feat: add ES slicing to CLI

benchmarks/cli.py

@@ -155,24 +155,25 @@ def _parse_config(
             sys.exit(-1)
 
 
-def _configure_source(args, dump=False):
-    # TODO we should probably have builders for sources as well, but for now
-    #   we'll just keep it simple.
-    if args.source_file:
-        if not args.source_file.exists():
-            print(f"Log source file {args.source_file} does not exist.")
-            sys.exit(-1)
-        return VectorFlatFileSource(
-            app_name="codex-benchmarks", file=args.source_file.open(encoding="utf-8")
-        )
-    else:
+def _configure_logstash_source(args, structured_only=True):
     import urllib3
 
     urllib3.disable_warnings()
 
     return LogstashSource(
         Elasticsearch(args.es_url, verify_certs=False),
-            structured_only=not dump,
+        chronological=args.chronological,
+        structured_only=structured_only,
+        slices=args.slices,
+    )
+
+
+def _configure_vector_source(args):
+    if not args.source_file.exists():
+        print(f"Log source file {args.source_file} does not exist.")
+        sys.exit(-1)
+    return VectorFlatFileSource(
+        app_name="codex-benchmarks", file=args.source_file.open(encoding="utf-8")
     )
 
 
@@ -186,10 +187,15 @@ def _init_logging():
 
 
 def main():
+    # TODO this is getting unwieldy, need pull this apart into submodules. For now we get away
+    #   with title comments.
     parser = argparse.ArgumentParser()
 
     commands = parser.add_subparsers(required=True)
 
+    ###########################################################################
+    #                              Experiments                                #
+    ###########################################################################
     experiments = commands.add_parser(
         "experiments", help="List or run experiments in config file."
     )
@@ -226,6 +232,9 @@ def main():
 
     describe_cmd.set_defaults(func=cmd_describe_experiment)
 
+    ###########################################################################
+    #                              Logs                                       #
+    ###########################################################################
     logs_cmd = commands.add_parser("logs", help="Parse logs.")
     log_subcommands = logs_cmd.add_subparsers(required=True)
 
@@ -243,15 +252,6 @@ def main():
     log_source_cmd = log_subcommands.add_parser(
         "source", help="Parse logs from a log source."
     )
-
-    source_group = log_source_cmd.add_mutually_exclusive_group(required=True)
-    source_group.add_argument(
-        "--source-file", type=Path, help="Vector log file to parse from."
-    )
-    source_group.add_argument(
-        "--es-url", type=str, help="URL to a logstash Elasticsearch instance."
-    )
-
     log_source_cmd.add_argument(
         "group_id", type=str, help="ID of experiment group to parse."
     )
@@ -267,16 +267,48 @@ def main():
         type=Path,
         help="Splits logs for the entire group into the specified folder.",
     )
-    log_source_cmd.set_defaults(
-        func=lambda args: cmd_split_log_source(
-            _configure_source(args, dump=False), args.group_id, args.output_dir
+
+    single_or_split.set_defaults(
+        func=lambda args: cmd_dump_single_experiment(
+            args.source(args, False), args.group_id, args.experiment_id
         )
-        if args.output_dir
-        else cmd_dump_single_experiment(
-            _configure_source(args, dump=True), args.group_id, args.experiment_id
+        if args.experiment_id
+        else cmd_split_log_source(
+            args.source(args, True), args.group_id, args.output_dir
         )
     )
 
+    source_type = log_source_cmd.add_subparsers(required=True)
+    es_source = source_type.add_parser("logstash", help="Logstash source.")
+    es_source.add_argument(
+        "es_url", type=str, help="URL to a logstash Elasticsearch instance."
+    )
+    es_source.add_argument(
+        "--chronological", action="store_true", help="Sort logs chronologically."
+    )
+    es_source.add_argument(
+        "--slices",
+        type=int,
+        help="Number of scroll slices to use when reading the log.",
+        default=2,
+    )
+
+    es_source.set_defaults(
+        source=lambda args, structured_only: _configure_logstash_source(
+            args, structured_only=structured_only
+        )
+    )
+
+    vector_source = source_type.add_parser("vector", help="Vector flat file source.")
+    vector_source.add_argument(
+        "source_file", type=Path, help="Vector log file to parse from."
+    )
+
+    vector_source.set_defaults(source=lambda args, _: _configure_vector_source(args))
+
+    ###########################################################################
+    #                              Agents                                     #
+    ###########################################################################
     agent_cmd = commands.add_parser("agent", help="Starts a local agent.")
     agent_cmd.add_argument(
         "config", type=Path, help="Path to the agent configuration file."

benchmarks/core/concurrency.py

@@ -34,6 +34,7 @@ def pflatmap(
         finally:
             q.put(_End())
 
+    # TODO handle SIGTERM properly
     executor = ThreadPoolExecutor(max_workers=workers)
     try:
         task_futures = [executor.submit(_consume, task) for task in tasks]

benchmarks/logging/sources/logstash.py

@@ -102,6 +102,7 @@ class LogstashSource(LogSource):
         ]
 
         if self.slices > 1:
+            logger.info(f"Querying ES with {self.slices} scroll slices.")
             yield from pflatmap(
                 [
                     self._run_scroll(sliced_query, actual_indexes)
@@ -153,8 +154,11 @@ class LogstashSource(LogSource):
 
                 # Get next batch of results
                 scroll_response = self.client.scroll(scroll_id=scroll_id, scroll="2m")
+        except Exception as e:
+            logger.exception(f"Error while scrolling: {e}")
         finally:
             # Clean up scroll context
+            logger.info("Worker done, clearing scroll context.")
             self.client.clear_scroll(scroll_id=scroll_id)
 
     def __str__(self):