Hi Yunming,
The problem I see with what you are proposing is that Hadoop only gives
you a single input vector per call of CIMapper.map(). Using multiple
threads to perform the body of that method would not be of benefit. If
you want to experiment with thread-based concurrent execution of that
clustering implementation, I'd suggest you look at the serial,
all-in-memory implementation (ClusterIterator.iterate()) first. I think
you might find that the classifier.classify() and policy.select() calls
are read-only and the classifier.train() method would be the one to
synchronize. This is just an educated guess, however. You are really on
your own in this endeavor.
But good luck if you decide to experiment,
Jeff
On 12/21/12 10:00 AM, Yunming Zhang wrote:
Hi,
I am trying to compare performance between using parallelism by using more
mappers (the way you suggested with reducing the max input split size) and
using possible parallelism within the Mapper, there can be advantage to using
fewer number of mappers,
Does anyone have any idea on where to start to make the CIMapper thread safe ?
Do I have to make changes to every application or I could just change some
implementation in the general classes used by all applications? It would be
really helpful if someone could point me to the right direction,
Thanks
Yunming
On Dec 20, 2012, at 10:54 PM, Marty Kube <[email protected]>
wrote:
Writing thread safe code is hard. Don't do it unless you have too.
On Dec 20, 2012, at 4:28 AM, Sean Owen <[email protected]> wrote:
... but making the implementation thread-safe won't make it be used by
multiple threads. If you want more parallelism, suggest to Hadoop to
use more mappers by reducing the max input split size. But this is
still not going to require your mappers to be thread-safe.
if you mean you are making your own parallelism in miniature by
writing a multi-threaded mapper, I wouldn't bother. Just use more
parallelism via Hadoop.
On Thu, Dec 20, 2012 at 3:31 AM, Yunming Zhang
<[email protected]> wrote:
Thanks Marty, Sean,
yeah, I took a look at the source code yesterday and realized that it is not
thread safe as well,
I am working on a high performance mapper that require making the mapper thread safe
so I could exploit the data parallelism that comes with processing multiple input
<key, val> pairs to a single mapper,
I am currently researching into if there is any easy way that I could make the
CIMapper implementation thread safe by may be making a few key data structures
that are thread safe, like the OpenIntDoubleHashMap, and hopefully this won't
screw up the correctness of the algorithm itself,
Yunming
On Dec 20, 2012, at 9:07 AM, Marty Kube <[email protected]>
wrote:
Sean is right, most MR code is not and does not need to be thread safe.
Why are you writing a multi-threaded mapper?
On 12/19/2012 07:50 PM, Sean Owen wrote:
Hadoop will only use one thread with one Mapper or Reducer instance. Unless
you are somehow spawning threads on your own concurrency should not be an
issue. I don't known if this behavior is guaranteed but seems to be how it
always works.
On Dec 19, 2012 4:03 PM, "Yunming Zhang" <[email protected]> wrote:
Hi ,
I am developing a custom mapper that is somewhat similar to the
multithreaded mapper that came with Hadoop, and I am getting weird errors
when running using multiple threads processing multiple input key, value
pairs simultaneously, here is the stack trace, I looked into
OpenIntDoubleHashMap, and it seems to be stemmed from null values stored in
the tables,
attempt_201212190955_0004_m_000000_0:
java.lang.ArrayIndexOutOfBoundsException: 24
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.math.map.OpenIntDoubleHashMap.indexOfKey(OpenIntDoubleHashMap.java:278)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.math.map.OpenIntDoubleHashMap.get(OpenIntDoubleHashMap.java:198)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.math.RandomAccessSparseVector.getQuick(RandomAccessSparseVector.java:130)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.math.AbstractVector.assign(AbstractVector.java:738)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.clustering.AbstractCluster.observe(AbstractCluster.java:263)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.clustering.AbstractCluster.observe(AbstractCluster.java:234)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.clustering.AbstractCluster.observe(AbstractCluster.java:229)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.clustering.AbstractCluster.observe(AbstractCluster.java:37)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.clustering.classify.ClusterClassifier.train(ClusterClassifier.java:158)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.clustering.iterator.CIMapper.map(CIMapper.java:46)
attempt_201212190955_0004_m_000000_0: at
org.apache.mahout.clustering.iterator.CIMapper.map(CIMapper.java:18)
Not sure if anyone knows if it is inherently thread safe to process
multiple input key, val pair to the mapper simultaneously ?
Thanks
Yunming
