def test_over_threshold(self):
queue = BulkQueue(self.es_client, flush_time=3, threshold=10)
queue.start_timer()
for num in range(0, 201):
queue.add(index='events', doc_type='event', body={'keyname': 'value' + str(num)})
assert self.num_objects_saved() == 200
assert queue.size() == 1
time.sleep(4)
assert self.num_objects_saved() == 201
assert queue.size() == 0
queue.stop_timer()
def test_basic_timer(self):
queue = BulkQueue(self.es_client, flush_time=2)
assert queue.started() is False
queue.start_timer()
assert queue.started() is True
queue.add(index='events', doc_type='event', body={'keyname': 'valuename'})
assert queue.size() == 1
time.sleep(3)
assert queue.size() == 0
queue.stop_timer()
assert queue.started() is False
def test_ten_iterations(self):
queue = BulkQueue(self.es_client, flush_time=3, threshold=10)
queue.start_timer()
total_events = 0
for num_rounds in range(0, 10):
for num in range(0, 20):
total_events += 1
queue.add(index='events', doc_type='event', body={'keyname': 'value' + str(num)})
assert self.num_objects_saved() == total_events
assert queue.size() == 0
queue.stop_timer()
assert self.num_objects_saved() == 200
class TestAdd(BulkQueueTest):
def setup(self):
super(TestAdd, self).setup()
self.queue = BulkQueue(self.es_client, threshold=20)
def test_basic_add(self):
assert self.queue.size() == 0
self.queue.add(index='events', doc_type='event', body={'keyname', 'valuename'})
assert self.queue.size() == 1
assert self.queue.started() is False
def test_add_exact_threshold(self):
for num in range(0, 20):
self.queue.add(index='events', doc_type='event', body={'keyname': 'value' + str(num)})
assert self.queue.size() == 0
assert self.num_objects_saved() == 20
assert self.queue.started() is False
def test_add_over_threshold(self):
for num in range(0, 21):
self.queue.add(index='events', doc_type='event', body={'keyname': 'value' + str(num)})
assert self.num_objects_saved() == 20
assert self.queue.size() == 1
assert self.queue.started() is False
def test_add_multiple_thresholds(self):
for num in range(0, 201):
self.queue.add(index='events', doc_type='event', body={'keyname': 'value' + str(num)})
assert self.num_objects_saved() == 200
assert self.queue.size() == 1
assert self.queue.started() is False
class ElasticsearchClient():
def __init__(self, servers, bulk_amount=100, bulk_refresh_time=30):
self.es_connection = Elasticsearch(servers)
self.es_connection.ping()
self.bulk_queue = BulkQueue(self,
threshold=bulk_amount,
flush_time=bulk_refresh_time)
def delete_index(self, index_name, ignore_fail=False):
ignore_codes = []
if ignore_fail is True:
ignore_codes = [400, 404]
self.es_connection.indices.delete(index=index_name,
ignore=ignore_codes)
def get_indices(self):
return self.es_connection.indices.stats()['indices'].keys()
def index_exists(self, index_name):
return self.es_connection.indices.exists(index_name)
def create_index(self, index_name, index_config=None):
if not index_config:
index_config = '''
{
"mappings":{}
}'''
self.es_connection.indices.create(index=index_name,
update_all_types='true',
body=index_config)
def create_alias(self, alias, index):
actions = []
if self.es_connection.indices.exists_alias('*', alias):
actions.append({'remove': {'index': '*', 'alias': alias}})
actions.append({'add': {'index': index, 'alias': alias}})
self.es_connection.indices.update_aliases(dict(actions=actions))
def create_alias_multiple_indices(self, alias_name, indices):
actions = []
if self.es_connection.indices.exists_alias('*', alias_name):
actions.append({'remove': {'index': '*', 'alias': alias_name}})
for index in indices:
actions.append({'add': {'index': index, 'alias': alias_name}})
self.es_connection.indices.update_aliases(dict(actions=actions))
def get_alias(self, alias_name):
return self.es_connection.indices.get_alias(index='*',
name=alias_name).keys()
def refresh(self, index_name):
self.es_connection.indices.refresh(index=index_name)
def search(self, search_query, indices, size, request_timeout):
results = []
try:
results = Search(using=self.es_connection, index=indices).params(
size=size, request_timeout=request_timeout).filter(
search_query).execute()
except NotFoundError:
raise ElasticsearchInvalidIndex(indices)
result_set = SimpleResults(results)
return result_set
def aggregated_search(self, search_query, indices, aggregations, size,
request_timeout):
search_obj = Search(using=self.es_connection, index=indices).params(
size=size, request_timeout=request_timeout)
query_obj = search_obj.filter(search_query)
