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From Amandeep Khurana <ama...@gmail.com>
Subject Re: HDFS architecture based on GFS?
Date Mon, 16 Feb 2009 02:00:59 GMT
Assuming that the job is purely in Java and not involving streaming or
pipes, wouldnt the resources (files) required by the job as inputs be known
beforehand? So, if the map task is accessing a second file, how does it make
it different except that there are multiple files. The JobTracker would know
beforehand that multiple files would be accessed. Right?

I am slightly confused why you have mentioned this case separately... Can
you elaborate on it a little bit?

Amandeep


Amandeep Khurana
Computer Science Graduate Student
University of California, Santa Cruz


On Sun, Feb 15, 2009 at 4:47 PM, Matei Zaharia <matei@cloudera.com> wrote:

> Typically the data flow is like this:1) Client submits a job description to
> the JobTracker.
> 2) JobTracker figures out block locations for the input file(s) by talking
> to HDFS NameNode.
> 3) JobTracker creates a job description file in HDFS which will be read by
> the nodes to copy over the job's code etc.
> 4) JobTracker starts map tasks on the slaves (TaskTrackers) with the
> appropriate data blocks.
> 5) After running, maps create intermediate output files on those slaves.
> These are not in HDFS, they're in some temporary storage used by MapReduce.
> 6) JobTracker starts reduces on a series of slaves, which copy over the
> appropriate map outputs, apply the reduce function, and write the outputs
> to
> HDFS (one output file per reducer).
> 7) Some logs for the job may also be put into HDFS by the JobTracker.
>
> However, there is a big caveat, which is that the map and reduce tasks run
> arbitrary code. It is not unusual to have a map that opens a second HDFS
> file to read some information (e.g. for doing a join of a small table
> against a big file). If you use Hadoop Streaming or Pipes to write a job in
> Python, Ruby, C, etc, then you are launching arbitrary processes which may
> also access external resources in this manner. Some people also read/write
> to DBs (e.g. MySQL) from their tasks. A comprehensive security solution
> would ideally deal with these cases too.
>
> On Sun, Feb 15, 2009 at 3:22 PM, Amandeep Khurana <amansk@gmail.com>
> wrote:
>
> > A quick question here. How does a typical hadoop job work at the system
> > level? What are the various interactions and how does the data flow?
> >
> > Amandeep
> >
> >
> > Amandeep Khurana
> > Computer Science Graduate Student
> > University of California, Santa Cruz
> >
> >
> > On Sun, Feb 15, 2009 at 3:20 PM, Amandeep Khurana <amansk@gmail.com>
> > wrote:
> >
> > > Thanks Matei. If the basic architecture is similar to the Google stuff,
> I
> > > can safely just work on the project using the information from the
> > papers.
> > >
> > > I am aware of the 4487 jira and the current status of the permissions
> > > mechanism. I had a look at them earlier.
> > >
> > > Cheers
> > > Amandeep
> > >
> > >
> > > Amandeep Khurana
> > > Computer Science Graduate Student
> > > University of California, Santa Cruz
> > >
> > >
> > > On Sun, Feb 15, 2009 at 2:40 PM, Matei Zaharia <matei@cloudera.com>
> > wrote:
> > >
> > >> Forgot to add, this JIRA details the latest security features that are
> > >> being
> > >> worked on in Hadoop trunk:
> > >> https://issues.apache.org/jira/browse/HADOOP-4487.
> > >> This document describes the current status and limitations of the
> > >> permissions mechanism:
> > >>
> http://hadoop.apache.org/core/docs/current/hdfs_permissions_guide.html.
> > >>
> > >> On Sun, Feb 15, 2009 at 2:35 PM, Matei Zaharia <matei@cloudera.com>
> > >> wrote:
> > >>
> > >> > I think it's safe to assume that Hadoop works like MapReduce/GFS at
> > the
> > >> > level described in those papers. In particular, in HDFS, there is
a
> > >> master
> > >> > node containing metadata and a number of slave nodes (datanodes)
> > >> containing
