How to move Word and PDF documents to Hadoop HDFS? - hadoop

I want to copy/upload some files from a local system (a system not in Hadoop cluster) onto Hadoop HDFS. The local system can be Windows system too.
I tried with Flume spool directory. It works fine with Text files. For other docs, the mime type is getting corrupted.
Please let me know different approaches to load a file(s) to HDFS.


hadoop fs -copyFromLocal <localsrc> URI
Check Hadoop documentation: copyFromLocal
Keep in mind, Apache Flume wasn't created to copy some files.


You can also use hadoop fs -put <localsrcpath> <hdfspath>
This is one of the alternative to copyFromLocal


In hadoop 2.0 (YARN) you can do as follows to transfer local files to HDFS:
hdfs dfs -put "localsrcpath" "hdfspath"
where hdfs is the command located in the bin directory.


Java code can do that easily. You don't require any tools for this. Check below, the piece of code that worked:
Configuration conf = new Configuration();
try {
conf.set("fs.defaultFS",<<namenode>>); //something like hdfs://server:9000 or copy from core-site.xml
FileSystem fileSystem= FileSystem.get(conf);
System.out.println("Uploading please wait...");
fileSystem.copyFromLocalFile(false, new Path(args[0]), new Path(args[1].trim()));//args[0]=C://file or dir args[1]=/imported
Prepare jar out of this and run on any OS. Keep in mind you no need to
have Hadoop running in the machine, where you are going to run this
code. If you need any help, add comments.
Don't forget to add dnsresolver line where you run this code. Open /drivers/etc/hosts (for Windows)
hadoopnamenode ip-address
slavenode ip-address


First you need to load docs from your Windows machine to linux machine using filezilla or other tool.
And then you need to use:
hadoop fs -put localsrcpath hdfspath
Following command will also work.
hadoop fs -copyFromLocal localsrcpath hdfspath

Related

Reading a file in Spark in cluster mode in Amazon EC2

I'm trying to execute a spark program in cluster mode in Amazon Ec2 using
spark-submit --master spark://<master-ip>:7077 --deploy-mode cluster --class com.mycompany.SimpleApp ./spark.jar
And the class has a line that tries to read a file:
JavaRDD<String> logData = sc.textFile("/user/input/CHANGES.txt").cache();
I'm unable to read this txt file in cluster mode even if I'm able to read in standalone mode. In cluster mode, it's looking to read from hdfs. So I put the file in hdfs at /root/persistent-hdfs using
hadoop fs -mkdir -p /wordcount/input
hadoop fs -put /app/hadoop/tmp/input.txt /wordcount/input/input.txt
And I can see the file using hadoop fs -ls /workcount/input. But Spark is still unable to read the file. Any idea what I'm doing wrong. Thanks.

You might want to check the following points:
Is the file really in the persistent HDFS?
It seems that you just copy the input file from /app/hadoop/tmp/input.txt to /wordcount/input/input.txt, all in the node disk. I believe you misunderstand the functionality of the hadoop commands.
Instead, you should try putting the file explicitly in the persistent HDFS (root/persistent-hdfs/), and then loading it using the hdfs://... prefix.
Is the persistent HDFS server up?
Please take a look here, it seems Spark only starts the ephemeral HDFS server by default. In order to switch to the persistent HDFS server, you must do the following:
1) Stop the ephemeral HDFS server: /root/ephemeral-hdfs/bin/stop-dfs.sh
2) Start the persistent HDFS server: /root/persistent-hdfs/bin/start-dfs.sh
Please try these things, I hope they can serve you well.

Issues when using hadoop to copy files from grid to local

I am trying to copy some files from the hadoop HDFS to local. I used the following command
hadoop fs -copyToLocal <hdfs path> <local path>
The size of the file is just 80M. I had run a job before where I had no issue in copying files of size 70MB to local. However, this time I am having Input/Output error
copyToLocal: Input/output error
can anyone tell me what could have gone wrong?

It might be a space constraint on your machine. I had the same issue because the file was too big for it to be moved to my local machine. Once I made space, I was able to perform the copyToLocal operation.

Hadoop filesystem reads linux filesystem instead of hdfs?

I have a strange thing happening, when I read hadoop filesystem it shows me linux filesystem not the hadoop one, anyone is familiar with this issue?
Thanks,
Mika

This will happen if a valid hadoop configuration is not found.
e.g. if you do:
hadoop fs -ls
and there is no configuration is found at the default location, then you will see the linux filesystem. You can test this by adding either the -conf option after the "hadoop" command e.g.
hadoop -conf=<path-to-conf-files> fs -ls

Run a Local file system directory as input of a Mapper in cluster

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

Copying directories in HDFS using the JAVA API

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

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