Bugfix/prod 399 triggered prediction error on public api production at 2022 07 29 t 16 07 15 529 z

spark_log_parser/__init__.py

@@ -1,3 +1,3 @@
 """Tools for providing Spark event log"""
 
-__version__ = "0.1.1"
+__version__ = "0.1.2"

spark_log_parser/cli.py

@@ -3,12 +3,14 @@
 import sys
 import tempfile
 from pathlib import Path
+from urllib.parse import unquote
 
 import spark_log_parser
 
 logging.captureWarnings(True)
 
 from spark_log_parser.eventlog import EventLogBuilder  # noqa: E402
+from spark_log_parser.extractor import Extractor  # noqa: E402
 from spark_log_parser.parsing_models.application_model_v2 import sparkApplication  # noqa: E402
 
 logger = logging.getLogger("spark_log_parser")
@@ -39,7 +41,10 @@ def main():
     print("--Processing log file: " + str(args.log_file))
 
     with tempfile.TemporaryDirectory() as work_dir:
-        event_log = EventLogBuilder(args.log_file.resolve().as_uri(), work_dir).build()
+
+        log_path = unquote(args.log_file.resolve().as_uri())
+        event_log_paths = Extractor(log_path, work_dir).extract()
+        event_log = EventLogBuilder(event_log_paths, work_dir).build()
         app = sparkApplication(eventlog=str(event_log))
 
     if args.log_file.suffixes:

spark_log_parser/eventlog.py

@@ -1,27 +1,22 @@
 import json
 import tempfile
 from pathlib import Path
-from urllib.parse import ParseResult
 
 import pandas as pd
 
-from spark_log_parser.extractor import Extractor, ExtractThresholds
-
 
 class EventLogBuilder:
     def __init__(
         self,
-        source_url: ParseResult | str,
+        event_log_paths: list[Path] | list[str],
         work_dir: Path | str,
-        s3_client=None,
-        extract_thresholds=ExtractThresholds(),
     ):
-        self.source_url = source_url
+
+        self.event_log_paths = self._validate_event_log_paths(event_log_paths)
         self.work_dir = self._validate_work_dir(work_dir)
-        self.s3_client = s3_client
-        self.extractor = Extractor(
-            self.source_url, self.work_dir, self.s3_client, extract_thresholds
-        )
+
+    def _validate_event_log_paths(self, event_log_paths: list[Path] | list[str]) -> list[Path]:
+        return [Path(x) for x in event_log_paths]
 
     def _validate_work_dir(self, work_dir: Path | str) -> Path:
         work_dir_path = work_dir if isinstance(work_dir, Path) else Path(work_dir)
@@ -31,12 +26,11 @@ def _validate_work_dir(self, work_dir: Path | str) -> Path:
         return work_dir_path
 
     def build(self) -> Path:
-        paths = self.extractor.extract()
 
-        if not paths:
+        if not self.event_log_paths:
             raise ValueError("No files found")
 
-        self.event_log = self._get_event_log(paths)
+        self.event_log = self._get_event_log(self.event_log_paths)
 
         return self.event_log
 
@@ -68,9 +62,11 @@ def _get_event_log(self, paths: list[Path]) -> Path:
         return log_files[0]
 
     def _concat(self, rollover_dat: list[tuple[str, str, str]]) -> Path:
-        rollover_df = pd.DataFrame(
-            rollover_dat, columns=["rollover_index", "context_id", "path"]
-        ).sort_values("rollover_index")
+        rollover_df = (
+            pd.DataFrame(rollover_dat, columns=["rollover_index", "context_id", "path"])
+            .sort_values("rollover_index")
+            .reset_index()
+        )
 
         if not len(rollover_df.context_id.unique()) == 1:
             raise ValueError("Not all rollover log files have the same Spark context ID")

