browbeat/lib/Elastic.py
jkilpatr c02a2890bf Bulk indexing of all elastic docs
This creates a general purpose Elastic object cache in the Browbeat
Elastic class. Every call to insert pushes into a cache which is then
emptied at the end of the workload run, when the cache max
size value is full or when more than a given amount of time has passed.
By default 1000 entires or 10 minutes. With a final flush being called
on the destruction of the Elasticsearch object. (even gets called on
sigterm so in theory you can ctrl-c and save your results)
It is emptied using a 4 parallel workers and the bulk api.
So it should be efficient at inserting large amounts of data.

If the upload of any one of the objects fails the rest will not be
inserted and the entire cache, included previously successful inserts
will be written to the disk. Possible improvement is to have the helper
return a list of pass/failed inserts and dump only those objects.

Change-Id: I0fceb5888c6f7d3167320593177d9cdc72504878
2017-06-27 07:36:16 -04:00

287 lines
12 KiB
Python

# 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.
from collections import deque
import elasticsearch
from elasticsearch import helpers
import logging
import json
import datetime
import uuid
import sys
import time
import os
import re
browbeat_uuid = uuid.uuid4()
class Elastic(object):
def __init__(self, config, workload, tool="browbeat", cache_size=1000, max_cache_time=10):
self.config = config
self.cache = deque()
self.max_cache_size = cache_size
self.last_upload = datetime.datetime.utcnow()
self.max_cache_age = datetime.timedelta(minutes=max_cache_time)
self.logger = logging.getLogger('browbeat.Elastic')
self.es = elasticsearch.Elasticsearch([
{'host': self.config['elasticsearch']['host'],
'port': self.config['elasticsearch']['port']}],
send_get_body_as='POST'
)
self.workload = workload
today = datetime.datetime.today()
self.index = "{}-{}-{}".format(tool,
workload, today.strftime('%Y.%m.%d'))
def __del__(self):
self.flush_cache()
def load_json(self, result):
json_data = None
self.logger.info("Loading JSON")
json_data = json.loads(result)
return json_data
def load_json_file(self, result):
json_data = None
self.logger.info("Loading JSON file : {}".format(result))
try:
with open(result) as jdata:
json_data = json.load(jdata)
except (IOError, OSError):
self.logger.error("Error loading JSON file : {}".format(result))
return False
return json_data
def combine_metadata(self, result):
if (self.config['elasticsearch']['metadata_files'] is not None and
len(self.config['elasticsearch']['metadata_files']) > 0):
meta = self.config['elasticsearch']['metadata_files']
for _meta in meta:
try:
with open(_meta['file']) as jdata:
result[_meta['name']] = json.load(jdata)
except Exception:
self.logger.error(
"Error loading Metadata file : {}".format(
_meta['file']))
self.logger.error(
"Please make sure the metadata file exists and"
" is valid JSON or run the playbook ansible/gather/site.yml"
" before running the Browbeat test Suite")
sys.exit(1)
return result
# Used to transform the cache dict into a elastic insertable iterable
def cache_insertable_iterable(self):
output = deque()
for item in self.cache:
es_item = {}
es_item['_id'] = item['_id']
es_item['_source'] = item['result']
es_item['_type'] = item['_type']
es_item['_index'] = self.index
output.append(es_item)
return output
def flush_cache(self):
if len(self.cache) == 0:
return True
retry = 2
for i in range(retry):
try:
to_upload = helpers.parallel_bulk(self.es,
self.cache_insertable_iterable())
counter = 0
num_items = len(self.cache)
for item in to_upload:
self.logger.debug("{} of {} Elastic objects uploaded".format(num_items,
counter))
output = "Pushed {} items to Elasticsearch to index {}".format(num_items,
self.index)
output += " and browbeat UUID {}".format(str(browbeat_uuid))
self.logger.info(output)
self.cache = deque()
self.last_upload = datetime.datetime.utcnow()
return True
except Exception as Err:
self.logger.error(
"Error pushing data to Elasticsearch, going to retry"
" in 10 seconds")
self.logger.error("Exception: {}".format(Err))
time.sleep(10)
if i == (retry-1):
