在CAP理论与MongoDB一致性、可用性的一些思考一文中提到，MongoDB提供了一些选项，如Read Preference、Read Concern、Write Concern，对MongoDB的一致性、可用性、可靠性（durability）、性能会有较大的影响。与Read Concern、Write Concern不同的是，Read Preference基本上完全由MongoDb Driver实现，因此，本文通过PyMongo来看看Read Preference具体是如何实现的。
本文分析的PyMongo版本是PyMongo3.6，该版本兼容MongoDB3.6及以下的MongoDB。
本文地址：https://www.cnblogs.com/xybaby/p/10256812.html
Read Preference
Read preference describes how MongoDB clients route read operations to the members of a replica set.
Read Prefenrece决定了使用复制集（replica set）时，读操作路由到哪个mongod节点，如果使用Sharded Cluster，路由选择由Mongos决定，如果直接使用replica set，那么路由选择由driver决定。如下图所示：
MongoDB提供了以下Read Preference Mode：
- primary：默认模式，一切读操作都路由到replica set的primary节点
- primaryPreferred：正常情况下都是路由到primary节点，只有当primary节点不可用（failover）的时候，才路由到secondary节点。
- secondary：一切读操作都路由到replica set的secondary节点
- secondaryPreferred：正常情况下都是路由到secondary节点，只有当secondary节点不可用的时候，才路由到primary节点。
- nearest：从延时最小的节点读取数据，不管是primary还是secondary。对于分布式应用且MongoDB是多数据中心部署，nearest能保证最好的data locality。
这五种模式还受到maxStalenessSeconds和tagsets的影响。
不同的read Preference mode适合不同的应用场景，如果数据的一致性很重要，比如必须保证read-after-write一致性，那么就需要从primary读，因为secondary的数据有一定的滞后。如果能接受一定程度的stale data，那么从secondary读数据可以减轻primary的压力，且在primary failover期间也能提供服务，可用性更高。如果对延时敏感，那么适合nearest。另外，通过tagsets，还可以有更丰富的定制化读取策略，比如指定从某些datacenter读取。
PyMongo
首先给出pymongo中与read preference相关的类，方便后面的分析。
上图中实线箭头表示强引用（复合），虚线箭头表示弱引用（聚合）
connect to replica set
PyMongo的文档给出了如何连接到复制集：指定复制集的名字，以及一个或多个该复制集内的节点。如：
MongoClient(\'localhost\', replicaset=\'foo\')
上述操作是non-blocking，立即返回，通过后台线程去连接指定节点，PyMongo连接到节点后，会从mongod节点获取到复制集内其他节点的信息，然后再连接到复制集内的其他节点。
from time import sleep
c = MongoClient(\'localhost\', replicaset=\'foo\'); print(c.nodes); sleep(0.1); print(c.nodes)
frozenset([])
frozenset([(u\'localhost\', 27019), (u\'localhost\', 27017), (u\'localhost\', 27018)])
可以看到，刚初始化MongoClient实例时，并没有连接到任何节点(c.nodes)为空；过了一段时间，再查看，那么会发现已经连上了复制集内的三个节点。
那么问题来了，创建MongoClient后，尚未连接到复制集节点之前，能否立即操作数据库？
If you need to do any operation with a MongoClient, such as a find() or an insert_one(), the client waits to discover a suitable member before it attempts the operation.
通过后续的代码分析可以看到，会通过一个条件变量（threading.Condition）去协调。
PyMongo Monitor
上面提到，初始化MongoClient对象的时候，会通过指定的mognod节点去发现复制集内的其他节点，这个就是通过monitor.Monitor来实现的。从上面的类图可以看到，每一个server（与一个mongod节点对应）都有一个monitor。Monitor的作用在于：
- Health: detect when a member goes down or comes up, or if a different member becomes primary
- Configuration: detect when members are added or removed, and detect changes in members’ tags
- Latency: track a moving average of each member’s ping time
Monitor会启动一个后台线程 PeriodExecutor，定时（默认10s）通过socket连接Pool给对应的mongod节点发送 ismaster 消息。核心代码（略作调整)如下
def _run(self):
self._server_description = self._check_with_retry()
self._topology.on_change(self._server_description)
def _check_with_retry(self):
address = self._server_description.address
response, round_trip_time = self._check_with_socket(
sock_info, metadata=metadata)
self._avg_round_trip_time.add_sample(round_trip_time) # 更新rtt
sd = ServerDescription(
address=address,
ismaster=response,
round_trip_time=self._avg_round_trip_time.get())
return sd
def _check_with_socket(self, sock_info, metadata=None):
"""Return (IsMaster, round_trip_time).
Can raise ConnectionFailure or OperationFailure.