tests/test_bad_eventlog.py

@@ -3,46 +3,41 @@
 from pathlib import Path
 from zipfile import ZipFile
 
-from spark_log_parser.eventlog import EventLogBuilder
+from spark_log_parser import eventlog, extractor
 
 
 class BadEventLog(unittest.TestCase):
-    def test_multiple_context_ids(self):
-        event_log = Path("tests", "logs", "bad", "non-unique-context-id.zip").resolve()
+    def check_value_error(self, event_log_path, msg):
 
         with tempfile.TemporaryDirectory() as temp_dir:
-            with self.assertRaises(
-                ValueError, msg="Not all rollover files have the same Spark context ID"
-            ):
-                EventLogBuilder(event_log.as_uri(), temp_dir).build()
+            with self.assertRaises(ValueError) as cm:
+
+                event_log_paths = extractor.Extractor(event_log_path.as_uri(), temp_dir).extract()
+                eventlog.EventLogBuilder(event_log_paths, temp_dir).build()
+
+            assert str(cm.exception) == msg  # , "Exception message matches"
+
+    def test_multiple_context_ids(self):
+        event_log = Path("tests", "logs", "bad", "non-unique-context-id.zip").resolve()
+        self.check_value_error(
+            event_log, "Not all rollover log files have the same Spark context ID"
+        )
 
     def test_missing_dbc_event(self):
         event_log = Path("tests", "logs", "bad", "missing-dbc-event.zip").resolve()
-
-        with tempfile.TemporaryDirectory() as temp_dir:
-            with self.assertRaises(ValueError, msg="Expected DBC event not found"):
-                EventLogBuilder(event_log.as_uri(), temp_dir).build()
+        self.check_value_error(event_log, "No rollover properties found in log file")
 
     def test_duplicate_log_part(self):
         event_log = Path("tests", "logs", "bad", "duplicate-part.tgz").resolve()
-
-        with tempfile.TemporaryDirectory() as temp_dir:
-            with self.assertRaises(ValueError, msg="Duplicate rollover file detected"):
-                EventLogBuilder(event_log.as_uri(), temp_dir).build()
+        self.check_value_error(event_log, "Duplicate rollover log file detected")
 
     def test_missing_log_part(self):
         event_log = Path("tests", "logs", "bad", "missing-part.zip").resolve()
-
-        with tempfile.TemporaryDirectory() as temp_dir:
-            with self.assertRaises(ValueError, msg="Rollover file appears to be missing"):
-                EventLogBuilder(event_log.as_uri(), temp_dir).build()
+        self.check_value_error(event_log, "Rollover log file appears to be missing")
 
     def test_missing_first_part(self):
         event_log = Path("tests", "logs", "bad", "missing-first-part.zip").resolve()
-
-        with tempfile.TemporaryDirectory() as temp_dir:
-            with self.assertRaises(ValueError, msg="Rollover file appears to be missing"):
-                EventLogBuilder(event_log.as_uri(), temp_dir).build()
+        self.check_value_error(event_log, "Rollover log file appears to be missing")
 
     def test_only_non_first_part(self):
         with tempfile.TemporaryDirectory() as temp_dir:
@@ -51,10 +46,8 @@ def test_only_non_first_part(self):
                     [zinfo for zinfo in zfile.infolist() if not zinfo.is_dir()][0], temp_dir
                 )
 
-            with self.assertRaises(ValueError, msg="Rollover file appears to be missing"):
-                EventLogBuilder(Path(temp_dir).as_uri(), temp_dir).build()
+            self.check_value_error(Path(temp_dir), "Rollover log file appears to be missing")
 
     def test_empty_log_dir(self):
         with tempfile.TemporaryDirectory() as temp_dir:
-            with self.assertRaises(ValueError, msg="No log files found"):
-                EventLogBuilder(Path(temp_dir).as_uri(), temp_dir).build()
+            self.check_value_error(Path(temp_dir), "No files found")

tests/test_eventlog.py

@@ -4,34 +4,32 @@
 import zipfile
 from pathlib import Path
 
-from spark_log_parser import eventlog
+from spark_log_parser import eventlog, extractor
 
