514 lines
20 KiB
Python
514 lines
20 KiB
Python
# This Source Code Form is subject to the terms of the Mozilla Public
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# License, v. 2.0. If a copy of the MPL was not distributed with this
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# file, You can obtain one at http://mozilla.org/MPL/2.0/.
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import collections
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import itertools
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import json
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import math
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import os
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import re
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import sys
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# Constants.
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MAX_LABEL_LENGTH = 20
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MAX_LABEL_COUNT = 100
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# histogram_tools.py is used by scripts from a mozilla-central build tree
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# and also by outside consumers, such as the telemetry server. We need
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# to ensure that importing things works in both contexts. Therefore,
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# unconditionally importing things that are local to the build tree, such
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# as buildconfig, is a no-no.
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try:
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import buildconfig
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# Need to update sys.path to be able to find usecounters.
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sys.path.append(os.path.join(buildconfig.topsrcdir, 'dom/base/'))
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except ImportError:
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# Must be in an out-of-tree usage scenario. Trust that whoever is
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# running this script knows we need the usecounters module and has
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# ensured it's in our sys.path.
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pass
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from collections import OrderedDict
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def table_dispatch(kind, table, body):
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"""Call body with table[kind] if it exists. Raise an error otherwise."""
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if kind in table:
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return body(table[kind])
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else:
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raise BaseException, "don't know how to handle a histogram of kind %s" % kind
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class DefinitionException(BaseException):
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pass
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def linear_buckets(dmin, dmax, n_buckets):
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ret_array = [0] * n_buckets
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dmin = float(dmin)
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dmax = float(dmax)
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for i in range(1, n_buckets):
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linear_range = (dmin * (n_buckets - 1 - i) + dmax * (i - 1)) / (n_buckets - 2)
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ret_array[i] = int(linear_range + 0.5)
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return ret_array
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def exponential_buckets(dmin, dmax, n_buckets):
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log_max = math.log(dmax);
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bucket_index = 2;
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ret_array = [0] * n_buckets
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current = dmin
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ret_array[1] = current
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for bucket_index in range(2, n_buckets):
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log_current = math.log(current)
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log_ratio = (log_max - log_current) / (n_buckets - bucket_index)
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log_next = log_current + log_ratio
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next_value = int(math.floor(math.exp(log_next) + 0.5))
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if next_value > current:
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current = next_value
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else:
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current = current + 1
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ret_array[bucket_index] = current
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return ret_array
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always_allowed_keys = ['kind', 'description', 'cpp_guard', 'expires_in_version',
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'alert_emails', 'keyed', 'releaseChannelCollection',
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'bug_numbers']
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whitelists = None;
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try:
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whitelist_path = os.path.join(os.path.abspath(os.path.realpath(os.path.dirname(__file__))), 'histogram-whitelists.json')
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with open(whitelist_path, 'r') as f:
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try:
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whitelists = json.load(f)
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for name, whitelist in whitelists.iteritems():
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whitelists[name] = set(whitelist)
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except ValueError, e:
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raise BaseException, 'error parsing whitelist (%s)' % whitelist_path
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except IOError:
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whitelists = None
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print 'Unable to parse whitelist (%s). Assuming all histograms are acceptable.' % whitelist_path
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class Histogram:
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"""A class for representing a histogram definition."""
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def __init__(self, name, definition, strict_type_checks=False):
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"""Initialize a histogram named name with the given definition.
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definition is a dict-like object that must contain at least the keys:
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- 'kind': The kind of histogram. Must be one of 'boolean', 'flag',
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'count', 'enumerated', 'linear', or 'exponential'.
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- 'description': A textual description of the histogram.
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- 'strict_type_checks': A boolean indicating whether to use the new, stricter type checks.
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The server-side still has to deal with old, oddly typed submissions,
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so we have to skip them there by default.
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The key 'cpp_guard' is optional; if present, it denotes a preprocessor
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symbol that should guard C/C++ definitions associated with the histogram."""
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self._strict_type_checks = strict_type_checks
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self._is_use_counter = name.startswith("USE_COUNTER2_")
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self.verify_attributes(name, definition)
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self._name = name
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self._description = definition['description']
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self._kind = definition['kind']
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self._cpp_guard = definition.get('cpp_guard')
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self._keyed = definition.get('keyed', False)
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self._expiration = definition.get('expires_in_version')
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self._labels = definition.get('labels', [])
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self.compute_bucket_parameters(definition)
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table = {
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'boolean': 'BOOLEAN',
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'flag': 'FLAG',
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'count': 'COUNT',
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'enumerated': 'LINEAR',
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'categorical': 'CATEGORICAL',
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'linear': 'LINEAR',
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'exponential': 'EXPONENTIAL',
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}
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table_dispatch(self.kind(), table,
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lambda k: self._set_nsITelemetry_kind(k))
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datasets = { 'opt-in': 'DATASET_RELEASE_CHANNEL_OPTIN',
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'opt-out': 'DATASET_RELEASE_CHANNEL_OPTOUT' }
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value = definition.get('releaseChannelCollection', 'opt-in')
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if not value in datasets:
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raise DefinitionException, "unknown release channel collection policy for " + name
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self._dataset = "nsITelemetry::" + datasets[value]
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def name(self):
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"""Return the name of the histogram."""
