Re: Random Shuffling
That's not the point. In Machine Learning one often divides a data set X
into f.e. three sets, one for the training, one for the validation, one for
the final testing. The sets are usually created randomly according to some
ratio. Thus it would be important to keep the ratio and to do the whole
process randomly.
Cheers,
Max
On Wed, Jun 24, 2015 at 9:51 AM, Stephan Ewen se...@apache.org wrote:
If you do rebalance(), it will redistribute elements round-robin
fashion, which should give you very even partition sizes.
On Tue, Jun 23, 2015 at 11:51 AM, Maximilian Alber
alber.maximil...@gmail.com wrote:
Thank you!
Still I cannot guarantee the size of each partition, or can I?
Something like randomSplit in Spark.
Cheers,
Max
On Mon, Jun 15, 2015 at 5:46 PM, Matthias J. Sax
mj...@informatik.hu-berlin.de wrote:
Hi,
using partitionCustom, the data distribution depends only on your
probability distribution. If it is uniform, you should be fine (ie,
choosing the channel like
private final Random random = new Random(System.currentTimeMillis());
int partition(K key, int numPartitions) {
return random.nextInt(numPartitions);
}
should do the trick.
-Matthias
On 06/15/2015 05:41 PM, Maximilian Alber wrote:
Thanks!
Ok, so for a random shuffle I need partitionCustom. But in that case
the
data might be out of balance then?
For the splitting. Is there no way to have exact sizes?
Cheers,
Max
On Mon, Jun 15, 2015 at 2:26 PM, Till Rohrmann trohrm...@apache.org
mailto:trohrm...@apache.org wrote:
Hi Max,
you can always shuffle your elements using the |rebalance| method.
What Flink here does is to distribute the elements of each
partition
among all available TaskManagers. This happens in a round-robin
fashion and is thus not completely random.
A different mean is the |partitionCustom| method which allows you
to
specify for each element to which partition it shall be sent. You
would have to specify a |Partitioner| to do this.
For the splitting there is at moment no syntactic sugar. What you
can do, though, is to assign each item a split ID and then use a
|filter| operation to filter the individual splits. Depending on
you
split ID distribution you will have differently sized splits.
Cheers,
Till
On Mon, Jun 15, 2015 at 1:50 PM Maximilian Alber
alber.maximil...@gmail.com
http://mailto:alber.maximil...@gmail.com wrote:
Hi Flinksters,
I would like to shuffle my elements in the data set and then
split it in two according to some ratio. Each element in the
data set has an unique id. Is there a nice way to do it with
the
flink api?
(It would be nice to have guaranteed random shuffling.)
Thanks!
Cheers,
Max
Re: Random Shuffling
A very simple way to achieve is to generate a random variate on the
driver that describes a mapping of datapoints to samples. Then you
simply join the dataset with this mapping to generate the samples.
This approach requires you to know the size of the dataset in advance,
but has the advantage that you can guarantee the sizes of the samples
and can easily support more involved techniques such as sampling with
replacement.
--sebastian
On 24.06.2015 10:38, Maximilian Alber wrote:
That's not the point. In Machine Learning one often divides a data set X
into f.e. three sets, one for the training, one for the validation, one
for the final testing. The sets are usually created randomly according
to some ratio. Thus it would be important to keep the ratio and to do
the whole process randomly.
Cheers,
Max
On Wed, Jun 24, 2015 at 9:51 AM, Stephan Ewen se...@apache.org
mailto:se...@apache.org wrote:
If you do rebalance(), it will redistribute elements round-robin
fashion, which should give you very even partition sizes.
On Tue, Jun 23, 2015 at 11:51 AM, Maximilian Alber
alber.maximil...@gmail.com mailto:alber.maximil...@gmail.com wrote:
Thank you!
Still I cannot guarantee the size of each partition, or can I?
Something like randomSplit in Spark.
Cheers,
Max
On Mon, Jun 15, 2015 at 5:46 PM, Matthias J. Sax
mj...@informatik.hu-berlin.de
mailto:mj...@informatik.hu-berlin.de wrote:
Hi,
using partitionCustom, the data distribution depends only on
your
probability distribution. If it is uniform, you should be
fine (ie,
choosing the channel like
private final Random random = new
Random(System.currentTimeMillis());
int partition(K key, int numPartitions) {
return random.nextInt(numPartitions);
}
should do the trick.
-Matthias
On 06/15/2015 05:41 PM, Maximilian Alber wrote:
Thanks!
Ok, so for a random shuffle I need partitionCustom. But in that
case the
data might be out of balance then?
For the splitting. Is there no way to have exact sizes?
Cheers,
Max
On Mon, Jun 15, 2015 at 2:26 PM, Till Rohrmann trohrm...@apache.org
mailto:trohrm...@apache.org
mailto:trohrm...@apache.org mailto:trohrm...@apache.org
wrote:
Hi Max,
you can always shuffle your elements using the |rebalance|
method.
What Flink here does is to distribute the elements of each
partition
among all available TaskManagers. This happens in a
round-robin
fashion and is thus not completely random.
A different mean is the |partitionCustom| method which allows
you to
specify for each element to which partition it shall be sent.
You
would have to specify a |Partitioner| to do this.
For the splitting there is at moment no syntactic sugar. What
you
can do, though, is to assign each item a split ID and then
use a
|filter| operation to filter the individual splits. Depending
on you
split ID distribution you will have differently sized splits.
