Add error handling when log timestamp extraction fails

[rh-rahulshetty]

Issue

Identified a scenario where the entire model-pipeline fails when timestamp extraction for a log line fails either due to unknown timestamp format.

Log Line (redacted lines for safety):

Sep 02 21:33:49 ip-10-***** kubenswrapper[3872]: E0902 21:33:49.941756    3872 event.go:346] "Server rejected event (will not retry!)" err="Timeout: request did not complete within requested timeout - conte.......

Error:

INFO: Pandarallel will run on 4 workers.
INFO: Pandarallel will use Memory file system to transfer data between the main process and workers.
INFO: Pandarallel will run on 4 workers.
INFO: Pandarallel will use Memory file system to transfer data between the main process and workers.
Namespace(input_files=['../../debug/5d900be3/0.log'], time_range='all-data', output_dir='./tmp/output', debug_mode=True, process_log_files=True, process_txt_files=False, model_type=<ModelType.ZERO_SHOT: 'zero_shot'>, model_name=<ZeroShotModels.CROSSENCODER: 'cross-encoder/nli-MiniLM2-L6-H768'>, clean_up=False)
Input files:
['../../debug/5d900be3/0.log']
../../debug/5d900be3/0.log patoolib.is_archive(file_): False
../../debug/5d900be3/0.log os.path.isdir(file_): False
'.csv' in extensions: False
'.xml' in extensions: False
Files to process:
../../debug/5d900be3/0.log
100%|█████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00,  1.66it/s]
Debug mode is set to: True
Starting pandarallel for log processing
multiprocessing.pool.RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/usr/lib64/python3.11/multiprocessing/pool.py", line 125, in worker
    result = (True, func(*args, **kwds))
                    ^^^^^^^^^^^^^^^^^^^
  File "/usr/lib64/python3.11/multiprocessing/pool.py", line 51, in starmapstar
    return list(itertools.starmap(args[0], args[1]))
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandarallel/core.py", line 95, in __call__
    result = self.work_function(
             ^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandarallel/data_types/series.py", line 26, in work
    return data.apply(
           ^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandas/core/series.py", line 4924, in apply
    ).apply()
      ^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandas/core/apply.py", line 1427, in apply
    return self.apply_standard()
           ^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandas/core/apply.py", line 1507, in apply_standard
    mapped = obj._map_values(
             ^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandas/core/base.py", line 921, in _map_values
    return algorithms.map_array(arr, mapper, na_action=na_action, convert=convert)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandas/core/algorithms.py", line 1743, in map_array
    return lib.map_infer(values, mapper, convert=convert)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "lib.pyx", line 2972, in pandas._libs.lib.map_infer
  File "/home/rashetty/Desktop/LogAn/open-source/logan/preprocessing/preprocessing.py", line 828, in <lambda>
    df[['timestamps', 'epoch', 'text', 'preprocessed_text', 'numeric_count', "total_count", "token_count"]] = df['text'].parallel_apply(lambda log: pd.Series(self.process_fn(log, self.timezone_dict, self.master_timestamp_list, self.master_format_list)))
                                                                                                                                                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/preprocessing/preprocessing.py", line 667, in process_fn
    timestamp, ts = self.extract_ts(log, rbr, timezone_dict, master_timestamp_list, master_format_list)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/preprocessing/preprocessing.py", line 638, in extract_ts
    timestamp, ts, future_flag = self.master_datetime_extractor(log, timezone_dict, master_timestamp_list, master_format_list)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/preprocessing/preprocessing.py", line 584, in master_datetime_extractor
    future_flag = parsed_date.timestamp() >= current_datetime.timestamp()
                  ^^^^^^^^^^^^^^^^^^^^^^^
ValueError: year 0 is out of range
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/rashetty/Desktop/LogAn/open-source/logan/run_log_diagnosis.py", line 101, in <module>
    preprocessing_obj.preprocess(args.input_files, 
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/preprocessing/preprocessing.py", line 828, in preprocess
    df[['timestamps', 'epoch', 'text', 'preprocessed_text', 'numeric_count', "total_count", "token_count"]] = df['text'].parallel_apply(lambda log: pd.Series(self.process_fn(log, self.timezone_dict, self.master_timestamp_list, self.master_format_list)))
                                                                                                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/rashetty/Desktop/LogAn/open-source/logan/.venv/lib64/python3.11/site-packages/pandarallel/core.py", line 333, in closure
    results_promise.get()
  File "/usr/lib64/python3.11/multiprocessing/pool.py", line 774, in get
    raise self._value
ValueError: year 0 is out of range

Fix

To resolve the issue, this PR wraps the timestamp extraction with a simple try/except block and logs the failure.