def get_tier_preference()

in curator/helpers/getters.py [0:0]

• 23 lines of code
• 5 McCabe index (conditional complexity)

def get_tier_preference(client, target_tier='data_frozen'):
    """Do the tier preference thing in reverse order from coldest to hottest
    Based on the value of ``target_tier``, build out the list to use.

    :param client: A client connection object
    :param target_tier: The target data tier, e.g. data_warm.

    :type client: :py:class:`~.elasticsearch.Elasticsearch`
    :type target_tier: str

    :returns: A suitable tier preference string in csv format
    :rtype: str
    """
    tiermap = {
        'data_content': 0,
        'data_hot': 1,
        'data_warm': 2,
        'data_cold': 3,
        'data_frozen': 4,
    }
    tiers = get_data_tiers(client)
    test_list = []
    for tier in ['data_hot', 'data_warm', 'data_cold', 'data_frozen']:
        if tier in tiers and tiermap[tier] <= tiermap[target_tier]:
            test_list.insert(0, tier)
    if target_tier == 'data_frozen':
        # We're migrating to frozen here. If a frozen tier exists, frozen searchable
        # snapshot mounts should only ever go to the frozen tier.
        if 'data_frozen' in tiers and tiers['data_frozen']:
            return 'data_frozen'
    # If there are no  nodes with the 'data_frozen' role...
    preflist = []
    for key in test_list:
        # This ordering ensures that colder tiers are prioritized
        if key in tiers and tiers[key]:
            preflist.append(key)
    # If all of these are false, then we have no data tiers and must use 'data_content'
    if not preflist:
        return 'data_content'
    # This will join from coldest to hottest as csv string,
    # e.g. 'data_cold,data_warm,data_hot'
    return ','.join(preflist)