java.lang.ArrayIndexOutOfBoundsException: 2

JIRA | Johannes | 3 months ago
  1. 0

    The following assignment of my variable rnd_data... {code} rnd_data = [[1], [2], [3], [1], [4], [2], [1], [4], [5], [10], [3]] rnd_f = h2o.H2OFrame.from_python(rnd_data, destination_frame = "rnd") rnd_f075, rnd_f025 = rnd_f.split_frame(ratios = [0.75], destination_frames = ["rnd075", "rnd025"]) kmeans6 = h2o.estimators.kmeans.H2OKMeansEstimator(model_id = "rnd_kmeans_6", training_frame = rnd_f075.frame_id, validation_frame = rnd_f025.frame_id, nfolds = 2, fold_assignment = "Random", score_each_iteration = True, k = 6) kmeans6.train(training_frame = rnd_f075, validation_frame = rnd_f025) {code} results in an ArrayIndexOutOfBoundsException: {code:none} kmeans Model Build progress: | (failed) --------------------------------------------------------------------------- OSError Traceback (most recent call last) <ipython-input-27-4067a2add74e> in <module>() ----> 1 kmeans6.train(training_frame = rnd_f075, validation_frame = rnd_f025) /opt/conda/lib/python3.5/site-packages/h2o/estimators/estimator_base.py in train(self, x, y, training_frame, offset_column, fold_column, weights_column, validation_frame, max_runtime_secs, **params) 161 parms["weights_column"] = weights_column 162 parms["max_runtime_secs"] = max_runtime_secs --> 163 self.build_model(parms) 164 165 def build_model(self, algo_params): /opt/conda/lib/python3.5/site-packages/h2o/estimators/estimator_base.py in build_model(self, algo_params) 174 if is_auto_encoder and y is not None: raise ValueError("y should not be specified for autoencoder.") 175 if not is_unsupervised and y is None: raise ValueError("Missing response") --> 176 self._model_build(x, y, training_frame, validation_frame, algo_params) 177 178 def _model_build(self, x, y, tframe, vframe, kwargs): /opt/conda/lib/python3.5/site-packages/h2o/estimators/estimator_base.py in _model_build(self, x, y, tframe, vframe, kwargs) 201 return 202 --> 203 model.poll() 204 model_json = h2o.api("GET /%d/Models/%s" % (rest_ver, model.dest_key))["models"][0] 205 self._resolve_model(model.dest_key, model_json) /opt/conda/lib/python3.5/site-packages/h2o/job.py in poll(self) 75 if (isinstance(self.job, dict)) and ("stacktrace" in list(self.job)): 76 raise EnvironmentError("Job with key {} failed with an exception: {}\nstacktrace: " ---> 77 "\n{}".format(self.job_key, self.exception, self.job["stacktrace"])) 78 else: 79 raise EnvironmentError("Job with key %s failed with an exception: %s" % (self.job_key, self.exception)) OSError: Job with key $0301ac11000332d4ffffffff$_a3c95020f0efb0e769cf63bf75024abf failed with an exception: java.lang.ArrayIndexOutOfBoundsException: 2 stacktrace: java.lang.ArrayIndexOutOfBoundsException: 2 at hex.kmeans.KMeans$KMeansDriver.createScoringHistoryTable(KMeans.java:364) at hex.kmeans.KMeans$KMeansDriver.computeStatsFillModel(KMeans.java:208) at hex.kmeans.KMeans$KMeansDriver.computeImpl(KMeans.java:281) at hex.ModelBuilder$Driver.compute2(ModelBuilder.java:169) at water.H2O$H2OCountedCompleter.compute(H2O.java:1198) at jsr166y.CountedCompleter.exec(CountedCompleter.java:468) at jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263) at jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:974) at jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477) at jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104) {code} Same error, if I cast the python list into a numpy array, i.e.: {code:python} rnd_data = np.array(rnd_data) {code} If I do this... {code:python} rnd_data = np.random.rand(30) {code} ...then the error is: {code:none} --------------------------------------------------------------------------- H2OResponseError Traceback (most recent call last) <ipython-input-37-4067a2add74e> in <module>() ----> 1 kmeans6.train(training_frame = rnd_f075, validation_frame = rnd_f025) /opt/conda/lib/python3.5/site-packages/h2o/estimators/estimator_base.py in train(self, x, y, training_frame, offset_column, fold_column, weights_column, validation_frame, max_runtime_secs, **params) 161 parms["weights_column"] = weights_column 162 parms["max_runtime_secs"] = max_runtime_secs --> 163 self.build_model(parms) 164 165 def build_model(self, algo_params): /opt/conda/lib/python3.5/site-packages/h2o/estimators/estimator_base.py in build_model(self, algo_params) 174 if is_auto_encoder and y is not None: raise ValueError("y should not be specified for autoencoder.") 175 if not is_unsupervised and y is None: raise ValueError("Missing response") --> 176 self._model_build(x, y, training_frame, validation_frame, algo_params) 177 178 def _model_build(self, x, y, tframe, vframe, kwargs): /opt/conda/lib/python3.5/site-packages/h2o/estimators/estimator_base.py in _model_build(self, x, y, tframe, vframe, kwargs) 194 rest_ver = kwargs.pop("_rest_version") if "_rest_version" in kwargs else 3 195 --> 196 model = H2OJob(h2o.api("POST /%d/ModelBuilders/%s" % (rest_ver, self.algo), data=kwargs), 197 job_type=(self.algo + " Model Build")) 198 /opt/conda/lib/python3.5/site-packages/h2o/h2o.py in api(endpoint, data, json, filename, save_to) 76 # type checks are performed in H2OConnection class 77 _check_connection() ---> 78 return h2oconn.request(endpoint, data=data, json=json, filename=filename, save_to=save_to) 79 80 /opt/conda/lib/python3.5/site-packages/h2o/backend/connection.py in request(self, endpoint, data, json, filename, save_to) 249 auth=self._auth, verify=self._verify_ssl_cert, proxies=self._proxies) 250 self._log_end_transaction(start_time, resp) --> 251 return self._process_response(resp, save_to) 252 253 except (requests.exceptions.ConnectionError, requests.exceptions.HTTPError) as e: /opt/conda/lib/python3.5/site-packages/h2o/backend/connection.py in _process_response(response, save_to) 574 # Client errors (400 = "Bad Request", 404 = "Not Found", 412 = "Precondition Failed") 575 if status_code in {400, 404, 412} and isinstance(data, (H2OErrorV3, H2OModelBuilderErrorV3)): --> 576 raise H2OResponseError(data) 577 578 # Server errors (notably 500 = "Server Error") H2OResponseError: <h2o.schemas.error.H2OModelBuilderErrorV3 object at 0x7fd12bdc46a0> {code} But if I do as follows, then kmeans is successful: {code:python} rnd_data = np.random.rand(30,1) {code} I however think, that any one of the above assignments to rnd_data should work.

