feat: add prepare_submit_job (no spark-submit invocation)

spark_executor/tools/submit.py

@@ -0,0 +1,57 @@
+# coding=utf-8
+"""
+@Time   :2026/6/24
+@Author :tao.chen
+"""
+import secrets
+from datetime import datetime
+
+from common.logging import logger
+from spark_executor.core.connection_store import store as conn_store
+from spark_executor.core.pending_store import store as pending_store
+from spark_executor.core.spark_submit import run_spark_submit  # re-exported for monkeypatch in tests
+from spark_executor.models import PendingSubmission
+
+
+def _new_pending_id() -> str:
+    return "p_" + secrets.token_hex(6)
+
+
+def prepare_submit_job(
+    *,
+    connection: str,
+    script_path: str,
+    queue: str = "default",
+    executor_memory: str = "4G",
+    executor_cores: int = 2,
+    num_executors: int = 2,
+) -> dict[str, object]:
+    """Snapshot connection params and persist a PendingSubmission. Does NOT submit."""
+    conn = conn_store.get(connection)
+    if conn is None:
+        raise KeyError(f"Unknown connection: {connection}")
+
+    pending_id = _new_pending_id()
+    pending = PendingSubmission(
+        pending_id=pending_id,
+        connection=connection,
+        master=conn.master,
+        deploy_mode=conn.deploy_mode,
+        script_path=script_path,
+        queue=queue,
+        executor_memory=executor_memory,
+        executor_cores=executor_cores,
+        num_executors=num_executors,
+        spark_conf=dict(conn.spark_conf),
+        created_at=datetime.utcnow(),
+        status="PENDING",
+    )
+    pending_store.save(pending)
+    logger.info(
+        f"prepare_submit_job pending_id={pending_id} connection={connection} master={conn.master}"
+    )
+    return {
+        "pending_id": pending_id,
+        "status": "PENDING",
+        "parameters": pending.model_dump(),
+    }