def get_schema(self, get_stats=False):
connection = atsd_client.connect_url(
self.url,
self.configuration.get("username"),
self.configuration.get("password"),
verify=self.configuration.get("trust_certificate", False),
timeout=self.configuration.get("timeout", 600),
)
metrics = MetricsService(connection)
ml = metrics.list(
expression=self.configuration.get("expression", None),
minInsertDate=self.configuration.get("min_insert_date", None),
limit=self.configuration.get("limit", 5000),
)
metrics_list = [i.name.encode("utf-8") for i in ml]
metrics_list.append("atsd_series")
schema = {}
default_columns = [
"entity",
"datetime",
"time",
"metric",
"value",
"text",
"tags",
"entity.tags",
"metric.tags",
]
for table_name in metrics_list:
schema[table_name] = {
"name": "'{}'".format(table_name),
"columns": default_columns,
}
values = list(schema.values())
return values
def get_schema(self, get_stats=False):
connection = atsd_client.connect_url(
self.url,
self.configuration.get('username'),
self.configuration.get('password'),
verify=self.configuration.get('trust_certificate', False),
timeout=self.configuration.get('timeout', 600))
metrics = MetricsService(connection)
ml = metrics.list(
expression=self.configuration.get('expression', None),
minInsertDate=self.configuration.get('min_insert_date', None),
limit=self.configuration.get('limit', 5000))
metrics_list = [i.name.encode('utf-8') for i in ml]
metrics_list.append('atsd_series')
schema = {}
default_columns = [
'entity', 'datetime', 'time', 'metric', 'value', 'text', 'tags',
'entity.tags', 'metric.tags'
]
for table_name in metrics_list:
schema[table_name] = {
'name': "'{}'".format(table_name),
'columns': default_columns
}
values = schema.values()
return values
def get_schema(self, get_stats=False):
connection = atsd_client.connect_url(self.url,
self.configuration.get('username'),
self.configuration.get('password'),
verify=self.configuration.get('trust_certificate', False),
timeout=self.configuration.get('timeout', 600))
metrics = MetricsService(connection)
ml = metrics.list(expression=self.configuration.get('expression', None),
minInsertDate=self.configuration.get('min_insert_date', None),
limit=self.configuration.get('limit', 5000))
metrics_list = [i.name.encode('utf-8') for i in ml]
metrics_list.append('atsd_series')
schema = {}
default_columns = ['entity', 'datetime', 'time', 'metric', 'value', 'text',
'tags', 'entity.tags', 'metric.tags']
for table_name in metrics_list:
schema[table_name] = {'name': "'{}'".format(table_name),
'columns': default_columns}
values = schema.values()
return values
from atsd_client import connect, connect_url
from atsd_client.services import MetricsService
'''
Locate a collection of metrics that have been created after specified date.
'''
# Connect to ATSD server
#connection = connect('/path/to/connection.properties')
connection = connect_url('https://atsd_hostname:8443', 'username', 'password')
# Initialize services
metrics_service = MetricsService(connection)
# query all metrics created after specified_date
metric_list = metrics_service.list(expression="createdDate > '2018-05-16T00:00:00Z'")
print('metric_name')
for metric in metric_list:
print(metric.name)
from atsd_client.services import MetricsService, SeriesService
'''
Find series with data older than `now - (metric.retention_days + grace_interval_days)`.
'''
# Connect to ATSD server
#connection = connect('/path/to/connection.properties')
connection = connect_url('https://atsd_hostname:8443', 'username', 'password')
# Initialize services
svc = SeriesService(connection)
metric_service = MetricsService(connection)
metric_expression = "enabled AND persistent AND retentionDays > 0"
metric_list = metric_service.list(expression=metric_expression)
series_count = 0
# ATSD expired data removal schedule frequency, default is one day
grace_interval_days = 1
t = PrettyTable(['Metric', 'Entity', 'Tags', 'Retention Days', 'Threshold', 'Presented Sample Date'])
for metric in metric_list:
# calculate datetime before which there is data
threshold = datetime.now() - timedelta(days=metric.retention_days + grace_interval_days)
# query series with current metric and all entities from the beginning up to threshold
# enough to get at least one value, limit set to 1
sf = SeriesFilter(metric=metric.name)
ef = EntityFilter(entity='*')
df = DateFilter(start_date="1970-01-01T00:00:00Z", end_date=threshold)
cf = ControlFilter(limit=1)
from atsd_client import connect_url
from atsd_client.services import MetricsService
'''
Locate a collection of metrics that have no last_insert_date.
