Hi guys,

I want to confirm when on each task node either mapper or reducer access
distributed cache file, it resides on disk, not resides in memory. Just
want to make sure distributed cache file does not fully loaded into memory
which compete memory consumption with mapper/reducer tasks. Is that correct?

thanks in advance,
Lin

Hi,

Am 22.12.2012 um 13:03 schrieb Lin Ma <[EMAIL PROTECTED]>:

> I want to confirm when on each task node either mapper or reducer access distributed cache file, it resides on disk, not resides in memory. Just want to make sure distributed cache file does not fully loaded into memory which compete memory consumption with mapper/reducer tasks. Is that correct?
Yes, you are correct. The JobTracker will put files for the distributed cache into HDFS with a higher replication count (10 by default). Whenever a TaskTracker needs those files for a task it is launching locally, it will fetch a copy to its local disk. So it won't need to do this again for future tasks on this node. After a job is done, all local copies and the HDFS copies of files in the distributed cache are cleaned up.

Kai

--
Kai Voigt
[EMAIL PROTECTED]

Thanks Kai, using higher replication count for the purpose of?

regards,
Lin

On Sat, Dec 22, 2012 at 8:44 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:

> Hi,
>
> Am 22.12.2012 um 13:03 schrieb Lin Ma <[EMAIL PROTECTED]>:
>
> > I want to confirm when on each task node either mapper or reducer access
> distributed cache file, it resides on disk, not resides in memory. Just
> want to make sure distributed cache file does not fully loaded into memory
> which compete memory consumption with mapper/reducer tasks. Is that correct?
>
>
> Yes, you are correct. The JobTracker will put files for the distributed
> cache into HDFS with a higher replication count (10 by default). Whenever a
> TaskTracker needs those files for a task it is launching locally, it will
> fetch a copy to its local disk. So it won't need to do this again for
> future tasks on this node. After a job is done, all local copies and the
> HDFS copies of files in the distributed cache are cleaned up.
>
> Kai
>
> --
> Kai Voigt
> [EMAIL PROTECTED]
>
>
>
>
>

Hi,

simple math. Assuming you have n TaskTrackers in your cluster that will need to access the files in the distributed cache. And r is the replication level of those files.

Copying the files into HDFS requires r copy operations over the network. The n TaskTrackers need to get their local copies from HDFS, so the n TaskTrackers copy from r DataNodes, so n/r concurrent operation. In total, r+n/r concurrent operations. If you optimize r depending on n, SRQT(n) is the optimal replication level. So 10 is a reasonable default setting for most clusters that are not 500+ nodes big.

Kai

Am 22.12.2012 um 13:46 schrieb Lin Ma <[EMAIL PROTECTED]>:

> Thanks Kai, using higher replication count for the purpose of?
>
> regards,
> Lin
>
> On Sat, Dec 22, 2012 at 8:44 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
> Hi,
>
> Am 22.12.2012 um 13:03 schrieb Lin Ma <[EMAIL PROTECTED]>:
>
> > I want to confirm when on each task node either mapper or reducer access distributed cache file, it resides on disk, not resides in memory. Just want to make sure distributed cache file does not fully loaded into memory which compete memory consumption with mapper/reducer tasks. Is that correct?
>
>
> Yes, you are correct. The JobTracker will put files for the distributed cache into HDFS with a higher replication count (10 by default). Whenever a TaskTracker needs those files for a task it is launching locally, it will fetch a copy to its local disk. So it won't need to do this again for future tasks on this node. After a job is done, all local copies and the HDFS copies of files in the distributed cache are cleaned up.
>
> Kai
>
> --
> Kai Voigt
> [EMAIL PROTECTED]
>
>
>
>
>

--
Kai Voigt
[EMAIL PROTECTED]

Hi Kai,

Smart answer! :-)

   - The assumption you have is one distributed cache replica could only
   serve one download session for tasktracker node (this is why you get
   concurrency n/r). The question is, why one distributed cache replica cannot
   serve multiple concurrent download session? For example, supposing a
   tasktracker use elapsed time t to download a file from a specific
   distributed cache replica, it is possible for 2 tasktrackers to download
   from the specific distributed cache replica in parallel using elapsed time
   t as well, or 1.5 t, which is faster than sequential download time 2t you
   mentioned before?
   - "In total, r+n/r concurrent operations. If you optimize r depending on
   n, SRQT(n) is the optimal replication level." -- how do you get SRQT(n) for
   minimize r+n/r? Appreciate if you could point me to more details.