> > >> > blocks, as in GFS. Clients start by talking to the master to list
> > >> > directories, etc. When they want to read a region of some file, they
> > >> tell
> > >> > the master the filename and offset, and they receive a list of block
> > >> > locations (datanodes). They then contact the individual datanodes
to
> > >> read
> > >> > the blocks. When clients write a file, they first obtain a new block
> > ID
> > >> and
> > >> > list of nodes to write it to from the master, then contact the
> > datanodes
> > >> to
> > >> > write it (actually, the datanodes pipeline the write as in GFS) and
> > >> report
> > >> > when the write is complete. HDFS actually has some security
> mechanisms
> > >> built
> > >> > in, authenticating users based on their Unix ID and providing
> > Unix-like
> > >> file
> > >> > permissions. I don't know much about how these are implemented, but
> > they
> > >> > would be a good place to start looking.
> > >> >
> > >> > On Sun, Feb 15, 2009 at 1:36 PM, Amandeep Khurana <amansk@gmail.com
> > >> >wrote:
> > >> >
> > >> >> Thanks Matie
> > >> >>
> > >> >> I had gone through the architecture document online. I am currently
> > >> >> working
> > >> >> on a project towards Security in Hadoop. I do know how the data
> moves
> > >> >> around
> > >> >> in the GFS but wasnt sure how much of that does HDFS follow and
how
> > >> >> different it is from GFS. Can you throw some light on that?
> > >> >>
> > >> >> Security would also involve the Map Reduce jobs following the
same
> > >> >> protocols. Thats why the question about how does the Hadoop
> framework
> > >> >> integrate with the HDFS, and how different is it from Map Reduce
> and
> > >> GFS.
> > >> >> The GFS and Map Reduce papers give a good information on how those
> > >> systems
> > >> >> are designed but there is nothing that concrete for Hadoop that
I
> > have
> > >> >> been
> > >> >> able to find.
> > >> >>
> > >> >> Amandeep
> > >> >>
> > >> >>
> > >> >> Amandeep Khurana
> > >> >> Computer Science Graduate Student
> > >> >> University of California, Santa Cruz
> > >> >>
> > >> >>
> > >> >> On Sun, Feb 15, 2009 at 12:07 PM, Matei Zaharia <
> matei@cloudera.com>
> > >> >> wrote:
> > >> >>
> > >> >> > Hi Amandeep,
> > >> >> > Hadoop is definitely inspired by MapReduce/GFS and aims to
> provide
> > >> those
> > >> >> > capabilities as an open-source project. HDFS is similar to
GFS
> > (large
> > >> >> > blocks, replication, etc); some notable things missing are
> > read-write
> > >> >> > support in the middle of a file (unlikely to be provided
because
> > few
> > >> >> Hadoop
> > >> >> > applications require it) and multiple appenders (the record
> append
> > >> >> > operation). You can read about HDFS architecture at
> > >> >> > http://hadoop.apache.org/core/docs/current/hdfs_design.html.
The
> > >> >> MapReduce
> > >> >> > part of Hadoop interacts with HDFS in the same way that Google's
> > >> >> MapReduce
> > >> >> > interacts with GFS (shipping computation to the data), although
> > >> Hadoop
> > >> >> > MapReduce also supports running over other distributed
> filesystems.
> > >> >> >
> > >> >> > Matei
> > >> >> >
> > >> >> > On Sun, Feb 15, 2009 at 11:57 AM, Amandeep Khurana <
> > amansk@gmail.com
> > >> >
> > >> >> > wrote:
> > >> >> >
> > >> >> > > Hi
> > >> >> > >
> > >> >> > > Is the HDFS architecture completely based on the Google
> > Filesystem?
> > >> If
> > >> >> it
> > >> >> > > isnt, what are the differences between the two?
> > >> >> > >
> > >> >> > > Secondly, is the coupling between Hadoop and HDFS same
as how
> it
> > is
> > >> >> > between
> > >> >> > > the Google's version of Map Reduce and GFS?
> > >> >> > >
> > >> >> > > Amandeep
> > >> >> > >
> > >> >> > >
> > >> >> > > Amandeep Khurana
> > >> >> > > Computer Science Graduate Student
> > >> >> > > University of California, Santa Cruz
> > >> >> > >
> > >> >> >
> > >> >>
> > >> >
> > >> >
> > >>
> > >
> > >
> >
>

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