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return self._name
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def description(self):
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"""Return the description of the histogram."""
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return self._description
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def kind(self):
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"""Return the kind of the histogram.
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Will be one of 'boolean', 'flag', 'count', 'enumerated', 'categorical', 'linear',
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or 'exponential'."""
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return self._kind
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def expiration(self):
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"""Return the expiration version of the histogram."""
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return self._expiration
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def nsITelemetry_kind(self):
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"""Return the nsITelemetry constant corresponding to the kind of
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the histogram."""
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return self._nsITelemetry_kind
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def _set_nsITelemetry_kind(self, kind):
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self._nsITelemetry_kind = "nsITelemetry::HISTOGRAM_%s" % kind
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def low(self):
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"""Return the lower bound of the histogram."""
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return self._low
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def high(self):
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"""Return the high bound of the histogram."""
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return self._high
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def n_buckets(self):
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"""Return the number of buckets in the histogram."""
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return self._n_buckets
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def cpp_guard(self):
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"""Return the preprocessor symbol that should guard C/C++ definitions
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associated with the histogram. Returns None if no guarding is necessary."""
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return self._cpp_guard
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def keyed(self):
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"""Returns True if this a keyed histogram, false otherwise."""
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return self._keyed
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def dataset(self):
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"""Returns the dataset this histogram belongs into."""
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return self._dataset
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def labels(self):
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"""Returns a list of labels for a categorical histogram, [] for others."""
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return self._labels
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def ranges(self):
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"""Return an array of lower bounds for each bucket in the histogram."""
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table = {
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'boolean': linear_buckets,
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'flag': linear_buckets,
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'count': linear_buckets,
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'enumerated': linear_buckets,
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'categorical': linear_buckets,
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'linear': linear_buckets,
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'exponential': exponential_buckets,
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}
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return table_dispatch(self.kind(), table,
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lambda p: p(self.low(), self.high(), self.n_buckets()))
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def compute_bucket_parameters(self, definition):
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table = {
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'boolean': Histogram.boolean_flag_bucket_parameters,
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'flag': Histogram.boolean_flag_bucket_parameters,
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'count': Histogram.boolean_flag_bucket_parameters,
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'enumerated': Histogram.enumerated_bucket_parameters,
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'categorical': Histogram.categorical_bucket_parameters,
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'linear': Histogram.linear_bucket_parameters,
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'exponential': Histogram.exponential_bucket_parameters,
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}
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table_dispatch(self.kind(), table,
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lambda p: self.set_bucket_parameters(*p(definition)))
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def verify_attributes(self, name, definition):
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global always_allowed_keys
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general_keys = always_allowed_keys + ['low', 'high', 'n_buckets']
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table = {
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'boolean': always_allowed_keys,
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'flag': always_allowed_keys,
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'count': always_allowed_keys,
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'enumerated': always_allowed_keys + ['n_values'],
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'categorical': always_allowed_keys + ['labels'],
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'linear': general_keys,
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'exponential': general_keys,
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}
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# We removed extended_statistics_ok on the client, but the server-side,
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# where _strict_type_checks==False, has to deal with historical data.
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if not self._strict_type_checks:
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table['exponential'].append('extended_statistics_ok')
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table_dispatch(definition['kind'], table,
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lambda allowed_keys: Histogram.check_keys(name, definition, allowed_keys))
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self.check_name(name)
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self.check_field_types(name, definition)
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self.check_whitelistable_fields(name, definition)
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self.check_expiration(name, definition)
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self.check_label_values(name, definition)
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def check_name(self, name):
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if '#' in name:
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raise ValueError, '"#" not permitted for %s' % (name)
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# Avoid C++ identifier conflicts between histogram enums and label enum names.
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if name.startswith("LABELS_"):
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raise ValueError, "Histogram name '%s' can not start with LABELS_" % (name)
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# To make it easier to generate C++ identifiers from this etc., we restrict
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# the histogram names to a strict pattern.
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# We skip this on the server to avoid failures with old Histogram.json revisions.
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if self._strict_type_checks:
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pattern = '^[a-z][a-z0-9_]+[a-z0-9]$'
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if not re.match(pattern, name, re.IGNORECASE):
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raise ValueError, "Histogram name '%s' doesn't confirm to '%s'" % (name, pattern)
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def check_expiration(self, name, definition):
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field = 'expires_in_version'
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expiration = definition.get(field)
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if not expiration:
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return
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# We forbid new probes from using "expires_in_version" : "default" field/value pair.