regards,
Lin

On Sat, Dec 22, 2012 at 8:51 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:

> Hi,
>
> simple math. Assuming you have n TaskTrackers in your cluster that will
> need to access the files in the distributed cache. And r is the replication
> level of those files.
>
> Copying the files into HDFS requires r copy operations over the network.
> The n TaskTrackers need to get their local copies from HDFS, so the n
> TaskTrackers copy from r DataNodes, so n/r concurrent operation. In total,
> r+n/r concurrent operations. If you optimize r depending on n, SRQT(n) is
> the optimal replication level. So 10 is a reasonable default setting for
> most clusters that are not 500+ nodes big.
>
> Kai
>
> Am 22.12.2012 um 13:46 schrieb Lin Ma <[EMAIL PROTECTED]>:
>
> Thanks Kai, using higher replication count for the purpose of?
>
> regards,
> Lin
>
> On Sat, Dec 22, 2012 at 8:44 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
>
>> Hi,
>>
>> Am 22.12.2012 um 13:03 schrieb Lin Ma <[EMAIL PROTECTED]>:
>>
>> > I want to confirm when on each task node either mapper or reducer
>> access distributed cache file, it resides on disk, not resides in memory.
>> Just want to make sure distributed cache file does not fully loaded into
>> memory which compete memory consumption with mapper/reducer tasks. Is that
>> correct?
>>
>>
>> Yes, you are correct. The JobTracker will put files for the distributed
>> cache into HDFS with a higher replication count (10 by default). Whenever a
>> TaskTracker needs those files for a task it is launching locally, it will
>> fetch a copy to its local disk. So it won't need to do this again for
>> future tasks on this node. After a job is done, all local copies and the
>> HDFS copies of files in the distributed cache are cleaned up.
>>
>> Kai
>>
>> --
>> Kai Voigt
>> [EMAIL PROTECTED]
>>
>>
>>
>>
>>
>
> --
> Kai Voigt
> [EMAIL PROTECTED]
>
>
>
>
>

Hi Lin,

DistributedCache files are stored onto the HDFS by the client first.
The TaskTrackers download and localize it. Therefore, as with any
other file on HDFS, "downloads" can be efficiently parallel with
higher replicas.

The point of having higher replication for these files is also tied to
the concept of racks in a cluster - you would want more replicas
spread across racks such that on task bootup the downloads happen with
rack locality.

On Sat, Dec 22, 2012 at 6:54 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
> Hi Kai,
>
> Smart answer! :-)
>
> The assumption you have is one distributed cache replica could only serve
> one download session for tasktracker node (this is why you get concurrency
> n/r). The question is, why one distributed cache replica cannot serve
> multiple concurrent download session? For example, supposing a tasktracker
> use elapsed time t to download a file from a specific distributed cache
> replica, it is possible for 2 tasktrackers to download from the specific
> distributed cache replica in parallel using elapsed time t as well, or 1.5
> t, which is faster than sequential download time 2t you mentioned before?
> "In total, r+n/r concurrent operations. If you optimize r depending on n,
> SRQT(n) is the optimal replication level." -- how do you get SRQT(n) for
> minimize r+n/r? Appreciate if you could point me to more details.
>
> regards,
> Lin
>
>
> On Sat, Dec 22, 2012 at 8:51 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
>>
>> Hi,
>>
>> simple math. Assuming you have n TaskTrackers in your cluster that will
>> need to access the files in the distributed cache. And r is the replication
>> level of those files.
>>
>> Copying the files into HDFS requires r copy operations over the network.
>> The n TaskTrackers need to get their local copies from HDFS, so the n
>> TaskTrackers copy from r DataNodes, so n/r concurrent operation. In total,
>> r+n/r concurrent operations. If you optimize r depending on n, SRQT(n) is
>> the optimal replication level. So 10 is a reasonable default setting for
>> most clusters that are not 500+ nodes big.
>>
>> Kai
>>
>> Am 22.12.2012 um 13:46 schrieb Lin Ma <[EMAIL PROTECTED]>:
>>
>> Thanks Kai, using higher replication count for the purpose of?
>>
>> regards,
>> Lin
>>
>> On Sat, Dec 22, 2012 at 8:44 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
>>>
>>> Hi,
>>>
>>> Am 22.12.2012 um 13:03 schrieb Lin Ma <[EMAIL PROTECTED]>:
>>>
>>> > I want to confirm when on each task node either mapper or reducer
>>> > access distributed cache file, it resides on disk, not resides in memory.
>>> > Just want to make sure distributed cache file does not fully loaded into
>>> > memory which compete memory consumption with mapper/reducer tasks. Is that
>>> > correct?
>>>
>>>
>>> Yes, you are correct. The JobTracker will put files for the distributed
>>> cache into HDFS with a higher replication count (10 by default). Whenever a
>>> TaskTracker needs those files for a task it is launching locally, it will
>>> fetch a copy to its local disk. So it won't need to do this again for future
>>> tasks on this node. After a job is done, all local copies and the HDFS
>>> copies of files in the distributed cache are cleaned up.
>>>
>>> Kai
>>>
>>> --
>>> Kai Voigt
>>> [EMAIL PROTECTED]
>>>
>>>
>>>
>>>
>>
>>
>> --
>> Kai Voigt
>> [EMAIL PROTECTED]
>>
>>
>>
>>
>

