def METHOD_NAME(session):
    """
    If the targeted database contains any metric entries, this function emits important,
    database-specific information about the ``create_latest_metrics_table`` migration.
    If the targeted database does *not* contain any metric entries, this output is omitted
    in order to avoid superfluous log output when initializing a new Tracking database.
    """
    num_metric_entries = session.query(SqlMetric).count()
    if num_metric_entries <= 0:
        return
    _logger.warning(
        "**IMPORTANT**: This migration creates a `latest_metrics` table and populates it with the"
        " latest metric entry for each unique (run_id, metric_key) tuple. Latest metric entries are"
        " computed based on step, timestamp, and value. This migration may take a long time for"
        " databases containing a large number of metric entries. Please refer to {readme_link} for"
        " information about this migration, including how to estimate migration size and how to"
        " restore your database to its original state if the migration is unsuccessful. If you"
        " encounter failures while executing this migration, please file a GitHub issue at"
        " {issues_link}.".format(
            readme_link=(
                "https://github.com/mlflow/mlflow/blob/master/mlflow/store/db_migrations/README.md"
                "#89d4b8295536_create_latest_metrics_table"
            ),
            issues_link="https://github.com/mlflow/mlflow/issues",
        )
    )
    num_metric_keys = (
        session.query(SqlMetric.run_uuid, SqlMetric.key)
        .group_by(SqlMetric.run_uuid, SqlMetric.key)
        .count()
    )
    num_runs_containing_metrics = session.query(distinct(SqlMetric.run_uuid)).count()
    _logger.info(
        "This tracking database has {num_metric_entries} total metric entries for {num_metric_keys}"
        " unique metrics across {num_runs} runs.".format(
            num_metric_entries=num_metric_entries,
            num_metric_keys=num_metric_keys,
            num_runs=num_runs_containing_metrics,
        )
    )