I've been working with H2O for the last year, and I am getting very tired of server crashes. I have given up on "nightly releases", as they are easily crashed by my data sets. Please tell me where I can download a release that is stable.
Charles
My environment is:
- Windows 10 enterprise, build 1607, with 64 GB memory.
- Java SE Development Kit 8 Update 77 (64-bit).
- Anaconda Python 3.6.2-0.
I started the server with:
localH2O = h2o.init(ip = "localhost",
port = 54321,
max_mem_size="12G",
nthreads = 4)
The h2o init information is:
H2O cluster uptime: 12 hours 12 mins
H2O cluster version: 3.10.5.2
H2O cluster version age: 1 month and 6 days
H2O cluster name: H2O_from_python_Charles_ji1ndk
H2O cluster total nodes: 1
H2O cluster free memory: 6.994 Gb
H2O cluster total cores: 8
H2O cluster allowed cores: 4
H2O cluster status: locked, healthy
H2O connection url: http://localhost:54321
H2O connection proxy:
H2O internal security: False
Python version: 3.6.2 final
The crash information is:
OSError: Job with key $03017f00000132d4ffffffff$_a0ce9b2c855ea5cff1aa58d65c2a4e7c failed with an exception: java.lang.AssertionError: I am really confused about the heap usage; MEM_MAX=11453595648 heapUsedGC=11482667352
stacktrace:
java.lang.AssertionError: I am really confused about the heap usage; MEM_MAX=11453595648 heapUsedGC=11482667352
at water.MemoryManager.set_goals(MemoryManager.java:97)
at water.MemoryManager.malloc(MemoryManager.java:265)
at water.MemoryManager.malloc(MemoryManager.java:222)
at water.MemoryManager.arrayCopyOfRange(MemoryManager.java:291)
at water.AutoBuffer.expandByteBuffer(AutoBuffer.java:719)
at water.AutoBuffer.putA4f(AutoBuffer.java:1355)
at hex.deeplearning.Storage$DenseRowMatrix$Icer.write129(Storage$DenseRowMatrix$Icer.java)
at hex.deeplearning.Storage$DenseRowMatrix$Icer.write(Storage$DenseRowMatrix$Icer.java)
at water.Iced.write(Iced.java:61)
at water.AutoBuffer.put(AutoBuffer.java:771)
at water.AutoBuffer.putA(AutoBuffer.java:883)
at hex.deeplearning.DeepLearningModelInfo$Icer.write128(DeepLearningModelInfo$Icer.java)
at hex.deeplearning.DeepLearningModelInfo$Icer.write(DeepLearningModelInfo$Icer.java)
at water.Iced.write(Iced.java:61)
at water.AutoBuffer.put(AutoBuffer.java:771)
at hex.deeplearning.DeepLearningModel$Icer.write105(DeepLearningModel$Icer.java)
at hex.deeplearning.DeepLearningModel$Icer.write(DeepLearningModel$Icer.java)
at water.Iced.write(Iced.java:61)
at water.Iced.asBytes(Iced.java:42)
at water.Value.<init>(Value.java:348)
at water.TAtomic.atomic(TAtomic.java:22)
at water.Atomic.compute2(Atomic.java:56)
at water.Atomic.fork(Atomic.java:39)
at water.Atomic.invoke(Atomic.java:31)
at water.Lockable.unlock(Lockable.java:181)
at water.Lockable.unlock(Lockable.java:176)
at hex.deeplearning.DeepLearning$DeepLearningDriver.trainModel(DeepLearning.java:491)
at hex.deeplearning.DeepLearning$DeepLearningDriver.buildModel(DeepLearning.java:311)
at hex.deeplearning.DeepLearning$DeepLearningDriver.computeImpl(DeepLearning.java:216)
at hex.ModelBuilder$Driver.compute2(ModelBuilder.java:173)
at hex.deeplearning.DeepLearning$DeepLearningDriver.compute2(DeepLearning.java:209)
at water.H2O$H2OCountedCompleter.compute(H2O.java:1349)
at jsr166y.CountedCompleter.exec(CountedCompleter.java:468)
at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263)
at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:974)
at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477)
at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)