--
Harsh J

There is no limitation in HDFS that limits reads of a block to a
single client at a time (no reason to do so) - so downloads can be as
concurrent as possible.

On Wed, Dec 26, 2012 at 3:41 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
> Thanks Harsh,
>
> Supposing DistributedCache is uploaded by client, for each replica, in
> Hadoop design, it could only serve one download session (download from a
> mapper or a reducer which requires the DistributedCache) at a time until
> DistributedCache file download is completed, or it could serve multiple
> concurrent parallel download session (download from multiple mappers or
> reducers which requires the DistributedCache).
>
> regards,
> Lin
>
>
> On Wed, Dec 26, 2012 at 4:51 PM, Harsh J <[EMAIL PROTECTED]> wrote:
>>
>> Hi Lin,
>>
>> DistributedCache files are stored onto the HDFS by the client first.
>> The TaskTrackers download and localize it. Therefore, as with any
>> other file on HDFS, "downloads" can be efficiently parallel with
>> higher replicas.
>>
>> The point of having higher replication for these files is also tied to
>> the concept of racks in a cluster - you would want more replicas
>> spread across racks such that on task bootup the downloads happen with
>> rack locality.
>>
>> On Sat, Dec 22, 2012 at 6:54 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
>> > Hi Kai,
>> >
>> > Smart answer! :-)
>> >
>> > The assumption you have is one distributed cache replica could only
>> > serve
>> > one download session for tasktracker node (this is why you get
>> > concurrency
>> > n/r). The question is, why one distributed cache replica cannot serve
>> > multiple concurrent download session? For example, supposing a
>> > tasktracker
>> > use elapsed time t to download a file from a specific distributed cache
>> > replica, it is possible for 2 tasktrackers to download from the specific
>> > distributed cache replica in parallel using elapsed time t as well, or
>> > 1.5
>> > t, which is faster than sequential download time 2t you mentioned
>> > before?
>> > "In total, r+n/r concurrent operations. If you optimize r depending on
>> > n,
>> > SRQT(n) is the optimal replication level." -- how do you get SRQT(n) for
>> > minimize r+n/r? Appreciate if you could point me to more details.
>> >
>> > regards,
>> > Lin
>> >
>> >
>> > On Sat, Dec 22, 2012 at 8:51 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
>> >>
>> >> Hi,
>> >>
>> >> simple math. Assuming you have n TaskTrackers in your cluster that will
>> >> need to access the files in the distributed cache. And r is the
>> >> replication
>> >> level of those files.
>> >>
>> >> Copying the files into HDFS requires r copy operations over the
>> >> network.
>> >> The n TaskTrackers need to get their local copies from HDFS, so the n
>> >> TaskTrackers copy from r DataNodes, so n/r concurrent operation. In
>> >> total,
>> >> r+n/r concurrent operations. If you optimize r depending on n, SRQT(n)
>> >> is
>> >> the optimal replication level. So 10 is a reasonable default setting
>> >> for
>> >> most clusters that are not 500+ nodes big.
>> >>
>> >> Kai
>> >>
>> >> Am 22.12.2012 um 13:46 schrieb Lin Ma <[EMAIL PROTECTED]>:
>> >>
>> >> Thanks Kai, using higher replication count for the purpose of?
>> >>
>> >> regards,
>> >> Lin
>> >>
>> >> On Sat, Dec 22, 2012 at 8:44 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
>> >>>
>> >>> Hi,
>> >>>
>> >>> Am 22.12.2012 um 13:03 schrieb Lin Ma <[EMAIL PROTECTED]>:
>> >>>
>> >>> > I want to confirm when on each task node either mapper or reducer
>> >>> > access distributed cache file, it resides on disk, not resides in
>> >>> > memory.
>> >>> > Just want to make sure distributed cache file does not fully loaded
>> >>> > into
>> >>> > memory which compete memory consumption with mapper/reducer tasks.
>> >>> > Is that
>> >>> > correct?
>> >>>
>> >>>
>> >>> Yes, you are correct. The JobTracker will put files for the
>> >>> distributed
>> >>> cache into HDFS with a higher replication count (10 by default).
>> >>> Whenever a
>> >>> TaskTracker needs those files for a task it is launching locally, it

