从PyMongo看MongoDB Read Preference

  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不一样的是，Read Preference基本上彻底由MongoDb Driver实现，所以，本文经过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及如下的MongoDB。

  本文地址：http://www.javashuo.com/article/p-cwetbpre-bb.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，读操做路由到哪一个mongod节点，若是使用Sharded Cluster，路由选择由Mongos决定，若是直接使用replica set，那么路由选择由driver决定。以下图所示：

  MongoDB提供了如下Read Preference Mode：

• primary：默认模式，一切读操做都路由到replica set的primary节点
• primaryPreferred：正常状况下都是路由到primary节点，只有当primary节点不可用（failover）的时候，才路由到secondary节点。
• secondary：一切读操做都路由到replica set的secondary节点
• secondaryPreferred：正常状况下都是路由到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，不论是primary仍是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。

  不一样的read Preference mode适合不一样的应用场景，若是数据的一致性很重要，好比必须保证read-after-write一致性，那么就须要从primary读，由于secondary的数据有必定的滞后。若是能接受必定程度的stale data，那么从secondary读数据能够减轻primary的压力，且在primary failover期间也能提供服务，可用性更高。若是对延时敏感，那么适合nearest。另外，经过tagsets，还能够有更丰富的定制化读取策略，好比指定从某些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的文档给出了如何链接到复制集：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')

  上述操做是non-blocking，当即返回，经过后台线程去链接指定节点，PyMongo链接到节点后，会从mongod节点获取到复制集内其余节点的信息，而后再链接到复制集内的其余节点。

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)])

  能够看到，刚初始化MongoClient实例时，并无链接到任何节点(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，建立MongoClient后，还没有链接到复制集节点以前，可否当即操做数据库？

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.

  经过后续的代码分析能够看到，会经过一个条件变量（threading.Condition）去协调。

PyMongo Monitor

  上面提到，初始化MongoClient对象的时候，会经过指定的mognod节点去发现复制集内的其余节点，这个就是经过monitor.Monitor来实现的。从上面的类图能够看到，每个server（与一个mongod节点对应）都有一个monitor。Monitor的做用在于：

• 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）经过socket链接Pool给对应的mongod节点发送 ismaster 消息。核心代码（略做调整)以下

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，复制集中的全部节点
• 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，链接到新增的节点，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。以一种状况为例：收到一个ismaster command response，对方自称本身是primary，无论当前topology有没有primary，都会进入调用如下函数

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

• 是否是同一个复制集
• 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
• 若是topology中已经有stale primary，那么将其server-type改为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全部节点的ismaster消息，Source of Truth在于复制集，并且这个Truth来自于majority 节点。所以，某个节点返回给driver的信息多是过时的、错误的，driver经过有限的信息判断复制集的状态，若是判断失误，好比将写操做发到了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。

  咱们从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，而后经过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

  能够看到，不必定能一次选出来，若是选不出server，意味着此时尚未链接到足够多的mongod节点，那么等待一段时间（_condition.wait）重试。在上面Topology.on_change 能够看到，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，而后再用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，若是节点有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

  我的以为能够这么理解：假设网络延时一致，若是在同一时刻收到心跳回复，那么只用P.lastWriteDate - S.lastWriteDate就好了，但心跳时间不一样，因此得算上时间差。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，若是刚心跳完以后secondary就中止复制，那么在下一次心跳以前最多的stale程度就得加上 心跳间隔。

  从代码能够看到Nearest找出了全部可读的节点，而后经过apply_local_threshold函数来刷选出最近的。

references

Read preference

PyMongo 3.6.0 Documentation