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Difference between revisions of "Running Hadoop with Lustre"

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* Lustre is a real parallel file system, which enables temporary or intermediate data to be stored parallel in multinode, alleviating the load of a single node.  
 
* Lustre is a real parallel file system, which enables temporary or intermediate data to be stored parallel in multinode, alleviating the load of a single node.  
  
* Lustre has its own network protocol, which is better for bulk data transfer compared to the HTTP protocol. Additionally, as a real shared file system, each client sees the same file system image, so [[hardlink]] '''hardlinks?''' can be used to avoid data transfer between nodes.
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* Lustre has its own network protocol, which is better for bulk data transfer compared to the HTTP protocol. Additionally, as a real shared file system, each client sees the same file system image, so [[hardlink]] '''[[hardlinks?]]''' can be used to avoid data transfer between nodes.
  
* Lustre is more '''easily?''' extended and can be mounted as a normal POSIX file system.
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* Lustre is more '''[[easily?]]''' extended and can be mounted as a normal POSIX file system.
  
 
== Disadvantages of Using Hadoop with HDFS ==
 
== Disadvantages of Using Hadoop with HDFS ==
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* Hadoop sometimes generates a large amount of temporary or intermediate data during the Map/Reduce process. HDFS stores these files on the local disk, which results in a considerable load on the OS/disk.
 
* Hadoop sometimes generates a large amount of temporary or intermediate data during the Map/Reduce process. HDFS stores these files on the local disk, which results in a considerable load on the OS/disk.
  
* During the Map/Reduce process, the Reduce node uses the HTTP protocol to retrieve Map results from the Map node protocol. The HTTP protocol is not a good choice for big data transfers '''because?...'''
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* During the Map/Reduce process, the Reduce node uses the HTTP protocol to retrieve Map results from the Map node protocol. The HTTP protocol is not a good choice for big data transfers '''[[because?...]]'''
  
 
* Hadoop is designed for Map/Reduce jobs, which makes it difficult to extend '''Hadoop?''' as a normal file system.
 
* Hadoop is designed for Map/Reduce jobs, which makes it difficult to extend '''Hadoop?''' as a normal file system.

Revision as of 12:47, 5 August 2009

This page describes how Hadoop performs with the Lustre file system when the Hadoop Distributed File System (HDFS) is replaced by Lustre.

Advantages of Using Hadoop with Lustre

Using Hadoop with Lustre offers several advantages over HDFS. We have made several enhancements to improve the use of Hadoop with Lustre. Advantages include:

  • Lustre is a real parallel file system, which enables temporary or intermediate data to be stored parallel in multinode, alleviating the load of a single node.
  • Lustre has its own network protocol, which is better for bulk data transfer compared to the HTTP protocol. Additionally, as a real shared file system, each client sees the same file system image, so hardlink hardlinks? can be used to avoid data transfer between nodes.
  • Lustre is more easily? extended and can be mounted as a normal POSIX file system.

Disadvantages of Using Hadoop with HDFS

  • Hadoop sometimes generates a large amount of temporary or intermediate data during the Map/Reduce process. HDFS stores these files on the local disk, which results in a considerable load on the OS/disk.
  • During the Map/Reduce process, the Reduce node uses the HTTP protocol to retrieve Map results from the Map node protocol. The HTTP protocol is not a good choice for big data transfers because?...
  • Hadoop is designed for Map/Reduce jobs, which makes it difficult to extend Hadoop? as a normal file system.
  • Using Hadoop is time-consuming for small files.

Test Comparisons Between Lustre vs HDFS

This paper provides suggestions about how to set up Lustre with Hadoop and how to use stripe information to help Hadoop schedule the job.

Using Lustre with Hadoop