For xcoms pushed from different tasks, having the same execution_date and in the same Dag, the result of the xcom_pull with key set as None is not deterministic in its order

**Apache Airflow version**: 2.0


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`):

**Environment**:

- **Cloud provider or hardware configuration**:
- **OS** (e.g. from /etc/os-release):
- **Kernel** (e.g. `uname -a`):
- **Install tools**:
- **Others**:

**What happened**:
When tasks in the same dag push Xcoms, the result of the xcom_pull comes in any order. The order is not deterministic.

**What you expected to happen**:

I expected the order to be deterministic.

**How to reproduce it**:

Run the provided example_xcom dag in the repository multiple times


airflow/models/taskinstance.py
session=None,
    ) -> bool:
        """
        Checks dependencies and then sets state to RUNNING if they are met. Returns
        True if and only if state is set to RUNNING, which implies that task should be
        executed, in preparation for _run_raw_task
        :param verbose: whether to turn on more verbose logging
        :type verbose: bool
        :param ignore_all_deps: Ignore all of the non-critical dependencies, just runs
        :type ignore_all_deps: bool
        :param ignore_depends_on_past: Ignore depends_on_past DAG attribute
        :type ignore_depends_on_past: bool
        :param ignore_task_deps: Don't check the dependencies of this TaskInstance's task
        :type ignore_task_deps: bool
        :param ignore_ti_state: Disregards previous task instance state
        :type ignore_ti_state: bool
        :param mark_success: Don't run the task, mark its state as success
        :type mark_success: bool
        :param test_mode: Doesn't record success or failure in the DB
        :type test_mode: bool
        :param job_id: Job (BackfillJob / LocalTaskJob / SchedulerJob) ID
        :type job_id: str
        :param pool: specifies the pool to use to run the task instance
        :type pool: str
        :param session: SQLAlchemy ORM Session
        :type session: Session
        :return: whether the state was changed to running or not
        :rtype: bool
        """
        task = self.task