"""
cmd = SON([(\'ismaster\', 1)])
if metadata is not None:
cmd[\'client\'] = metadata
if self._server_description.max_wire_version >= 6:
cluster_time = self._topology.max_cluster_time()
if cluster_time is not None:
cmd[\'$clusterTime\'] = cluster_time
start = _time()
request_id, msg, max_doc_size = message.query(
0, \'admin.$cmd\', 0, -1, cmd,
None, DEFAULT_CODEC_OPTIONS)
# TODO: use sock_info.command()
sock_info.send_message(msg, max_doc_size)
reply = sock_info.receive_message(request_id)
return IsMaster(reply.command_response()), _time() - start
类IsMaster是对ismaster command reponse的封装，比较核心的属性包括：
- replica_set_name：从mongod节点看来，复制集的名字
- primary：从mongod节点看来，谁是Priamry
- all_hosts: 从mongod节点看来，复制集中的所有节点
- last_write_date： mongod节点最后写入数据的时间，用来判断secondary节点的staleness
- set_version：config version
- election_id：只有当mongod是primary时才会设置，表示最新的primary选举编号
当某个server的monitor获取到了在server对应的mongod上的复制集信息信息时，调用Tolopogy.on_change更新复制集的拓扑信息：
def on_change(self, server_description):
"""Process a new ServerDescription after an ismaster call completes."""
if self._description.has_server(server_description.address):
self._description = updated_topology_description(
self._description, server_description)
self._update_servers() # 根据信息，连接到新增的节点，移除（断开）已经不存在的节点
self._receive_cluster_time_no_lock(
server_description.cluster_time)
# Wake waiters in select_servers().
self._condition.notify_all()
核心在updated_topology_description, 根据本地记录的topology信息，以及收到的server_description(来自IsMaster- ismaster command response)，来调整本地的topology信息。以一种情况为例：收到一个ismaster command response，对方自称自己是primary，不管当前topology有没有primary，都会进入调用以下函数
def _update_rs_from_primary(
sds,
replica_set_name,
server_description,
max_set_version,
max_election_id):
"""Update topology description from a primary\'s ismaster response.
Pass in a dict of ServerDescriptions, current replica set name, the
ServerDescription we are processing, and the TopologyDescription\'s
max_set_version and max_election_id if any.
Returns (new topology type, new replica_set_name, new max_set_version,
new max_election_id).
"""
if replica_set_name is None:
replica_set_name = server_description.replica_set_name
elif replica_set_name != server_description.replica_set_name: # 不是来自同一个复制集
# We found a primary but it doesn\'t have the replica_set_name
# provided by the user.
sds.pop(server_description.address)
return (_check_has_primary(sds),
replica_set_name,
max_set_version,
max_election_id)
max_election_tuple = max_set_version, max_election_id
if None not in server_description.election_tuple:
if (None not in max_election_tuple and
max_election_tuple > server_description.election_tuple): # 节点是priamry，但比topology中记录的旧
# Stale primary, set to type Unknown.
address = server_description.address
sds[address] = ServerDescription(address) # 传入空dict，则server-type为UnKnown
return (_check_has_primary(sds),
replica_set_name,
max_set_version,
max_election_id)
max_election_id = server_description.election_id
if (server_description.set_version is not None and # 节点的config version版本更高
(max_set_version is None or
server_description.set_version > max_set_version)):
max_set_version = server_description.set_version
# We\'ve heard from the primary. Is it the same primary as before?
for server in sds.values():
if (server.server_type is SERVER_TYPE.RSPrimary
and server.address != server_description.address):
# Reset old primary\'s type to Unknown.
sds[server.address] = ServerDescription(server.address)
# There can be only one prior primary.
break
# Discover new hosts from this primary\'s response.
for new_address in server_description.all_hosts:
if new_address not in sds:
sds[new_address] = ServerDescription(new_address)
# Remove hosts not in the response.
for addr in set(sds) - server_description.all_hosts:
sds.pop(addr)