 
-def test_simple_emr_log():
-    event_log_path = Path("tests", "logs", "emr.zip").resolve()
+def get_event(event_log_path):
 
     with tempfile.TemporaryDirectory() as temp_dir:
-        event_log = eventlog.EventLogBuilder(
-            source_url=event_log_path.as_uri(), work_dir=temp_dir
-        ).build()
+        event_log_paths = extractor.Extractor(event_log_path.resolve().as_uri(), temp_dir).extract()
+        event_log = eventlog.EventLogBuilder(event_log_paths, temp_dir).build()
 
         with open(event_log) as log_fobj:
             event = json.loads(log_fobj.readline())
 
-    assert all(key in event for key in ["Event", "Spark Version"]), "All keys are present"
+        return event
+
+
+def test_simple_emr_log():
+    event_log_path = Path("tests", "logs", "emr.zip").resolve()
+    event = get_event(event_log_path)
 
+    assert all(key in event for key in ["Event", "Spark Version"]), "All keys are present"
     assert event["Event"] == "SparkListenerLogStart", "Expected first event is present"
 
 
 def test_simple_databricks_log():
     event_log_path = Path("tests", "logs", "databricks.zip").resolve()
-
-    with tempfile.TemporaryDirectory() as temp_dir:
-        event_log = eventlog.EventLogBuilder(event_log_path.as_uri(), temp_dir).build()
-
-        with open(event_log) as log_fobj:
-            event = json.loads(log_fobj.readline())
-
+    event = get_event(event_log_path)
     assert all(
         key in event
         for key in ["Event", "Spark Version", "Timestamp", "Rollover Number", "SparkContext Id"]
@@ -40,12 +38,19 @@ def test_simple_databricks_log():
 
 def test_raw_databricks_log():
     event_log_path = Path("tests", "logs", "databricks.json").resolve()
+    event = get_event(event_log_path)
 
-    with tempfile.TemporaryDirectory() as temp_dir:
-        event_log = eventlog.EventLogBuilder(event_log_path.as_uri(), temp_dir).build()
+    assert all(
+        key in event
+        for key in ["Event", "Spark Version", "Timestamp", "Rollover Number", "SparkContext Id"]
+    ), "All keys are present"
 
-        with open(event_log) as log_fobj:
-            event = json.loads(log_fobj.readline())
+    assert event["Event"] == "DBCEventLoggingListenerMetadata", "Expected first event is present"
+
+
+def test_log_in_dir():
+    event_log_path = Path("tests", "logs", "log_in_dir", "databricks.json.gz").resolve()
+    event = get_event(event_log_path)
 
     assert all(
         key in event
@@ -71,9 +76,12 @@ def test_databricks_messy_rollover_log_dir(self):
                 zfile.extractall(temp_dir_path)
                 self.validate_log(temp_dir_path, 3, 16945)
 
-    def validate_log(self, event_log: Path, log_file_total: int, log_entry_total: int):
+    def validate_log(self, event_log_path: Path, log_file_total: int, log_entry_total: int):
         with tempfile.TemporaryDirectory() as temp_dir:
-            event_log = eventlog.EventLogBuilder(event_log.as_uri(), temp_dir).build()
+            event_log_paths = extractor.Extractor(
+                event_log_path.resolve().as_uri(), temp_dir
+            ).extract()
+            event_log = eventlog.EventLogBuilder(event_log_paths, temp_dir).build()
 
             with open(event_log) as log_fobj:
                 event = json.loads(log_fobj.readline())

tests/test_eventlog_s3.py

@@ -10,7 +10,7 @@
 import pytest
 from botocore.stub import ANY, Stubber
 
-from spark_log_parser import eventlog
+from spark_log_parser import eventlog, extractor
 
