d2379a018e
*Merge monasca-log-api into merge-api *Enable logs endpoints *Add configuration that allow to enable/disable metrics and logs part *Remove redundant log-api source code Story: 2003881 Task: 30533 Change-Id: Iaa5689694e7081f3375f1a2235cad31d6a7b5f76
135 lines
4.5 KiB
Python
135 lines
4.5 KiB
Python
# Copyright 2016 FUJITSU LIMITED
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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from oslo_log import log
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from monasca_api.api.core.log import log_publisher
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from monasca_api.api.core.log import model
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from monasca_api.api.core.log import validation
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from monasca_api import conf
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LOG = log.getLogger(__name__)
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CONF = conf.CONF
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class BulkProcessor(log_publisher.LogPublisher):
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"""BulkProcessor for effective log processing and publishing.
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BulkProcessor is customized version of
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:py:class:`monasca_log_api.app.base.log_publisher.LogPublisher`
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that utilizes processing of bulk request inside single loop.
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"""
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def __init__(self, logs_in_counter=None, logs_rejected_counter=None):
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"""Initializes BulkProcessor.
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:param logs_in_counter: V2 received logs counter
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:param logs_rejected_counter: V2 rejected logs counter
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"""
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super(BulkProcessor, self).__init__()
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self.service_region = CONF.region
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def send_message(self, logs, global_dimensions=None, log_tenant_id=None):
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"""Sends bulk package to kafka
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:param list logs: received logs
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:param dict global_dimensions: global dimensions for each log
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:param str log_tenant_id: tenant who sent logs
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"""
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num_of_msgs = len(logs) if logs else 0
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to_send_msgs = []
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LOG.debug('Bulk package <logs=%d, dimensions=%s, tenant_id=%s>',
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num_of_msgs, global_dimensions, log_tenant_id)
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try:
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for log_el in logs:
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t_el = self._transform_message(log_el,
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global_dimensions,
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log_tenant_id)
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if t_el:
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to_send_msgs.append(t_el)
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self._publish(to_send_msgs)
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except Exception as ex:
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LOG.error('Failed to send bulk package <logs=%d, dimensions=%s>',
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num_of_msgs, global_dimensions)
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LOG.exception(ex)
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def _transform_message(self, log_element, *args):
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try:
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validation.validate_log_message(log_element)
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log_envelope = model.Envelope.new_envelope(
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log=log_element,
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tenant_id=args[1],
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region=self.service_region,
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dimensions=self._get_dimensions(log_element,
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global_dims=args[0])
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)
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msg_payload = (super(BulkProcessor, self)
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._transform_message(log_envelope))
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return msg_payload
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except Exception as ex:
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LOG.error('Log transformation failed, rejecting log')
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LOG.exception(ex)
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return None
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def _create_envelope(self, log_element, tenant_id, dimensions=None):
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"""Create a log envelope.
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:param dict log_element: raw log element
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:param str tenant_id: tenant who sent logs
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:param dict dimensions: log dimensions
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:return: log envelope
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:rtype: model.Envelope
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"""
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return
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def _get_dimensions(self, log_element, global_dims=None):
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"""Get the dimensions of log element.
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If global dimensions are specified and passed to this method,
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both instances are merged with each other.
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If neither is specified empty dictionary is returned.
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If only local dimensions are specified they are returned without any
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additional operations. The last statement applies also
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to global dimensions.
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:param dict log_element: raw log instance
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:param dict global_dims: global dimensions or None
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:return: local dimensions merged with global dimensions
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:rtype: dict
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"""
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local_dims = log_element.get('dimensions', {})
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if not global_dims:
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global_dims = {}
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if local_dims:
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validation.validate_dimensions(local_dims)
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dimensions = global_dims.copy()
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dimensions.update(local_dims)
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return dimensions
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