feat: structured DEBUG/INFO logging via loguru

- common/logging.py: improve format to timestamp|LEVEL|module:func:line - message
- core/ layer: DEBUG log every subprocess invocation (cmd, rc, byte counts),
  JSON load/dump events, parsed application_id. ERROR log on failures.
- tools/ layer: DEBUG log every public tool entry with key parameters,
  INFO log on business outcomes (saved/submitted/killed/...).
- New tests/unit/test_logging.py: capture loguru output via in-memory sink
  and assert DEBUG + INFO messages are emitted for representative flows.

spark_executor/core/spark_submit.py

@@ -5,6 +5,8 @@
 """
 import subprocess
 
+from common.logging import logger
+
 
 class SparkSubmitError(Exception):
     """Raised when spark-submit exits with a non-zero return code."""
@@ -33,12 +35,19 @@ def build_spark_submit_command(
     for key, value in (spark_conf or {}).items():
         cmd.extend(["--conf", f"{key}={value}"])
     cmd.append(script_path)
+    logger.debug(f"build_spark_submit_command -> {cmd}")
     return cmd
 
 
 def run_spark_submit(cmd: list[str]) -> "subprocess.CompletedProcess[str]":
+    logger.debug(f"run_spark_submit exec: {cmd}")
     result = subprocess.run(cmd, capture_output=True, text=True, errors="replace")
+    logger.debug(
+        f"run_spark_submit done rc={result.returncode} "
+        f"stdout_len={len(result.stdout)} stderr_len={len(result.stderr)}"
+    )
     if result.returncode != 0:
+        logger.error(f"spark-submit failed (rc={result.returncode}): {result.stderr[:500]}")
         raise SparkSubmitError(
             f"spark-submit failed (rc={result.returncode}): {result.stderr}"
         )