This file is indexed.

/usr/lib/python3/dist-packages/gnocchi/storage/redis.py is in python3-gnocchi 4.2.0-0ubuntu5.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
# -*- encoding: utf-8 -*-
#
# Copyright © 2017 Red Hat
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.

import six

from gnocchi.common import redis
from gnocchi import storage
from gnocchi import utils


class RedisStorage(storage.StorageDriver):
    WRITE_FULL = True

    STORAGE_PREFIX = b"timeseries"
    FIELD_SEP = '_'

    def __init__(self, conf, coord=None):
        super(RedisStorage, self).__init__(conf, coord)
        self._client = redis.get_client(conf)

    def __str__(self):
        return "%s: %s" % (self.__class__.__name__, self._client)

    def _metric_key(self, metric):
        return redis.SEP.join([self.STORAGE_PREFIX, str(metric.id).encode()])

    @staticmethod
    def _unaggregated_field(version=3):
        return 'none' + ("_v%s" % version if version else "")

    @classmethod
    def _aggregated_field_for_split(cls, aggregation, key, version=3,
                                    granularity=None):
        path = cls.FIELD_SEP.join([
            str(key), aggregation,
            str(utils.timespan_total_seconds(granularity or key.sampling))])
        return path + '_v%s' % version if version else path

    def _create_metric(self, metric):
        key = self._metric_key(metric)
        if self._client.exists(key):
            raise storage.MetricAlreadyExists(metric)
        self._client.hset(key, self._unaggregated_field(), '')

    def _store_unaggregated_timeserie(self, metric, data, version=3):
        self._client.hset(self._metric_key(metric),
                          self._unaggregated_field(version), data)

    def _get_unaggregated_timeserie(self, metric, version=3):
        data = self._client.hget(self._metric_key(metric),
                                 self._unaggregated_field(version))
        if data is None:
            raise storage.MetricDoesNotExist(metric)
        return data

    def _list_split_keys(self, metric, aggregation, granularity, version=3):
        key = self._metric_key(metric)
        split_keys = set()
        hashes = self._client.hscan_iter(
            key, match=self._aggregated_field_for_split(
                aggregation, '*', version, granularity))
        for f, __ in hashes:
            meta = f.decode("utf8").split(self.FIELD_SEP, 1)
            split_keys.add(meta[0])
        if not split_keys and not self._client.exists(key):
            raise storage.MetricDoesNotExist(metric)
        return split_keys

    def _delete_metric_measures(self, metric, key, aggregation, version=3):
        field = self._aggregated_field_for_split(aggregation, key, version)
        self._client.hdel(self._metric_key(metric), field)

    def _store_metric_measures(self, metric, key, aggregation,
                               data, offset=None, version=3):
        field = self._aggregated_field_for_split(
            aggregation, key, version)
        self._client.hset(self._metric_key(metric), field, data)

    def _delete_metric(self, metric):
        self._client.delete(self._metric_key(metric))

    def _get_measures(self, metric, keys, aggregation, version=3):
        if not keys:
            return []
        redis_key = self._metric_key(metric)
        fields = [
            self._aggregated_field_for_split(aggregation, key, version)
            for key in keys
        ]
        results = self._client.hmget(redis_key, fields)
        for key, data in six.moves.zip(keys, results):
            if data is None:
                if not self._client.exists(redis_key):
                    raise storage.MetricDoesNotExist(metric)
                raise storage.AggregationDoesNotExist(
                    metric, aggregation, key.sampling)
        return results