class SpringSpatialQueryLatency(SpringLatency):
COLLECTOR = "spring_query_latency"
METRICS = ("latency_query",)
def __init__(self, settings, workload, spatial_settings, prefix=None):
super(SpringSpatialQueryLatency, self).__init__(settings, workload, prefix)
self.offset = 0
view_names = self._parse_views(spatial_settings.indexes)
self.clients = []
for bucket in self.get_buckets():
client = SpatialGen(
bucket=bucket, host=settings.master_node, username=bucket, password=settings.bucket_password
)
self.clients.append((bucket, client))
self.new_queries = SpatialQueryFromFile(
spatial_settings.queries, spatial_settings.dimensionality, view_names, spatial_settings.params
)
@staticmethod
def _parse_views(indexes):
views = []
for index in indexes:
ddoc_name, ddoc = index.split("::", 1)
for view_name in json.loads(ddoc)["spatial"].keys():
views.append("{}::{}".format(ddoc_name, view_name))
return views
def measure(self, client, metric, bucket):
ddoc_name, view_name, query = self.new_queries.next(self.offset)
_, latency = client.query(ddoc_name, view_name, query=query)
self.offset += 1
return 1000 * latency # s -> ms
class SpatialWorker(QueryWorker):
def __init__(self, workload_settings, target_settings, shutdown_event):
super(QueryWorker, self).__init__(workload_settings, target_settings,
shutdown_event)
self.total_workers = self.ws.spatial.workers
self.throughput = self.ws.spatial.throughput
self.name = 'spatial-worker'
self.new_queries = SpatialQueryFromFile(
workload_settings.spatial.queries,
workload_settings.spatial.dimensionality,
workload_settings.spatial.view_names,
workload_settings.spatial.params)
host, port = self.ts.node.split(':')
params = {'bucket': self.ts.bucket, 'host': host, 'port': port,
'username': self.ts.bucket, 'password': self.ts.password}
self.cb = SpatialGen(**params)
@with_sleep
def do_batch(self):
for i in xrange(self.BATCH_SIZE):
offset = self.curr_queries.value - self.BATCH_SIZE + i
ddoc_name, view_name, query = self.new_queries.next(offset)
self.cb.query(ddoc_name, view_name, query=query)
def __init__(self, settings, workload, spatial_settings, prefix=None):
super(SpringSpatialQueryLatency,
self).__init__(settings, workload, prefix)
self.offset = 0
view_names = self._parse_views(spatial_settings.indexes)
self.clients = []
for bucket in self.get_buckets():
client = SpatialGen(bucket=bucket,
host=settings.master_node,
username=bucket,
password=settings.bucket_password)
self.clients.append((bucket, client))
self.new_queries = SpatialQueryFromFile(
spatial_settings.queries, spatial_settings.dimensionality,
view_names, spatial_settings.params)
def __init__(self, workload_settings, target_settings, shutdown_event):
super(QueryWorker, self).__init__(workload_settings, target_settings,
shutdown_event)
self.total_workers = self.ws.spatial.workers
self.throughput = self.ws.spatial.throughput
self.name = 'spatial-worker'
self.new_queries = SpatialQueryFromFile(
workload_settings.spatial.queries,
workload_settings.spatial.dimensionality,
workload_settings.spatial.view_names,
workload_settings.spatial.params)
host, port = self.ts.node.split(':')
params = {'bucket': self.ts.bucket, 'host': host, 'port': port,
'username': self.ts.bucket, 'password': self.ts.password}
self.cb = SpatialGen(**params)
def __init__(self, settings, workload, spatial_settings, prefix=None):
super(SpringSpatialQueryLatency, self).__init__(settings, workload, prefix)
self.offset = 0
view_names = self._parse_views(spatial_settings.indexes)
self.clients = []
for bucket in self.get_buckets():
client = SpatialGen(
bucket=bucket, host=settings.master_node, username=bucket, password=settings.bucket_password
)
self.clients.append((bucket, client))
self.new_queries = SpatialQueryFromFile(
spatial_settings.queries, spatial_settings.dimensionality, view_names, spatial_settings.params
)
class SpringSpatialQueryLatency(SpringLatency):
COLLECTOR = "spring_query_latency"
METRICS = ("latency_query", )
def __init__(self, settings, workload, spatial_settings, prefix=None):
super(SpringSpatialQueryLatency,
self).__init__(settings, workload, prefix)
self.offset = 0
view_names = self._parse_views(spatial_settings.indexes)
self.clients = []
for bucket in self.get_buckets():
client = SpatialGen(bucket=bucket,
host=settings.master_node,
username=bucket,
password=settings.bucket_password)
self.clients.append((bucket, client))
self.new_queries = SpatialQueryFromFile(
spatial_settings.queries, spatial_settings.dimensionality,
view_names, spatial_settings.params)
@staticmethod
def _parse_views(indexes):
views = []
for index in indexes:
ddoc_name, ddoc = index.split('::', 1)
for view_name in json.loads(ddoc)['spatial'].keys():
views.append('{}::{}'.format(ddoc_name, view_name))
return views
def measure(self, client, metric, bucket):
ddoc_name, view_name, query = self.new_queries.next(self.offset)
_, latency = client.query(ddoc_name, view_name, query=query)
self.offset += 1
return 1000 * latency # s -> ms