for aggregation in aggregations:
query_obj.aggs.bucket(name=aggregation.to_dict()['terms']['field'],
agg_type=aggregation)
results = query_obj.execute()
result_set = AggregatedResults(results)
return result_set
def save_documents(self, documents):
try:
bulk(self.es_connection, documents)
except BulkIndexError as e:
logger.error("Error bulk indexing: " + str(e))
def finish_bulk(self):
self.bulk_queue.flush()
self.bulk_queue.stop_thread()
def __bulk_save_document(self, index, doc_type, body, doc_id=None):
if not self.bulk_queue.started():
self.bulk_queue.start_thread()
self.bulk_queue.add(index=index,
doc_type=doc_type,
body=body,
doc_id=doc_id)
def __save_document(self, index, doc_type, body, doc_id=None, bulk=False):
if bulk:
self.__bulk_save_document(index=index,
doc_type=doc_type,
body=body,
doc_id=doc_id)
else:
return self.es_connection.index(index=index,
doc_type=doc_type,
id=doc_id,
body=body)
def __parse_document(self, body, doc_type):
if type(body) is str:
body = json.loads(body)
if '_type' in body:
doc_type = body['_type']
doc_body = body
if '_source' in body:
doc_body = body['_source']
return doc_body, doc_type
def save_object(self, body, index, doc_type, doc_id=None, bulk=False):
doc_body, doc_type = self.__parse_document(body, doc_type)
return self.__save_document(index=index,
doc_type=doc_type,
body=doc_body,
doc_id=doc_id,
bulk=bulk)
def save_alert(self,
body,
index='alerts',
doc_type='alert',
doc_id=None,
bulk=False):
doc_body, doc_type = self.__parse_document(body, doc_type)
return self.__save_document(index=index,
doc_type=doc_type,
body=doc_body,
doc_id=doc_id,
bulk=bulk)
def save_event(self,
body,
index='events',
doc_type='event',
doc_id=None,
bulk=False):
doc_body, doc_type = self.__parse_document(body, doc_type)
event = Event(doc_body)
event.add_required_fields()
return self.__save_document(index=index,
doc_type=doc_type,
body=event,
doc_id=doc_id,
bulk=bulk)
def get_object_by_id(self, object_id, indices):
id_match = TermMatch('_id', object_id)
search_query = SearchQuery()
search_query.add_must(id_match)
results = search_query.execute(self, indices=indices)
if len(results['hits']) == 0:
return None
else:
return results['hits'][0]
def get_alert_by_id(self, alert_id):
return self.get_object_by_id(alert_id, ['alerts'])
def get_event_by_id(self, event_id):
return self.get_object_by_id(event_id, ['events'])
def save_dashboard(self, dash_file, dash_name):
f = open(dash_file)
dashboardjson = json.load(f)
f.close()
title = dashboardjson['title']
dashid = dash_name.replace(' ', '-')
if dash_name:
title = dash_name
dashboarddata = {
"user": "******",
"group": "guest",
"title": title,
"dashboard": json.dumps(dashboardjson)
}
return self.es_connection.index(index='.kibana',
doc_type='dashboard',
body=dashboarddata,
id=dashid)
def get_cluster_health(self):
health_dict = self.es_connection.cluster.health()
# To line up with the health stats from ES1, we're
# removing certain keys
health_dict.pop('active_shards_percent_as_number', None)
health_dict.pop('delayed_unassigned_shards', None)
health_dict.pop('number_of_in_flight_fetch', None)
health_dict.pop('number_of_pending_tasks', None)
health_dict.pop('task_max_waiting_in_queue_millis', None)
return health_dict
class ElasticsearchClient():
def __init__(self, servers, bulk_amount=100, bulk_refresh_time=30):
self.es_connection = Elasticsearch(servers)
self.es_connection.ping()
self.bulk_queue = BulkQueue(self, threshold=bulk_amount, flush_time=bulk_refresh_time)
def close_index(self, index_name):
return self.es_connection.indices.close(index=index_name)
def open_index(self, index_name):
return self.es_connection.indices.open(index=index_name)
def delete_index(self, index_name, ignore_fail=False):
ignore_codes = []
if ignore_fail is True:
ignore_codes = [400, 404]
self.es_connection.indices.delete(index=index_name, ignore=ignore_codes)
def get_indices(self):
return self.es_connection.indices.stats()['indices'].keys()
def index_exists(self, index_name):
return self.es_connection.indices.exists(index_name)
def create_index(self, index_name, index_config=None):
if not index_config:
index_config = '''
{
"mappings":{}
}'''
self.es_connection.indices.create(index=index_name, update_all_types='true', body=index_config)
def create_alias(self, alias, index):
actions = []
if self.es_connection.indices.exists_alias('*', alias):
actions.append({
'remove': {'index': '*', 'alias': alias}
})
actions.append({
'add': {'index': index, 'alias': alias}
})
