Source code for cassandra.policies

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from itertools import islice, cycle, groupby, repeat
import logging
from random import randint, shuffle
from threading import Lock
import socket

from cassandra import ConsistencyLevel, OperationTimedOut

log = logging.getLogger(__name__)


[docs]class HostDistance(object): """ A measure of how "distant" a node is from the client, which may influence how the load balancer distributes requests and how many connections are opened to the node. """ IGNORED = -1 """ A node with this distance should never be queried or have connections opened to it. """ LOCAL = 0 """ Nodes with ``LOCAL`` distance will be preferred for operations under some load balancing policies (such as :class:`.DCAwareRoundRobinPolicy`) and will have a greater number of connections opened against them by default. This distance is typically used for nodes within the same datacenter as the client. """ REMOTE = 1 """ Nodes with ``REMOTE`` distance will be treated as a last resort by some load balancing policies (such as :class:`.DCAwareRoundRobinPolicy`) and will have a smaller number of connections opened against them by default. This distance is typically used for nodes outside of the datacenter that the client is running in. """
class HostStateListener(object): def on_up(self, host): """ Called when a node is marked up. """ raise NotImplementedError() def on_down(self, host): """ Called when a node is marked down. """ raise NotImplementedError() def on_add(self, host): """ Called when a node is added to the cluster. The newly added node should be considered up. """ raise NotImplementedError() def on_remove(self, host): """ Called when a node is removed from the cluster. """ raise NotImplementedError()
[docs]class LoadBalancingPolicy(HostStateListener): """ Load balancing policies are used to decide how to distribute requests among all possible coordinator nodes in the cluster. In particular, they may focus on querying "near" nodes (those in a local datacenter) or on querying nodes who happen to be replicas for the requested data. You may also use subclasses of :class:`.LoadBalancingPolicy` for custom behavior. """ _hosts_lock = None def __init__(self): self._hosts_lock = Lock()
[docs] def distance(self, host): """ Returns a measure of how remote a :class:`~.pool.Host` is in terms of the :class:`.HostDistance` enums. """ raise NotImplementedError()
[docs] def populate(self, cluster, hosts): """ This method is called to initialize the load balancing policy with a set of :class:`.Host` instances before its first use. The `cluster` parameter is an instance of :class:`.Cluster`. """ raise NotImplementedError()
[docs] def make_query_plan(self, working_keyspace=None, query=None): """ Given a :class:`~.query.Statement` instance, return a iterable of :class:`.Host` instances which should be queried in that order. A generator may work well for custom implementations of this method. Note that the `query` argument may be :const:`None` when preparing statements. `working_keyspace` should be the string name of the current keyspace, as set through :meth:`.Session.set_keyspace()` or with a ``USE`` statement. """ raise NotImplementedError()
[docs] def check_supported(self): """ This will be called after the cluster Metadata has been initialized. If the load balancing policy implementation cannot be supported for some reason (such as a missing C extension), this is the point at which it should raise an exception. """ pass
[docs]class RoundRobinPolicy(LoadBalancingPolicy): """ A subclass of :class:`.LoadBalancingPolicy` which evenly distributes queries across all nodes in the cluster, regardless of what datacenter the nodes may be in. This load balancing policy is used by default. """ _live_hosts = frozenset(()) _position = 0 def populate(self, cluster, hosts): self._live_hosts = frozenset(hosts) if len(hosts) > 1: self._position = randint(0, len(hosts) - 1) def distance(self, host): return HostDistance.LOCAL def make_query_plan(self, working_keyspace=None, query=None): # not thread-safe, but we don't care much about lost increments # for the purposes of load balancing pos = self._position self._position += 1 hosts = self._live_hosts length = len(hosts) if length: pos %= length return islice(cycle(hosts), pos, pos + length) else: return [] def on_up(self, host): with self._hosts_lock: self._live_hosts = self._live_hosts.union((host, )) def on_down(self, host): with self._hosts_lock: self._live_hosts = self._live_hosts.difference((host, )) def on_add(self, host): with self._hosts_lock: self._live_hosts = self._live_hosts.union((host, )) def on_remove(self, host): with self._hosts_lock: self._live_hosts = self._live_hosts.difference((host, ))