Cheers,
Till
On Mon, Jun 15, 2015 at 1:50 PM Maximilian Alber
alber.maximil...@gmail.com mailto:alber.maximil...@gmail.com
http://mailto:alber.maximil...@gmail.com wrote:
Hi Flinksters,
I would like to shuffle my elements in the data
set and then
split it in two according to some ratio. Each
element in the
data set has an unique id. Is there a nice way to
do it with the
flink api?
(It would be nice to have guaranteed random
shuffling.)
Thanks!
Cheers,
Max
Re: Random Shuffling
Thank you!
Still I cannot guarantee the size of each partition, or can I?
Something like randomSplit in Spark.
Cheers,
Max
On Mon, Jun 15, 2015 at 5:46 PM, Matthias J. Sax
mj...@informatik.hu-berlin.de wrote:
Hi,
using partitionCustom, the data distribution depends only on your
probability distribution. If it is uniform, you should be fine (ie,
choosing the channel like
private final Random random = new Random(System.currentTimeMillis());
int partition(K key, int numPartitions) {
return random.nextInt(numPartitions);
}
should do the trick.
-Matthias
On 06/15/2015 05:41 PM, Maximilian Alber wrote:
Thanks!
Ok, so for a random shuffle I need partitionCustom. But in that case the
data might be out of balance then?
For the splitting. Is there no way to have exact sizes?
Cheers,
Max
On Mon, Jun 15, 2015 at 2:26 PM, Till Rohrmann trohrm...@apache.org
mailto:trohrm...@apache.org wrote:
Hi Max,
you can always shuffle your elements using the |rebalance| method.
What Flink here does is to distribute the elements of each partition
among all available TaskManagers. This happens in a round-robin
fashion and is thus not completely random.
A different mean is the |partitionCustom| method which allows you to
specify for each element to which partition it shall be sent. You
would have to specify a |Partitioner| to do this.
For the splitting there is at moment no syntactic sugar. What you
can do, though, is to assign each item a split ID and then use a
|filter| operation to filter the individual splits. Depending on you
split ID distribution you will have differently sized splits.
Cheers,
Till
On Mon, Jun 15, 2015 at 1:50 PM Maximilian Alber
alber.maximil...@gmail.com
http://mailto:alber.maximil...@gmail.com wrote:
Hi Flinksters,
I would like to shuffle my elements in the data set and then
split it in two according to some ratio. Each element in the
data set has an unique id. Is there a nice way to do it with the
flink api?
(It would be nice to have guaranteed random shuffling.)
Thanks!
Cheers,
Max
Random Shuffling
Hi Flinksters, I would like to shuffle my elements in the data set and then split it in two according to some ratio. Each element in the data set has an unique id. Is there a nice way to do it with the flink api? (It would be nice to have guaranteed random shuffling.) Thanks! Cheers, Max
Re: Random Shuffling
Hi Max, you can always shuffle your elements using the rebalance method. What Flink here does is to distribute the elements of each partition among all available TaskManagers. This happens in a round-robin fashion and is thus not completely random. A different mean is the partitionCustom method which allows you to specify for each element to which partition it shall be sent. You would have to specify a Partitioner to do this. For the splitting there is at moment no syntactic sugar. What you can do, though, is to assign each item a split ID and then use a filter operation to filter the individual splits. Depending on you split ID distribution you will have differently sized splits. Cheers, Till On Mon, Jun 15, 2015 at 1:50 PM Maximilian Alber alber.maximil...@gmail.com http://mailto:alber.maximil...@gmail.com wrote: Hi Flinksters, I would like to shuffle my elements in the data set and then split it in two according to some ratio. Each element in the data set has an unique id. Is there a nice way to do it with the flink api? (It would be nice to have guaranteed random shuffling.) Thanks! Cheers, Max
Re: Random Shuffling
I think, you need to implement an own Partitioner.java and hand it via DataSet.partitionCustom(partitioner, field) (Just specify any field you like; as you don't want to group by key, it doesn't matter.) When implementing the partitionier, you can ignore the key parameter and compute the output channel randomly. This is kind of a work-around, but it should work. -Matthias On 06/15/2015 01:49 PM, Maximilian Alber wrote: Hi Flinksters, I would like to shuffle my elements in the data set and then split it in two according to some ratio. Each element in the data set has an unique id. Is there a nice way to do it with the flink api? (It would be nice to have guaranteed random shuffling.) Thanks! Cheers, Max signature.asc Description: OpenPGP digital signature
Re: Random Shuffling
Thanks! Ok, so for a random shuffle I need partitionCustom. But in that case the data might be out of balance then? For the splitting. Is there no way to have exact sizes? Cheers, Max On Mon, Jun 15, 2015 at 2:26 PM, Till Rohrmann trohrm...@apache.org wrote: Hi Max, you can always shuffle your elements using the rebalance method. What Flink here does is to distribute the elements of each partition among all available TaskManagers. This happens in a round-robin fashion and is thus not completely random. A different mean is the partitionCustom method which allows you to specify for each element to which partition it shall be sent. You would have to specify a Partitioner to do this. For the splitting there is at moment no syntactic sugar. What you can do, though, is to assign each item a split ID and then use a filter operation to filter the individual splits. Depending on you split ID distribution you will have differently sized splits. Cheers, Till On Mon, Jun 15, 2015 at 1:50 PM Maximilian Alber alber.maximil...@gmail.com http://mailto:alber.maximil...@gmail.com wrote: Hi Flinksters, I would like to shuffle my elements in the data set and then split it in two according to some ratio. Each element in the data set has an unique id. Is there a nice way to do it with the flink api? (It would be nice to have guaranteed random shuffling.) Thanks! Cheers, Max
