def persist(self, timestamp, buffer, bucket):
def doit():
count = bucket.interval.total_seconds() / self.config.buckets[0].interval.total_seconds()
data = self.bucket_buffers[0].data
mean = np.mean(list(zip(*data[-count:]))[1])
buffer.push(timestamp, mean)
threadpool.apply(doit)
def persist(self, timestamp, buffer, bucket):
def doit():
count = bucket.interval.total_seconds(
) / self.config.buckets[0].interval.total_seconds()
data = self.bucket_buffers[0].data
mean = np.mean(list(zip(*data[-count:]))[1])
buffer.push(timestamp, mean)
threadpool.apply(doit)
def cursor(self):
threadpool = self._context.get("threadpool", gevent.get_hub().threadpool)
methods = ("callproc", "close", "execute", "executemany",
"fetchone", "fetchmany", "fetchall", "nextset", "setinputsizes", "setoutputsize")
return type("CursorProxy", (Proxy,), {
"_inner": threadpool.apply(self._inner.cursor, None, None),
"_context": dict(self._context.items()+[("methods", methods),]) })()
def connect(self, *args, **kwargs):
threadpool = self._context.get("threadpool", gevent.get_hub().threadpool)
if self._context.get("single_thread_connection"):
threadpool = gevent.threadpool.ThreadPool(1)
methods = ("close", "commit", "rollback", "cursor")
return type("ConnectionProxy", (ConnectionProxy,), {
"_inner": threadpool.apply(self._inner.connect, args, kwargs),
"_context": dict(self._context.items()+[("methods", methods), ("threadpool", threadpool)]) })()
def query(self, start, end, frequency):
self.logger.debug('Query: start={0}, end={1}, frequency={2}'.format(start, end, frequency))
buckets = list(self.config.get_covered_buckets(start, end))
def doit():
df = pd.DataFrame()
for b in buckets:
new = self.bucket_buffers[b.index].df
if new is not None:
df = pd.concat((df, new))
df = df.reset_index().drop_duplicates(subset='index').set_index('index')
if len(buckets):
df = df.sort()[0]
df = df[start:end]
df = df.resample(frequency, how='mean').interpolate()
return df
return threadpool.apply(doit)
def query(self, start, end, frequency):
self.logger.debug('Query: start={0}, end={1}, frequency={2}'.format(
start, end, frequency))
buckets = list(self.config.get_covered_buckets(start, end))
def doit():
df = pd.DataFrame()
for b in buckets:
new = self.bucket_buffers[b.index].df
if new is not None:
df = pd.concat((df, new))
df = df.reset_index().drop_duplicates(
subset='index').set_index('index')
if len(buckets):
df = df.sort()[0]
df = df[start:end]
df = df.resample(frequency, how='mean').interpolate()
return df
return threadpool.apply(doit)
