尝试在h2o(版本3.20.0.5)中训练DRF分类器,错误“ H2OServerError:HTTP 500服务器错误”,没有进一步的解释。
---------------------------------------------------------------------------
H2OServerError Traceback (most recent call last)
<ipython-input-44-f52d1cb4b77a> in <module>()
4 training_frame=train_u, validation_frame=val_u,
5 weights_column='weight',
----> 6 max_runtime_secs=max_train_time_hrs*60*60)
7
8
/home/mapr/python-virtual-envs/ml1c/venv/lib/python2.7/site-packages/h2o/estimators/estimator_base.pyc in train(self, x, y, training_frame, offset_column, fold_column, weights_column, validation_frame, max_runtime_secs, ignored_columns, model_id, verbose)
224 rest_ver = parms.pop("_rest_version") if "_rest_version" in parms else 3
225
--> 226 model_builder_json = h2o.api("POST /%d/ModelBuilders/%s" % (rest_ver, self.algo), data=parms)
227 model = H2OJob(model_builder_json, job_type=(self.algo + " Model Build"))
228
/home/mapr/python-virtual-envs/ml1c/venv/lib/python2.7/site-packages/h2o/h2o.pyc in api(endpoint, data, json, filename, save_to)
101 # type checks are performed in H2OConnection class
102 _check_connection()
--> 103 return h2oconn.request(endpoint, data=data, json=json, filename=filename, save_to=save_to)
104
105
/home/mapr/python-virtual-envs/ml1c/venv/lib/python2.7/site-packages/h2o/backend/connection.pyc in request(self, endpoint, data, json, filename, save_to)
400 auth=self._auth, verify=self._verify_ssl_cert, proxies=self._proxies)
401 self._log_end_transaction(start_time, resp)
--> 402 return self._process_response(resp, save_to)
403
404 except (requests.exceptions.ConnectionError, requests.exceptions.HTTPError) as e:
/home/mapr/python-virtual-envs/ml1c/venv/lib/python2.7/site-packages/h2o/backend/connection.pyc in _process_response(response, save_to)
728 # Note that it is possible to receive valid H2OErrorV3 object in this case, however it merely means the server
729 # did not provide the correct status code.
--> 730 raise H2OServerError("HTTP %d %s:\n%r" % (status_code, response.reason, data))
731
732
H2OServerError: HTTP 500 Server Error:
Server error java.lang.NullPointerException:
Error: Caught exception: java.lang.NullPointerException
Request: None
有问题的代码段如下所示:
max_train_time_hrs = 8
drf_proc.train(
x=train_features, y=train_response,
training_frame=train_u, validation_frame=val_u,
weights_column='weight',
max_runtime_secs=max_train_time_hrs*60*60)
运行h2o.init()
命令的输出看起来像
Checking whether there is an H2O instance running at http://172.18.4.62:54321. connected.
Warning: Your H2O cluster version is too old (7 months and 24 days)! Please download and install the latest version from http://h2o.ai/download/
H2O cluster uptime: 06 secs
H2O cluster timezone: Pacific/Honolulu
H2O data parsing timezone: UTC
H2O cluster version: 3.20.0.5
H2O cluster version age: 7 months and 24 days !!!
H2O cluster name: H2O_88021
H2O cluster total nodes: 4
H2O cluster free memory: 15.34 Gb
H2O cluster total cores: 8
H2O cluster allowed cores: 8
H2O cluster status: accepting new members, healthy
H2O connection url: http://172.18.4.62:54321
H2O connection proxy: None
H2O internal security: False
H2O API Extensions: AutoML, XGBoost, Algos, Core V3, Core V4
Python version: 2.7.12 fin
虽然我意识到有一个警告,我正在使用的h2o版本“太旧”,我正在使用的h2o python软件包的版本以及我要连接的集群仍然匹配,但是由于无法升级,到访问此群集并需要特定版本的其他h2o应用程序访问(所有这些应用程序似乎在群集上运行都没有问题)。同时,任何Web浏览器都无法连接到H2O连接URL。
关于此处可能发生的事情或调试可能涉及的步骤的任何想法吗?
答案 0 :(得分:2)
15GB的内存可能不足以用于您希望持续8小时的训练过程。 (此外:我建议您使用early stopping,而不要使用max_runtime_secs
,或者同时使用h2o.init()
。)
作为调试步骤,建议您在Flow界面中观看(将浏览器指向端口54321-在train_features
输出中查看连接URL)。尤其要注意内存使用率如何随着时间而增加。
(有时会出现“ 500”错误,这表明它已经变得不稳定,而内存不足是常见的触发条件。)
如果您立即收到错误消息,则不太可能是问题所在(除非您拥有庞大的数据集)。
在那种情况下,如果特定的列或数据行可能引起问题,我将尝试缩小范围。例如。
train_features
中列的前半部分train_u
中列的后半部分train_u
中的前半行valid_u
中的行的后半部分auth()
相同如果其中一对实验崩溃了,而另一对没有崩溃,那么请在崩溃的另一半上重复实验。