move updating into the dao fn

this helps manage the transaction by keeping it inside one function in the dao,
so after the function completes you know that the transaction has been released
and concurrent processing can resume

app/dao/jobs_dao.py

@@ -4,7 +4,7 @@ from sqlalchemy import func, desc, asc, cast, Date as sql_date
 
 from app import db
 from app.dao import days_ago
-from app.models import Job, NotificationHistory, JOB_STATUS_SCHEDULED
+from app.models import Job, NotificationHistory, JOB_STATUS_SCHEDULED, JOB_STATUS_PENDING
 from app.statsd_decorators import statsd
 
 
@@ -45,8 +45,15 @@ def dao_get_job_by_id(job_id):
     return Job.query.filter_by(id=job_id).one()
 
 
-def dao_get_scheduled_jobs():
-    return Job.query \
+def dao_set_scheduled_jobs_to_pending():
+    """
+    Sets all past scheduled jobs to pending, and then returns them for further processing.
+
+    this is used in the run_scheduled_jobs task, so we put a FOR UPDATE lock on the job table for the duration of
+    the transaction so that if the task is run more than once concurrently, one task will block the other select
+    from completing until it commits.
+    """
+    jobs = Job.query \
         .filter(
             Job.job_status == JOB_STATUS_SCHEDULED,
             Job.scheduled_for < datetime.utcnow()
@@ -55,6 +62,15 @@ def dao_get_scheduled_jobs():
         .with_for_update() \
         .all()
 
+    for job in jobs:
+        job.job_status = JOB_STATUS_PENDING
+
+    db.session.add_all(jobs)
+    db.session.commit()
+
+    return jobs
+
+
 
 def dao_get_future_scheduled_job_by_id_and_service_id(job_id, service_id):
     return Job.query \