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# Old ones that use this are added to the whitelist.
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if expiration == "default" and name not in whitelists['expiry_default']:
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raise ValueError, 'New histogram "%s" cannot have "default" %s value.' % (name, field)
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if re.match(r'^[1-9][0-9]*$', expiration):
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expiration = expiration + ".0a1"
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elif re.match(r'^[1-9][0-9]*\.0$', expiration):
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expiration = expiration + "a1"
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definition[field] = expiration
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def check_label_values(self, name, definition):
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labels = definition.get('labels')
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if not labels:
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return
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invalid = filter(lambda l: len(l) > MAX_LABEL_LENGTH, labels)
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if len(invalid) > 0:
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raise ValueError, 'Label values for %s exceed length limit of %d: %s' % \
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(name, MAX_LABEL_LENGTH, ', '.join(invalid))
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if len(labels) > MAX_LABEL_COUNT:
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raise ValueError, 'Label count for %s exceeds limit of %d' % \
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(name, MAX_LABEL_COUNT)
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# To make it easier to generate C++ identifiers from this etc., we restrict
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# the label values to a strict pattern.
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pattern = '^[a-z][a-z0-9_]+[a-z0-9]$'
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invalid = filter(lambda l: not re.match(pattern, l, re.IGNORECASE), labels)
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if len(invalid) > 0:
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raise ValueError, 'Label values for %s are not matching pattern "%s": %s' % \
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(name, pattern, ', '.join(invalid))
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# Check for the presence of fields that old histograms are whitelisted for.
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def check_whitelistable_fields(self, name, definition):
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# Use counters don't have any mechanism to add the fields checked here,
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# so skip the check for them.
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# We also don't need to run any of these checks on the server.
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if self._is_use_counter or not self._strict_type_checks:
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return
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# In the pipeline we don't have whitelists available.
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if whitelists is None:
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return
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for field in ['alert_emails', 'bug_numbers']:
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if field not in definition and name not in whitelists[field]:
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raise KeyError, 'New histogram "%s" must have a %s field.' % (name, field)
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if field in definition and name in whitelists[field]:
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msg = 'Should remove histogram "%s" from the whitelist for "%s" in histogram-whitelists.json'
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raise KeyError, msg % (name, field)
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def check_field_types(self, name, definition):
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# Define expected types for the histogram properties.
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type_checked_fields = {
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"n_buckets": int,
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"n_values": int,
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"low": int,
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"high": int,
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"keyed": bool,
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"expires_in_version": basestring,
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"kind": basestring,
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"description": basestring,
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"cpp_guard": basestring,
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"releaseChannelCollection": basestring,
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}
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# For list fields we check the items types.
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type_checked_list_fields = {
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"bug_numbers": int,
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"alert_emails": basestring,
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"labels": basestring,
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}
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# For the server-side, where _strict_type_checks==False, we want to
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# skip the stricter type checks for these fields for dealing with
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# historical data.
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coerce_fields = ["low", "high", "n_values", "n_buckets"]
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if not self._strict_type_checks:
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def try_to_coerce_to_number(v):
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try:
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return eval(v, {})
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except:
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return v
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for key in [k for k in coerce_fields if k in definition]:
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definition[key] = try_to_coerce_to_number(definition[key])
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# This handles old "keyed":"true" definitions (bug 1271986).
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if definition.get("keyed", None) == "true":
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definition["keyed"] = True
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def nice_type_name(t):
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if t is basestring:
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return "string"
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return t.__name__
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for key, key_type in type_checked_fields.iteritems():
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if not key in definition:
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continue
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if not isinstance(definition[key], key_type):
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raise ValueError, ('value for key "{0}" in Histogram "{1}" '
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'should be {2}').format(key, name, nice_type_name(key_type))
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for key, key_type in type_checked_list_fields.iteritems():
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if not key in definition:
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continue
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if not all(isinstance(x, key_type) for x in definition[key]):
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raise ValueError, ('all values for list "{0}" in Histogram "{1}" '
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'should be {2}').format(key, name, nice_type_name(key_type))
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@staticmethod
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def check_keys(name, definition, allowed_keys):
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for key in definition.iterkeys():
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if key not in allowed_keys:
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raise KeyError, '%s not permitted for %s' % (key, name)
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def set_bucket_parameters(self, low, high, n_buckets):
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self._low = low
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self._high = high
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self._n_buckets = n_buckets
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if whitelists is not None and self._n_buckets > 100 and type(self._n_buckets) is int:
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if self._name not in whitelists['n_buckets']:
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raise KeyError, ('New histogram "%s" is not permitted to have more than 100 buckets. '
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'Histograms with large numbers of buckets use disproportionately high amounts of resources. '
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'Contact the Telemetry team (e.g. in #telemetry) if you think an exception ought to be made.' % self._name)
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@staticmethod
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def boolean_flag_bucket_parameters(definition):
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return (1, 2, 3)
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@staticmethod
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def linear_bucket_parameters(definition):
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return (definition.get('low', 1),
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definition['high'],
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definition['n_buckets'])
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@staticmethod
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def enumerated_bucket_parameters(definition):
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n_values = definition['n_values']
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return (1, n_values, n_values + 1)
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@staticmethod
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def categorical_bucket_parameters(definition):
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n_values = len(definition['labels'])
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return (1, n_values, n_values + 1)
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@staticmethod
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def exponential_bucket_parameters(definition):
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return (definition.get('low', 1),
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definition['high'],
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definition['n_buckets'])
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# We support generating histograms from multiple different input files, not
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# just Histograms.json. For each file's basename, we have a specific
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# routine to parse that file, and return a dictionary mapping histogram
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# names to histogram parameters.
