# coding: utf-8
import logging
from datetime import timedelta
from enum import Enum
from random import random
from time import sleep
from typing import Union, List
import rx
from rx import operators as ops, Observable
from rx.core import GroupedObservable
from rx.scheduler import ThreadPoolScheduler
from rx.subject import Subject
from influxdb_client import WritePrecision, WriteService
from influxdb_client.client.abstract_client import AbstractClient
from influxdb_client.client.write.point import Point, DEFAULT_WRITE_PRECISION
from influxdb_client.rest import ApiException
logger = logging.getLogger(__name__)
class WriteType(Enum):
batching = 1
asynchronous = 2
synchronous = 3
class WriteOptions(object):
def __init__(self, write_type: WriteType = WriteType.batching,
batch_size=1_000, flush_interval=1_000,
jitter_interval=0,
retry_interval=1_000,
write_scheduler=ThreadPoolScheduler(max_workers=1)) -> None:
"""
Creates write api configuration.
:param write_type: methods of write (batching, asynchronous, synchronous)
:param batch_size: the number of data point to collect in batch
:param flush_interval: flush data at least in this interval
:param jitter_interval: this is primarily to avoid large write spikes for users running a large number of
client instances ie, a jitter of 5s and flush duration 10s means flushes will happen every 10-15s.
:param retry_interval: the time to wait before retry unsuccessful write
:param write_scheduler:
"""
self.write_type = write_type
self.batch_size = batch_size
self.flush_interval = flush_interval
self.jitter_interval = jitter_interval
self.retry_interval = retry_interval
self.write_scheduler = write_scheduler
SYNCHRONOUS = WriteOptions(write_type=WriteType.synchronous)
ASYNCHRONOUS = WriteOptions(write_type=WriteType.asynchronous)
class _BatchItem(object):
def __init__(self, key, data) -> None:
self.key = key
self.data = data
pass
def __str__(self) -> str:
return '_BatchItem[key:\'{}\', \'{}\']' \
.format(str(self.key), str(self.data))
class _BatchItemKey(object):
def __init__(self, bucket, org, precision=DEFAULT_WRITE_PRECISION) -> None:
self.bucket = bucket
self.org = org
self.precision = precision
pass
def __hash__(self) -> int:
return hash((self.bucket, self.org, self.precision))
def __eq__(self, o: object) -> bool:
return isinstance(o, self.__class__) \
and self.bucket == o.bucket and self.org == o.org and self.precision == o.precision
def __str__(self) -> str:
return '_BatchItemKey[bucket:\'{}\', org:\'{}\', precision:\'{}\']' \
.format(str(self.bucket), str(self.org), str(self.precision))
class _BatchResponse(object):
def __init__(self, data: _BatchItem, exception=None):
self.data = data
self.exception = exception
pass
def __str__(self) -> str:
return '_BatchResponse[status:\'{}\', \'{}\']' \
.format("failed" if self.exception else "success", str(self.data))
def _body_reduce(batch_items):
return b'\n'.join(map(lambda batch_item: batch_item.data, batch_items))
def _create_batch(group: GroupedObservable):
return lambda xs: _BatchItem(key=group.key, data=_body_reduce(xs))
def _group_by(batch_item: _BatchItem):
return batch_item.key
def _group_to_batch(group: GroupedObservable):
return group.pipe(ops.to_iterable(),
ops.map(list),
ops.map(_create_batch(group)))
def _window_to_group(value):
return value.pipe(
ops.to_iterable(),
ops.map(lambda x: rx.from_iterable(x).pipe(
# Group window by 'organization', 'bucket' and 'precision'
ops.group_by(_group_by),
# Create batch (concatenation line protocols by \n)
ops.map(_group_to_batch),
ops.merge_all())), ops.merge_all())
[docs]class WriteApi(AbstractClient):
def __init__(self, influxdb_client, write_options: WriteOptions = WriteOptions()) -> None:
self._influxdb_client = influxdb_client
self._write_service = WriteService(influxdb_client.api_client)
self._write_options = write_options
if self._write_options.write_type is WriteType.batching:
# Define Subject that listen incoming data and produces writes into InfluxDB
self._subject = Subject()
# Define a scheduler that is used for processing incoming data - default singleton
observable = self._subject.pipe(ops.observe_on(self._write_options.write_scheduler))
self._disposable = observable \
.pipe( # Split incoming data to windows by batch_size or flush_interval
ops.window_with_time_or_count(count=write_options.batch_size,
timespan=timedelta(milliseconds=write_options.flush_interval)),
# Map incoming batch window in groups defined by 'organization', 'bucket' and 'precision'
ops.flat_map(lambda v: _window_to_group(v)),
# Write data into InfluxDB (possibility to retry if its fail)
ops.map(mapper=lambda batch: self._retryable(data=batch, delay=self._jitter_delay())), #
ops.merge_all()) \
.subscribe(self._on_next, self._on_error, self._on_complete)
else:
self._subject = None
self._disposable = None
[docs] def write(self, bucket: str, org: str,
record: Union[
str, List['str'], Point, List['Point'], dict, List['dict'], bytes, List['bytes'], Observable],
write_precision: WritePrecision = DEFAULT_WRITE_PRECISION) -> None:
"""
Writes time-series data into influxdb.