 
 @pytest.mark.parametrize(
@@ -65,7 +65,8 @@ def test_emr_log_from_s3(event_log_url, event_log_file_archive, event_log_s3_dir
             chunk = fobj.read(chunk_size)
 
     with tempfile.TemporaryDirectory() as temp_dir, stubber:
-        event_log = eventlog.EventLogBuilder(event_log_url, temp_dir, s3).build()
+        event_log_paths = extractor.Extractor(event_log_url, temp_dir, s3).extract()
+        event_log = eventlog.EventLogBuilder(event_log_paths, temp_dir).build()
 
         with open(event_log) as log_fobj:
             event = json.loads(log_fobj.readline())
@@ -134,7 +135,8 @@ def test_databricks_log_from_s3_dir(event_log_url, event_log_file_archive, event
                         chunk = zobj.read(chunk_size)
 
         with stubber:
-            event_log = eventlog.EventLogBuilder(event_log_url, temp_dir, s3).build()
+            event_log_paths = extractor.Extractor(event_log_url, temp_dir, s3).extract()
+            event_log = eventlog.EventLogBuilder(event_log_paths, temp_dir).build()
 
         stubber.assert_no_pending_responses()
 

tests/test_parse.py

@@ -2,22 +2,30 @@
 import tempfile
 from pathlib import Path
 
-from spark_log_parser import eventlog
+from spark_log_parser import eventlog, extractor
 from spark_log_parser.parsing_models.application_model_v2 import sparkApplication
 
 
-def test_simple_databricks_log():
-    event_log_path = Path("tests", "logs", "databricks.zip").resolve()
+def get_parsed_log(event_log_path):
 
     with tempfile.TemporaryDirectory() as temp_dir:
-        event_log = eventlog.EventLogBuilder(event_log_path.as_uri(), temp_dir).build()
+        event_log_paths = extractor.Extractor(event_log_path.resolve().as_uri(), temp_dir).extract()
+        event_log = eventlog.EventLogBuilder(event_log_paths, temp_dir).build()
 
         result_path = str(Path(temp_dir, "result"))
         sparkApplication(eventlog=str(event_log)).save(result_path)
 
         with open(result_path + ".json") as result_fobj:
             parsed = json.load(result_fobj)
 
+    return parsed
+
+
+def test_simple_databricks_log():
+    event_log_path = Path("tests", "logs", "databricks.zip").resolve()
+
+    parsed = get_parsed_log(event_log_path)
+
     assert all(
         key in parsed
         for key in [
@@ -39,14 +47,7 @@ def test_simple_databricks_log():
 def test_simple_emr_log():
     event_log_path = Path("tests", "logs", "emr.zip").resolve()
 
-    with tempfile.TemporaryDirectory() as temp_dir:
-        event_log = eventlog.EventLogBuilder(event_log_path.as_uri(), temp_dir).build()
-
-        result_path = str(Path(temp_dir, "result"))
-        sparkApplication(eventlog=str(event_log)).save(result_path)
-
-        with open(str(result_path) + ".json") as result_fobj:
-            parsed = json.load(result_fobj)
+    parsed = get_parsed_log(event_log_path)
 
     assert all(
         key in parsed
@@ -70,7 +71,8 @@ def test_emr_missing_sql_events():
     event_log_path = Path("tests", "logs", "emr_missing_sql_events.zip").resolve()
 
     with tempfile.TemporaryDirectory() as temp_dir:
-        event_log = eventlog.EventLogBuilder(event_log_path.as_uri(), temp_dir).build()
+        event_log_paths = extractor.Extractor(event_log_path.resolve().as_uri(), temp_dir).extract()
+        event_log = eventlog.EventLogBuilder(event_log_paths, temp_dir).build()
         obj = sparkApplication(eventlog=str(event_log))
 
     assert list(obj.sqlData.index.values) == [0, 2, 3, 5, 6, 7, 8]