self.es_connection.indices.update_aliases(dict(actions=actions))
def create_alias_multiple_indices(self, alias_name, indices):
actions = []
if self.es_connection.indices.exists_alias('*', alias_name):
actions.append({
'remove': {'index': '*', 'alias': alias_name}
})
for index in indices:
actions.append({'add': {'index': index, 'alias': alias_name}})
self.es_connection.indices.update_aliases(dict(actions=actions))
def get_alias(self, alias_name):
return self.es_connection.indices.get_alias(index='*', name=alias_name).keys()
def get_aliases(self):
return self.es_connection.cat.stats()['indices'].keys()
def refresh(self, index_name):
self.es_connection.indices.refresh(index=index_name)
def search(self, search_query, indices, size, request_timeout):
results = []
try:
results = Search(using=self.es_connection, index=indices).params(size=size, request_timeout=request_timeout).filter(search_query).execute()
except NotFoundError:
raise ElasticsearchInvalidIndex(indices)
result_set = SimpleResults(results)
return result_set
def aggregated_search(self, search_query, indices, aggregations, size, request_timeout):
search_obj = Search(using=self.es_connection, index=indices).params(size=size, request_timeout=request_timeout)
query_obj = search_obj.filter(search_query)
for aggregation in aggregations:
query_obj.aggs.bucket(name=aggregation.to_dict()['terms']['field'], agg_type=aggregation)
results = query_obj.execute()
result_set = AggregatedResults(results)
return result_set
def save_documents(self, documents):
try:
bulk(self.es_connection, documents)
except BulkIndexError as e:
logger.error("Error bulk indexing: " + str(e))
def finish_bulk(self):
self.bulk_queue.flush()
self.bulk_queue.stop_thread()
def __bulk_save_document(self, index, doc_type, body, doc_id=None):
if not self.bulk_queue.started():
self.bulk_queue.start_thread()
self.bulk_queue.add(index=index, doc_type=doc_type, body=body, doc_id=doc_id)
def __save_document(self, index, doc_type, body, doc_id=None, bulk=False):
if bulk:
self.__bulk_save_document(index=index, doc_type=doc_type, body=body, doc_id=doc_id)
else:
return self.es_connection.index(index=index, doc_type=doc_type, id=doc_id, body=body)
def __parse_document(self, body, doc_type):
if type(body) is str:
body = json.loads(body)
if '_type' in body:
doc_type = body['_type']
doc_body = body
if '_source' in body:
doc_body = body['_source']
return doc_body, doc_type
def save_object(self, body, index, doc_type, doc_id=None, bulk=False):
doc_body, doc_type = self.__parse_document(body, doc_type)
return self.__save_document(index=index, doc_type=doc_type, body=doc_body, doc_id=doc_id, bulk=bulk)
def save_alert(self, body, index='alerts', doc_type='alert', doc_id=None, bulk=False):
doc_body, doc_type = self.__parse_document(body, doc_type)
return self.__save_document(index=index, doc_type=doc_type, body=doc_body, doc_id=doc_id, bulk=bulk)
def save_event(self, body, index='events', doc_type='event', doc_id=None, bulk=False):
doc_body, doc_type = self.__parse_document(body, doc_type)
event = Event(doc_body)
event.add_required_fields()
return self.__save_document(index=index, doc_type=doc_type, body=event, doc_id=doc_id, bulk=bulk)
def get_object_by_id(self, object_id, indices):
id_match = TermMatch('_id', object_id)
search_query = SearchQuery()
search_query.add_must(id_match)
results = search_query.execute(self, indices=indices)
if len(results['hits']) == 0:
return None
else:
return results['hits'][0]
def get_alert_by_id(self, alert_id):
return self.get_object_by_id(alert_id, ['alerts'])
def get_event_by_id(self, event_id):
return self.get_object_by_id(event_id, ['events'])
def save_dashboard(self, dash_file, dash_name):
f = open(dash_file)
dashboardjson = json.load(f)
f.close()
title = dashboardjson['title']
dashid = dash_name.replace(' ', '-')
if dash_name:
title = dash_name
dashboarddata = {
"user": "******",
"group": "guest",
"title": title,
"dashboard": json.dumps(dashboardjson)
}
return self.es_connection.index(index='.kibana', doc_type='dashboard', body=dashboarddata, id=dashid)
def get_cluster_health(self):
health_dict = self.es_connection.cluster.health()
# To line up with the health stats from ES1, we're
# removing certain keys
health_dict.pop('active_shards_percent_as_number', None)
health_dict.pop('delayed_unassigned_shards', None)
health_dict.pop('number_of_in_flight_fetch', None)
health_dict.pop('number_of_pending_tasks', None)
health_dict.pop('task_max_waiting_in_queue_millis', None)
return health_dict