# If the host list differs from the seed list, we may not have a primary
# after all.
return (_check_has_primary(sds),
replica_set_name,
max_set_version,
max_election_id)
注意看docstring中的Returns，都是返回新的复制集信息
那么整个函数从上往下检查
- 是不是同一个复制集
- 新节点（自认为是primary）与topology记录的primary相比，谁更新。比较(set_version, election_id)
- 比较set_servion
- 如果topology中已经有stale primary，那么将其server-type改成Unknown
- 从Primary节点的all_hosts中取出新加入复制集的节点
- 移除已经不存在于复制集中的节点
PyMongo关于复制集的状态都来自于所有节点的ismaster消息，Source of Truth在于复制集，而且这个Truth来自于majority 节点。因此，某个节点返回给driver的信息可能是过期的、错误的，driver通过有限的信息判断复制集的状态，如果判断失误，比如将写操作发到了stale primary上，那么会在复制集上再次判断，保证正确性。
PyMongo read preference
前面详细介绍了PyMongo是如何更新复制集的信息，那么这一部分来看看基于拓扑信息具体是如何根据read preference路由到某个节点上的。
我们从Collection.find出发，一路跟踪, 会调用MongoClient._send_message_with_response
def _send_message_with_response(self, operation, read_preference=None,
exhaust=False, address=None):
topology = self._get_topology()
if address:
server = topology.select_server_by_address(address)
if not server:
raise AutoReconnect(\'server %s:%d no longer available\'
% address)
else:
selector = read_preference or writable_server_selector
server = topology.select_server(selector)
return self._reset_on_error(
server,
server.send_message_with_response,
operation,
set_slave_ok,
self.__all_credentials,
self._event_listeners,
exhaust)
代码很清晰，根据指定的address或者read_preference， 选择出server，然后通过server发请求，等待回复。topology.select_server一路调用到下面这个函数
def _select_servers_loop(self, selector, timeout, address):
"""select_servers() guts. Hold the lock when calling this."""
now = _time()
end_time = now + timeout
server_descriptions = self._description.apply_selector( # _description是TopologyDescription
selector, address)
while not server_descriptions:
# No suitable servers.
if timeout == 0 or now > end_time:
raise ServerSelectionTimeoutError(
self._error_message(selector))
self._ensure_opened()
self._request_check_all()
# Release the lock and wait for the topology description to
# change, or for a timeout. We won\'t miss any changes that
# came after our most recent apply_selector call, since we\'ve
# held the lock until now.
self._condition.wait(common.MIN_HEARTBEAT_INTERVAL) # Conditional.wait
self._description.check_compatible()
now = _time()
server_descriptions = self._description.apply_selector(
selector, address)
self._description.check_compatible()
return server_descriptions
可以看到，不一定能一次选出来，如果选不出server，意味着此时还没有连接到足够多的mongod节点，那么等待一段时间（_condition.wait）重试。在上面Topology.on_change 可以看到，会调用_condition.notify_all唤醒。
def apply_selector(self, selector, address):
def apply_local_threshold(selection):
if not selection:
return []
settings = self._topology_settings
# Round trip time in seconds.
fastest = min(
s.round_trip_time for s in selection.server_descriptions)
threshold = settings.local_threshold_ms / 1000.0
return [s for s in selection.server_descriptions
if (s.round_trip_time - fastest) <= threshold]
# 省略了无关代码...
return apply_local_threshold(
selector(Selection.from_topology_description(self)))
上面selector就是read_preference._ServerMode的某一个子类，以Nearest为例
class Nearest(_ServerMode):
def __call__(self, selection):
"""Apply this read preference to Selection."""
return member_with_tags_server_selector(
self.tag_sets,
max_staleness_selectors.select(
self.max_staleness, selection))
首先要受到maxStalenessSeconds的约束，然后再用tagsets过滤一遍，这里只关注前者。
关于maxStalenessSeconds
The read preference maxStalenessSeconds option lets you specify a maximum replication lag, or “staleness”, for reads from secondaries. When a secondary’s estimated staleness exceeds maxStalenessSeconds, the client stops using it for read operations.
怎么计算的，如果节点有primary，则调用下面这个函数
def _with_primary(max_staleness, selection):
"""Apply max_staleness, in seconds, to a Selection with a known primary."""
primary = selection.primary
sds = []
for s in selection.server_descriptions:
if s.server_type == SERVER_TYPE.RSSecondary:
# See max-staleness.rst for explanation of this formula.
staleness = (
(s.last_update_time - s.last_write_date) -
(primary.last_update_time - primary.last_write_date) +
selection.heartbeat_frequency)
if staleness <= max_staleness:
sds.append(s)
else:
sds.append(s)
return selection.with_server_descriptions(sds)
上面的代码用到了IsMaster的last_write_date属性，正是用这个属性来判断staleness。
公式的解释可参考max-staleness.rst
个人觉得可以这么理解：假设网络延时一致，如果在同一时刻收到心跳回复，那么只用P.lastWriteDate - S.lastWriteDate就行了，但心跳时间不同，所以得算上时间差。我会写成(P.lastWriteDate - S.lastWriteDate) + (S.lastUpdateTime - P.lastUpdateTime) 。加上 心跳间隔是基于悲观假设，如果刚心跳完之后secondary就停止复制，那么在下一次心跳之前最多的stale程度就得加上 心跳间隔。
从代码可以看到Nearest找出了所有可读的节点，然后通过apply_local_threshold函数来刷选出最近的。