self.logger.error("Pushing Data to Elasticsearch failed in spite of retry,"
" dumping JSON for {} cached items".format(len(self.cache)))
for item in self.cache:
filename = item['test_name'] + '-' + item['identifier']
filename += '-elastic' + '.' + 'json'
elastic_file = os.path.join(item['result_dir'],
filename)
with open(elastic_file, 'w') as result_file:
json.dump(item['result'],
result_file,
indent=4,
sort_keys=True)
self.logger.info("Saved Elasticsearch consumable result JSON to {}".
format(elastic_file))
self.cache = deque()
self.last_upload = datetime.datetime.utcnow()
return False
def get_software_metadata(self, index, role, browbeat_uuid):
nodes = {}
results = self.query_uuid(index, browbeat_uuid)
pattern = re.compile(".*{}.*".format(role))
if results:
for result in results:
for metadata in result['_source']['software-metadata']:
for service in metadata:
if pattern.match(metadata[service]['node_name']):
if metadata[service]['node_name'] not in nodes:
nodes[metadata[service][
'node_name']] = metadata
return nodes
else:
self.logger.error("UUID {} wasn't found".format(browbeat_uuid))
return False
"""
Currently this function will only compare two uuids. I (rook) am not convinced it is worth
the effort to engineer anything > 2.
"""
def compare_metadata(self, index, role, uuids):
meta = []
for browbeat_uuid in uuids:
self.logger.info(
"Querying Elastic : index [{}] : role [{}] : browbeat_uuid [{}] ".format(
index, role, browbeat_uuid))
software_metadata = self.get_software_metadata(index, role, browbeat_uuid)
if software_metadata:
meta.append(software_metadata)
else:
return False
ignore = [
"connection",
"admin_url",
"bind_host",
"rabbit_hosts",
"auth_url",
"public_bind_host",
"host",
"key",
"url",
"auth_uri",
"coordination_url",
"swift_authurl",
"admin_token",
"memcached_servers",
"api_servers",
"osapi_volume_listen",
"nova_url",
"coordination_url",
"memcache_servers",
"novncproxy_host",
"backend_url",
"novncproxy_base_url",
"metadata_listen",
"osapi_compute_listen",
"admin_bind_host",
"glance_api_servers",
"iscsi_ip_address",
"registry_host",
"auth_address",
"swift_key",
"auth_encryption_key",
"metadata_proxy_shared_secret",
"telemetry_secret",
"heat_metadata_server_url",
"heat_waitcondition_server_url",
"transport_url"]
if len(meta) < 2:
self.logger.error("Unable to compare data-sets")
return False
for host in meta[0]:
if host not in meta[1]:
self.logger.error("Deployment differs: "
"Host [{}] missing ".format(host))
continue
for service in meta[0][host]:
for options in meta[0][host][service].keys():
if options not in meta[1][host][service]:
self.logger.error(
"Missing Option : "
"Host [{}] Service [{}] {}".format(
host, service, options))
continue
if isinstance(meta[0][host][service][options], dict):
for key in meta[0][host][service][options].keys():
if key not in ignore:
if key in meta[1][host][service][options]:
value = meta[0][host][
service][options][key]
new_value = meta[1][host][
service][options][key]
if value != new_value:
self.logger.info(
"Difference found : "
"Host [{}] Service [{}] Section {} {} [{}]".format(
host,
service,
options,
key,
meta[0][host][service][options][key]))
else:
self.logger.info(
"Missing Value : "
"Host [{}] Service [{}] {} [{}]".format(
host, service, options, key))
def query_uuid(self, index, browbeat_uuid):
body = {'query': {"match": {"browbeat_uuid": {
"query": browbeat_uuid, "type": "phrase"}}}}
results = self.es.search(index=index, doc_type='result', body=body)
if len(results['hits']['hits']) > 0:
return results['hits']['hits']
else:
return False
def index_result(self,
result,
test_name,
result_dir,
identifier='',
_type='result',
_id=None):
data = {}
result['browbeat_uuid'] = str(browbeat_uuid)
result['cloud_name'] = self.config['browbeat']['cloud_name']
result['browbeat_config'] = self.config
data['result'] = result
data['test_name'] = test_name
data['result_dir'] = result_dir
data['identifier'] = identifier
data['_type'] = _type
data['_id'] = _id
self.cache.append(data)
now = datetime.datetime.utcnow()
if len(self.cache) <= self.max_cache_size \
and (now - self.last_upload) <= self.max_cache_age:
return True
else:
return self.flush_cache()