Please ignore this whole thread. It's working out of nowhere. I'm not sure what was the root cause. After I restarted the VM the previous SIFT code also started working.

On Fri, Jun 5, 2015 at 10:40 PM, Sam Stoelinga <sammiestoel@gmail.com> wrote:
Thanks Davies. I will file a bug later with code and single image as dataset. Next to that I can give anybody access to my vagrant VM that already has spark with OpenCV and the dataset available.

Or you can setup the same vagrant machine at your place. All is automated ^^
git clone https://github.com/samos123/computer-vision-cloud-platform
cd computer-vision-cloud-platform
./scripts/setup.sh
vagrant ssh

(Expect failures, I haven't cleaned up and tested it for other people) btw I study at Tsinghua also currently.

On Fri, Jun 5, 2015 at 2:43 PM, Davies Liu <davies@databricks.com> wrote:
Please file a bug here: https://issues.apache.org/jira/browse/SPARK/

Could you also provide a way to reproduce this bug (including some datasets)?

On Thu, Jun 4, 2015 at 11:30 PM, Sam Stoelinga <sammiestoel@gmail.com> wrote:
> I've changed the SIFT feature extraction to SURF feature extraction and it
> works...
>
> Following line was changed:
> sift = cv2.xfeatures2d.SIFT_create()
>
> to
>
> sift = cv2.xfeatures2d.SURF_create()
>
> Where should I file this as a bug? When not running on Spark it works fine
> so I'm saying it's a spark bug.
>
> On Fri, Jun 5, 2015 at 2:17 PM, Sam Stoelinga <sammiestoel@gmail.com> wrote:
>>
>> Yea should have emphasized that. I'm running the same code on the same VM.
>> It's a VM with spark in standalone mode and I run the unit test directly on
>> that same VM. So OpenCV is working correctly on that same machine but when
>> moving the exact same OpenCV code to spark it just crashes.
>>
>> On Tue, Jun 2, 2015 at 5:06 AM, Davies Liu <davies@databricks.com> wrote:
>>>
>>> Could you run the single thread version in worker machine to make sure
>>> that OpenCV is installed and configured correctly?
>>>
>>> On Sat, May 30, 2015 at 6:29 AM, Sam Stoelinga <sammiestoel@gmail.com>
>>> wrote:
>>> > I've verified the issue lies within Spark running OpenCV code and not
>>> > within
>>> > the sequence file BytesWritable formatting.
>>> >
>>> > This is the code which can reproduce that spark is causing the failure
>>> > by
>>> > not using the sequencefile as input at all but running the same
>>> > function
>>> > with same input on spark but fails:
>>> >
>>> > def extract_sift_features_opencv(imgfile_imgbytes):
>>> >     imgfilename, discardsequencefile = imgfile_imgbytes
>>> >     imgbytes = bytearray(open("/tmp/img.jpg", "rb").read())
>>> >     nparr = np.fromstring(buffer(imgbytes), np.uint8)
>>> >     img = cv2.imdecode(nparr, 1)
>>> >     gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
>>> >     sift = cv2.xfeatures2d.SIFT_create()
>>> >     kp, descriptors = sift.detectAndCompute(gray, None)
>>> >     return (imgfilename, "test")
>>> >
>>> > And corresponding tests.py:
>>> > https://gist.github.com/samos123/d383c26f6d47d34d32d6
>>> >
>>> >
>>> > On Sat, May 30, 2015 at 8:04 PM, Sam Stoelinga <sammiestoel@gmail.com>
>>> > wrote:
>>> >>
>>> >> Thanks for the advice! The following line causes spark to crash:
>>> >>
>>> >> kp, descriptors = sift.detectAndCompute(gray, None)
>>> >>
>>> >> But I do need this line to be executed and the code does not crash
>>> >> when
>>> >> running outside of Spark but passing the same parameters. You're
>>> >> saying
>>> >> maybe the bytes from the sequencefile got somehow transformed and
>>> >> don't
>>> >> represent an image anymore causing OpenCV to crash the whole python
>>> >> executor.
>>> >>
>>> >> On Fri, May 29, 2015 at 2:06 AM, Davies Liu <davies@databricks.com>
>>> >> wrote:
>>> >>>
>>> >>> Could you try to comment out some lines in
>>> >>> `extract_sift_features_opencv` to find which line cause the crash?
>>> >>>
>>> >>> If the bytes came from sequenceFile() is broken, it's easy to crash a
>>> >>> C library in Python (OpenCV).
>>> >>>
>>> >>> On Thu, May 28, 2015 at 8:33 AM, Sam Stoelinga
>>> >>> <sammiestoel@gmail.com>
>>> >>> wrote:
>>> >>> > Hi sparkers,
>>> >>> >
>>> >>> > I am working on a PySpark application which uses the OpenCV
>>> >>> > library. It
>>> >>> > runs
>>> >>> > fine when running the code locally but when I try to run it on
>>> >>> > Spark on
>>> >>> > the
>>> >>> > same Machine it crashes the worker.
>>> >>> >
>>> >>> > The code can be found here:
>>> >>> > https://gist.github.com/samos123/885f9fe87c8fa5abf78f
>>> >>> >
>>> >>> > This is the error message taken from STDERR of the worker log:
>>> >>> > https://gist.github.com/samos123/3300191684aee7fc8013
>>> >>> >
>>> >>> > Would like pointers or tips on how to debug further? Would be nice
>>> >>> > to
>>> >>> > know
>>> >>> > the reason why the worker crashed.
>>> >>> >
>>> >>> > Thanks,
>>> >>> > Sam Stoelinga
>>> >>> >
>>> >>> >
>>> >>> > org.apache.spark.SparkException: Python worker exited unexpectedly
>>> >>> > (crashed)
>>> >>> > at
>>> >>> >
>>> >>> > org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:172)
>>> >>> > at
>>> >>> >
>>> >>> >
>>> >>> > org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:176)
>>> >>> > at
>>> >>> > org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:94)
>>> >>> > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>>> >>> > at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>>> >>> > at
>>> >>> > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
>>> >>> > at org.apache.spark.scheduler.Task.run(Task.scala:64)
>>> >>> > at
>>> >>> >
>>> >>> > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
>>> >>> > at
>>> >>> >
>>> >>> >
>>> >>> > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>>> >>> > at
>>> >>> >
>>> >>> >
>>> >>> > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>>> >>> > at java.lang.Thread.run(Thread.java:745)
>>> >>> > Caused by: java.io.EOFException
>>> >>> > at java.io.DataInputStream.readInt(DataInputStream.java:392)
>>> >>> > at
>>> >>> >
>>> >>> > org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:108)
>>> >>> >
>>> >>> >
>>> >>> >
>>> >>
>>> >>
>>> >
>>
>>
>