:param str org: specifies the destination organization for writes; take either the ID or Name interchangeably; if both orgID and org are specified, org takes precedence. (required)
:param str bucket: specifies the destination bucket for writes (required)
:param WritePrecision write_precision: specifies the precision for the unix timestamps within the body line-protocol
:param record: Points, line protocol, RxPY Observable to write
"""
if self._write_options.write_type is WriteType.batching:
return self._write_batching(bucket, org, record, write_precision)
final_string = self._serialize(record, write_precision)
_async_req = True if self._write_options.write_type == WriteType.asynchronous else False
return self._post_write(_async_req, bucket, org, final_string, write_precision)
def flush(self):
# TODO
pass
def __del__(self):
if self._subject:
self._subject.on_completed()
self._subject.dispose()
self._subject = None
# Wait for finish writing
while not self._disposable.is_disposed:
sleep(0.1)
if self._disposable:
self._disposable = None
pass
def _serialize(self, record, write_precision) -> bytes:
_result = b''
if isinstance(record, bytes):
_result = record
elif isinstance(record, str):
_result = record.encode("utf-8")
elif isinstance(record, Point):
_result = self._serialize(record.to_line_protocol(), write_precision=write_precision)
elif isinstance(record, dict):
_result = self._serialize(Point.from_dict(record, write_precision=write_precision),
write_precision=write_precision)
elif isinstance(record, list):
_result = b'\n'.join([self._serialize(item, write_precision=write_precision) for item in record])
return _result
def _write_batching(self, bucket, org, data, precision=DEFAULT_WRITE_PRECISION):
_key = _BatchItemKey(bucket, org, precision)
if isinstance(data, bytes):
self._subject.on_next(_BatchItem(key=_key, data=data))
elif isinstance(data, str):
self._write_batching(bucket, org, data.encode("utf-8"), precision)
elif isinstance(data, Point):
self._write_batching(bucket, org, data.to_line_protocol(), precision)
elif isinstance(data, dict):
self._write_batching(bucket, org, Point.from_dict(data, write_precision=precision), precision)
elif isinstance(data, list):
for item in data:
self._write_batching(bucket, org, item, precision)
elif isinstance(data, Observable):
data.subscribe(lambda it: self._write_batching(bucket, org, it, precision))
pass
return None
def _http(self, batch_item: _BatchItem):
logger.debug("http post to: %s", batch_item)
self._post_write(False, batch_item.key.bucket, batch_item.key.org, batch_item.data,
batch_item.key.precision)
return _BatchResponse(data=batch_item)
def _post_write(self, _async_req, bucket, org, body, precision):
return self._write_service.post_write(org=org, bucket=bucket, body=body, precision=precision,
async_req=_async_req, content_encoding="identity",
content_type="text/plain; charset=utf-8")
def _retryable(self, data: str, delay: timedelta):
return rx.of(data).pipe(
# use delay if its specified
ops.delay(duetime=delay, scheduler=self._write_options.write_scheduler),
# invoke http call
ops.map(lambda x: self._http(x)),
# if there is an error than retry
ops.catch(handler=lambda exception, source: self._retry_handler(exception, source, data)),
)
def _retry_handler(self, exception, source, data):
if isinstance(exception, ApiException):
if exception.status == 429 or exception.status == 503:
_delay = self._jitter_delay() + timedelta(milliseconds=self._write_options.retry_interval)
return self._retryable(data, delay=_delay)
return rx.just(_BatchResponse(exception=exception, data=data))
def _jitter_delay(self):
return timedelta(milliseconds=random() * self._write_options.jitter_interval)
@staticmethod
def _on_next(response: _BatchResponse):
if response.exception:
logger.error("The batch item wasn't processed successfully because: %s", response.exception)
else:
logger.debug("The batch item: %s was processed successfully.", response)
@staticmethod
def _on_error(ex):
logger.error("unexpected error during batching: %s", ex)
def _on_complete(self):
self._disposable.dispose()
logger.info("the batching processor was disposed")