Harsh J

Thanks Harsh, multiple concurrent read is generally faster or?

regards,
Lin

On Wed, Dec 26, 2012 at 6:21 PM, Harsh J <[EMAIL PROTECTED]> wrote:

> There is no limitation in HDFS that limits reads of a block to a
> single client at a time (no reason to do so) - so downloads can be as
> concurrent as possible.
>
> On Wed, Dec 26, 2012 at 3:41 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
> > Thanks Harsh,
> >
> > Supposing DistributedCache is uploaded by client, for each replica, in
> > Hadoop design, it could only serve one download session (download from a
> > mapper or a reducer which requires the DistributedCache) at a time until
> > DistributedCache file download is completed, or it could serve multiple
> > concurrent parallel download session (download from multiple mappers or
> > reducers which requires the DistributedCache).
> >
> > regards,
> > Lin
> >
> >
> > On Wed, Dec 26, 2012 at 4:51 PM, Harsh J <[EMAIL PROTECTED]> wrote:
> >>
> >> Hi Lin,
> >>
> >> DistributedCache files are stored onto the HDFS by the client first.
> >> The TaskTrackers download and localize it. Therefore, as with any
> >> other file on HDFS, "downloads" can be efficiently parallel with
> >> higher replicas.
> >>
> >> The point of having higher replication for these files is also tied to
> >> the concept of racks in a cluster - you would want more replicas
> >> spread across racks such that on task bootup the downloads happen with
> >> rack locality.
> >>
> >> On Sat, Dec 22, 2012 at 6:54 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
> >> > Hi Kai,
> >> >
> >> > Smart answer! :-)
> >> >
> >> > The assumption you have is one distributed cache replica could only
> >> > serve
> >> > one download session for tasktracker node (this is why you get
> >> > concurrency
> >> > n/r). The question is, why one distributed cache replica cannot serve
> >> > multiple concurrent download session? For example, supposing a
> >> > tasktracker
> >> > use elapsed time t to download a file from a specific distributed
> cache
> >> > replica, it is possible for 2 tasktrackers to download from the
> specific
> >> > distributed cache replica in parallel using elapsed time t as well, or
> >> > 1.5
> >> > t, which is faster than sequential download time 2t you mentioned
> >> > before?
> >> > "In total, r+n/r concurrent operations. If you optimize r depending on
> >> > n,
> >> > SRQT(n) is the optimal replication level." -- how do you get SRQT(n)
> for
> >> > minimize r+n/r? Appreciate if you could point me to more details.
> >> >
> >> > regards,
> >> > Lin
> >> >
> >> >
> >> > On Sat, Dec 22, 2012 at 8:51 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
> >> >>
> >> >> Hi,
> >> >>
> >> >> simple math. Assuming you have n TaskTrackers in your cluster that
> will
> >> >> need to access the files in the distributed cache. And r is the
> >> >> replication
> >> >> level of those files.
> >> >>
> >> >> Copying the files into HDFS requires r copy operations over the
> >> >> network.
> >> >> The n TaskTrackers need to get their local copies from HDFS, so the n
> >> >> TaskTrackers copy from r DataNodes, so n/r concurrent operation. In
> >> >> total,
> >> >> r+n/r concurrent operations. If you optimize r depending on n,
> SRQT(n)
> >> >> is
> >> >> the optimal replication level. So 10 is a reasonable default setting
> >> >> for
> >> >> most clusters that are not 500+ nodes big.
> >> >>
> >> >> Kai
> >> >>
> >> >> Am 22.12.2012 um 13:46 schrieb Lin Ma <[EMAIL PROTECTED]>:
> >> >>
> >> >> Thanks Kai, using higher replication count for the purpose of?
> >> >>
> >> >> regards,
> >> >> Lin
> >> >>
> >> >> On Sat, Dec 22, 2012 at 8:44 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
> >> >>>
> >> >>> Hi,
> >> >>>
> >> >>> Am 22.12.2012 um 13:03 schrieb Lin Ma <[EMAIL PROTECTED]>:
> >> >>>
> >> >>> > I want to confirm when on each task node either mapper or reducer
> >> >>> > access distributed cache file, it resides on disk, not resides in
> >> >>> > memory.
> >> >>> > Just want to make sure distributed cache file does not fully
> loaded

Hi Lin,

It is comparable (and is also logically similar) to reading a file
multiple times in parallel in a local filesystem - not too much of a
performance hit for small reads (by virtue of OS caches, and quick
completion per read, as is usually the case for distributed cache
files), and gradually decreasing performance for long reads (due to
frequent disk physical movement)? Thankfully, due to block sizes the
latter isn't a problem for large files on a proper DN, as the blocks
are spread over the disks and across the nodes.

