transferring data between two HDFS clusters.
If the clusters are running identical versions of Hadoop, the hdfs scheme is
appropriate:
% hadoop distcp hdfs://namenode1/foo hdfs://namenode2/bar
If you want to do it through Java code, see class org.apache.hadoop.tools.DistCp and call it appropriately.
You can try FileUtil.copy
http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/fs/FileUtil.html