'''
# Connect to an ATSD server
connection = connect_url('https://atsd_hostname:8443', 'user', 'password')
metric_service = MetricsService(connection)
# query entities without last_insert_date
metric_list = metric_service.list(max_insert_date="1970-01-01T00:00:00.000Z")
metrics_count = 0
print('metric_name')
for metric in metric_list:
if metric.enabled and metric.persistent \
and metric.retention_days == 0 and metric.series_retention_days == 0:
metrics_count += 1
print(metric.name)
print("\nMetrics count without last insert date is %d." % metrics_count)
from atsd_client import connect, connect_url
from atsd_client.services import MetricsService
'''
Locate a collection of metrics that have no last_insert_date.
'''
# Connect to ATSD server
#connection = connect('/path/to/connection.properties')
connection = connect_url('https://atsd_hostname:8443', 'username', 'password')
# Initialize services
metric_service = MetricsService(connection)
# query entities without last_insert_date
metric_list = metric_service.list(max_insert_date="1970-01-01T00:00:00.000Z")
metrics_count = 0
print('metric_name')
for metric in metric_list:
if metric.enabled and metric.persistent \
and metric.retention_days == 0 and metric.series_retention_days == 0:
metrics_count += 1
print(metric.name)
print("\nMetrics count without last insert date is %d." % metrics_count)
from atsd_client import connect_url
from atsd_client.models import SeriesFilter, EntityFilter, DateFilter, SeriesQuery
from atsd_client.services import MetricsService, SeriesService
'''
Retrieve metrics with 'frequency' tag. Load series for this metric.
Print values that violate frequency (but not data gaps if the gap is a multiple of the frequency period).
'''
# Connect to an ATSD server
connection = connect_url('https://atsd_hostname:8443', 'user', 'password')
svc = SeriesService(connection)
metric_service = MetricsService(connection)
# query metrics with not empty frequency tag, include all metric tags to response
metric_list = metric_service.list(expression='tags.frequency != ""', tags='*')
def resolve_frequency(frequency):
"""
Transform metric frequency tag into relativedelta instance
"""
if frequency in ['Daily (D)', 'Daily', 'Daily, 7-Day', 'Daily, Close']:
return relativedelta(days=1)
elif frequency in [
'Weekly',
'Weekly, As of Monday',
'Weekly, As of Wednesday',
'Weekly, As of Thursday',
'Weekly, Ending Monday',
from atsd_client.services import MetricsService
from atsd_client.utils import print_tags
'''
Locate high-cardinality series that have tags more than specified cardinality.
'''
# Connect to ATSD server
#connection = connect('/path/to/connection.properties')
connection = connect_url('https://atsd_hostname:8443', 'username', 'password')
# Initialize services
metrics_service = MetricsService(connection)
# query all metrics that have last_insert_date, i.e. series
metrics = metrics_service.list(min_insert_date="1970-01-01T00:00:00.000Z")
# set cardinality
cardinality = 8
series_count = 0
print('metric,entity,tags,last_insert_date')
for metric in metrics:
# query series list for each metric
series_list = metrics_service.series(metric)
for s in series_list:
# check tags cardinality for each series in list
if len(s.tags) > cardinality:
series_count += 1
print("%s,%s,%s,%s" % (s.metric, s.entity, print_tags(s.tags), s.last_insert_date))
from atsd_client.services import MetricsService, SeriesService
'''
Retrieve metrics with 'frequency' tag. Load series for this metric.
Print values that violate frequency (but not data gaps if the gap is a multiple of the frequency period).
'''
# Connect to ATSD server
#connection = connect('/path/to/connection.properties')
connection = connect_url('https://atsd_hostname:8443', 'username', 'password')
# Initialize services
svc = SeriesService(connection)
metric_service = MetricsService(connection)
# query metrics with not empty frequency tag, include all metric tags to response
metric_list = metric_service.list(expression='tags.frequency != ""', tags='*')
def resolve_frequency(frequency):
"""
Transform metric frequency tag into relativedelta instance
"""
if frequency in ['Daily (D)', 'Daily', 'Daily, 7-Day', 'Daily, Close']:
return relativedelta(days=1)
elif frequency in ['Weekly', 'Weekly, As of Monday', 'Weekly, As of Wednesday', 'Weekly, As of Thursday',
'Weekly, Ending Monday', 'Weekly, Ending Wednesday', 'Weekly, Ending Thursday',
'Weekly, Ending Friday', 'Weekly, Ending Saturday', ]:
return relativedelta(weeks=1)
elif frequency in ['Biweekly, Beg. of Period', 'Biweekly, Ending Wednesday']:
return relativedelta(weeks=2)