    JIRA | 3 months ago | Johannes
    java.lang.ArrayIndexOutOfBoundsException: 2
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    Root Cause Analysis

    1. java.lang.ArrayIndexOutOfBoundsException

      2

      at hex.kmeans.KMeans$KMeansDriver.createScoringHistoryTable()
    2. hex.kmeans
      KMeans$KMeansDriver.computeImpl
      1. hex.kmeans.KMeans$KMeansDriver.createScoringHistoryTable(KMeans.java:364)
      2. hex.kmeans.KMeans$KMeansDriver.computeStatsFillModel(KMeans.java:208)
      3. hex.kmeans.KMeans$KMeansDriver.computeImpl(KMeans.java:281)
      3 frames
    3. hex
      ModelBuilder$Driver.compute2
      1. hex.ModelBuilder$Driver.compute2(ModelBuilder.java:169)
      1 frame
    4. water
      H2O$H2OCountedCompleter.compute
      1. water.H2O$H2OCountedCompleter.compute(H2O.java:1198)
      1 frame
    5. jsr166y
      ForkJoinWorkerThread.run
      1. jsr166y.CountedCompleter.exec(CountedCompleter.java:468)
      2. jsr166y.ForkJoinTask.doExec(ForkJoinTask.java:263)
      3. jsr166y.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:974)
      4. jsr166y.ForkJoinPool.runWorker(ForkJoinPool.java:1477)
      5. jsr166y.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:104)
      5 frames