On Wed, Dec 26, 2012 at 4:13 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
> Thanks Harsh, multiple concurrent read is generally faster or?
>
> regards,
> Lin
>
>
> On Wed, Dec 26, 2012 at 6:21 PM, Harsh J <[EMAIL PROTECTED]> wrote:
>>
>> There is no limitation in HDFS that limits reads of a block to a
>> single client at a time (no reason to do so) - so downloads can be as
>> concurrent as possible.
>>
>> On Wed, Dec 26, 2012 at 3:41 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
>> > Thanks Harsh,
>> >
>> > Supposing DistributedCache is uploaded by client, for each replica, in
>> > Hadoop design, it could only serve one download session (download from a
>> > mapper or a reducer which requires the DistributedCache) at a time until
>> > DistributedCache file download is completed, or it could serve multiple
>> > concurrent parallel download session (download from multiple mappers or
>> > reducers which requires the DistributedCache).
>> >
>> > regards,
>> > Lin
>> >
>> >
>> > On Wed, Dec 26, 2012 at 4:51 PM, Harsh J <[EMAIL PROTECTED]> wrote:
>> >>
>> >> Hi Lin,
>> >>
>> >> DistributedCache files are stored onto the HDFS by the client first.
>> >> The TaskTrackers download and localize it. Therefore, as with any
>> >> other file on HDFS, "downloads" can be efficiently parallel with
>> >> higher replicas.
>> >>
>> >> The point of having higher replication for these files is also tied to
>> >> the concept of racks in a cluster - you would want more replicas
>> >> spread across racks such that on task bootup the downloads happen with
>> >> rack locality.
>> >>
>> >> On Sat, Dec 22, 2012 at 6:54 PM, Lin Ma <[EMAIL PROTECTED]> wrote:
>> >> > Hi Kai,
>> >> >
>> >> > Smart answer! :-)
>> >> >
>> >> > The assumption you have is one distributed cache replica could only
>> >> > serve
>> >> > one download session for tasktracker node (this is why you get
>> >> > concurrency
>> >> > n/r). The question is, why one distributed cache replica cannot serve
>> >> > multiple concurrent download session? For example, supposing a
>> >> > tasktracker
>> >> > use elapsed time t to download a file from a specific distributed
>> >> > cache
>> >> > replica, it is possible for 2 tasktrackers to download from the
>> >> > specific
>> >> > distributed cache replica in parallel using elapsed time t as well,
>> >> > or
>> >> > 1.5
>> >> > t, which is faster than sequential download time 2t you mentioned
>> >> > before?
>> >> > "In total, r+n/r concurrent operations. If you optimize r depending
>> >> > on
>> >> > n,
>> >> > SRQT(n) is the optimal replication level." -- how do you get SRQT(n)
>> >> > for
>> >> > minimize r+n/r? Appreciate if you could point me to more details.
>> >> >
>> >> > regards,
>> >> > Lin
>> >> >
>> >> >
>> >> > On Sat, Dec 22, 2012 at 8:51 PM, Kai Voigt <[EMAIL PROTECTED]> wrote:
>> >> >>
>> >> >> Hi,
>> >> >>
>> >> >> simple math. Assuming you have n TaskTrackers in your cluster that
>> >> >> will
>> >> >> need to access the files in the distributed cache. And r is the
>> >> >> replication
>> >> >> level of those files.
>> >> >>
>> >> >> Copying the files into HDFS requires r copy operations over the
>> >> >> network.
>> >> >> The n TaskTrackers need to get their local copies from HDFS, so the
>> >> >> n
>> >> >> TaskTrackers copy from r DataNodes, so n/r concurrent operation. In
>> >> >> total,
>> >> >> r+n/r concurrent operations. If you optimize r depending on n,
>> >> >> SRQT(n)
>> >> >> is
>> >> >> the optimal replication level. So 10 is a reasonable default setting

Harsh J