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def from_Histograms_json(filename):
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with open(filename, 'r') as f:
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try:
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histograms = json.load(f, object_pairs_hook=OrderedDict)
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except ValueError, e:
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raise BaseException, "error parsing histograms in %s: %s" % (filename, e.message)
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return histograms
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def from_UseCounters_conf(filename):
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return usecounters.generate_histograms(filename)
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def from_nsDeprecatedOperationList(filename):
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operation_regex = re.compile('^DEPRECATED_OPERATION\\(([^)]+)\\)')
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histograms = collections.OrderedDict()
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with open(filename, 'r') as f:
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for line in f:
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match = operation_regex.search(line)
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if not match:
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continue
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op = match.group(1)
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def add_counter(context):
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name = 'USE_COUNTER2_DEPRECATED_%s_%s' % (op, context.upper())
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histograms[name] = {
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'expires_in_version': 'never',
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'kind': 'boolean',
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'description': 'Whether a %s used %s' % (context, op)
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}
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add_counter('document')
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add_counter('page')
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return histograms
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FILENAME_PARSERS = {
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'Histograms.json': from_Histograms_json,
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'nsDeprecatedOperationList.h': from_nsDeprecatedOperationList,
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}
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# Similarly to the dance above with buildconfig, usecounters may not be
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# available, so handle that gracefully.
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try:
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import usecounters
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FILENAME_PARSERS['UseCounters.conf'] = from_UseCounters_conf
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except ImportError:
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pass
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def from_files(filenames):
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"""Return an iterator that provides a sequence of Histograms for
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the histograms defined in filenames.
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"""
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all_histograms = OrderedDict()
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for filename in filenames:
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parser = FILENAME_PARSERS[os.path.basename(filename)]
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histograms = parser(filename)
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# OrderedDicts are important, because then the iteration order over
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# the parsed histograms is stable, which makes the insertion into
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# all_histograms stable, which makes ordering in generated files
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# stable, which makes builds more deterministic.
|
|
if not isinstance(histograms, OrderedDict):
|
|
raise BaseException, "histogram parser didn't provide an OrderedDict"
|
|
|
|
for (name, definition) in histograms.iteritems():
|
|
if all_histograms.has_key(name):
|
|
raise DefinitionException, "duplicate histogram name %s" % name
|
|
all_histograms[name] = definition
|
|
|
|
# We require that all USE_COUNTER2_* histograms be defined in a contiguous
|
|
# block.
|
|
use_counter_indices = filter(lambda x: x[1].startswith("USE_COUNTER2_"),
|
|
enumerate(all_histograms.iterkeys()));
|
|
if use_counter_indices:
|
|
lower_bound = use_counter_indices[0][0]
|
|
upper_bound = use_counter_indices[-1][0]
|
|
n_counters = upper_bound - lower_bound + 1
|
|
if n_counters != len(use_counter_indices):
|
|
raise DefinitionException, "use counter histograms must be defined in a contiguous block"
|
|
|
|
# Check that histograms that were removed from Histograms.json etc. are also removed from the whitelists.
|
|
if whitelists is not None:
|
|
all_whitelist_entries = itertools.chain.from_iterable(whitelists.itervalues())
|
|
orphaned = set(all_whitelist_entries) - set(all_histograms.keys())
|
|
if len(orphaned) > 0:
|
|
msg = 'The following entries are orphaned and should be removed from histogram-whitelists.json: %s'
|
|
raise BaseException, msg % (', '.join(sorted(orphaned)))
|
|
|
|
for (name, definition) in all_histograms.iteritems():
|
|
yield Histogram(name, definition, strict_type_checks=True)
|