[docs]class DCAwareRoundRobinPolicy(LoadBalancingPolicy): """ Similar to :class:`.RoundRobinPolicy`, but prefers hosts in the local datacenter and only uses nodes in remote datacenters as a last resort. """ local_dc = None used_hosts_per_remote_dc = 0 def __init__(self, local_dc='', used_hosts_per_remote_dc=0): """ The `local_dc` parameter should be the name of the datacenter (such as is reported by ``nodetool ring``) that should be considered local. If not specified, the driver will choose a local_dc based on the first host among :attr:`.Cluster.contact_points` having a valid DC. If relying on this mechanism, all specified contact points should be nodes in a single, local DC. `used_hosts_per_remote_dc` controls how many nodes in each remote datacenter will have connections opened against them. In other words, `used_hosts_per_remote_dc` hosts will be considered :attr:`~.HostDistance.REMOTE` and the rest will be considered :attr:`~.HostDistance.IGNORED`. By default, all remote hosts are ignored. """ self.local_dc = local_dc self.used_hosts_per_remote_dc = used_hosts_per_remote_dc self._dc_live_hosts = {} self._position = 0 self._contact_points = [] LoadBalancingPolicy.__init__(self) def _dc(self, host): return host.datacenter or self.local_dc def populate(self, cluster, hosts): for dc, dc_hosts in groupby(hosts, lambda h: self._dc(h)): self._dc_live_hosts[dc] = tuple(set(dc_hosts)) if not self.local_dc: self._contact_points = cluster.contact_points_resolved self._position = randint(0, len(hosts) - 1) if hosts else 0 def distance(self, host): dc = self._dc(host) if dc == self.local_dc: return HostDistance.LOCAL if not self.used_hosts_per_remote_dc: return HostDistance.IGNORED else: dc_hosts = self._dc_live_hosts.get(dc) if not dc_hosts: return HostDistance.IGNORED if host in list(dc_hosts)[:self.used_hosts_per_remote_dc]: return HostDistance.REMOTE else: return HostDistance.IGNORED def make_query_plan(self, working_keyspace=None, query=None): # not thread-safe, but we don't care much about lost increments # for the purposes of load balancing pos = self._position self._position += 1 local_live = self._dc_live_hosts.get(self.local_dc, ()) pos = (pos % len(local_live)) if local_live else 0 for host in islice(cycle(local_live), pos, pos + len(local_live)): yield host # the dict can change, so get candidate DCs iterating over keys of a copy other_dcs = [dc for dc in self._dc_live_hosts.copy().keys() if dc != self.local_dc] for dc in other_dcs: remote_live = self._dc_live_hosts.get(dc, ()) for host in remote_live[:self.used_hosts_per_remote_dc]: yield host def on_up(self, host): # not worrying about threads because this will happen during # control connection startup/refresh if not self.local_dc and host.datacenter: if host.address in self._contact_points: self.local_dc = host.datacenter log.info("Using datacenter '%s' for DCAwareRoundRobinPolicy (via host '%s'); " "if incorrect, please specify a local_dc to the constructor, " "or limit contact points to local cluster nodes" % (self.local_dc, host.address)) del self._contact_points dc = self._dc(host) with self._hosts_lock: current_hosts = self._dc_live_hosts.get(dc, ()) if host not in current_hosts: self._dc_live_hosts[dc] = current_hosts + (host, ) def on_down(self, host): dc = self._dc(host) with self._hosts_lock: current_hosts = self._dc_live_hosts.get(dc, ()) if host in current_hosts: hosts = tuple(h for h in current_hosts if h != host) if hosts: self._dc_live_hosts[dc] = hosts else: del self._dc_live_hosts[dc] def on_add(self, host): self.on_up(host) def on_remove(self, host): self.on_down(host)
[docs]class TokenAwarePolicy(LoadBalancingPolicy): """ A :class:`.LoadBalancingPolicy` wrapper that adds token awareness to a child policy. This alters the child policy's behavior so that it first attempts to send queries to :attr:`~.HostDistance.LOCAL` replicas (as determined by the child policy) based on the :class:`.Statement`'s :attr:`~.Statement.routing_key`. If :attr:`.shuffle_replicas` is truthy, these replicas will be yielded in a random order. Once those hosts are exhausted, the remaining hosts in the child policy's query plan will be used in the order provided by the child policy. If no :attr:`~.Statement.routing_key` is set on the query, the child policy's query plan will be used as is. """ _child_policy = None _cluster_metadata = None shuffle_replicas = False """ Yield local replicas in a random order. """ def __init__(self, child_policy, shuffle_replicas=False): self._child_policy = child_policy self.shuffle_replicas = shuffle_replicas def populate(self, cluster, hosts): self._cluster_metadata = cluster.metadata self._child_policy.populate(cluster, hosts) def check_supported(self): if not self._cluster_metadata.can_support_partitioner(): raise RuntimeError( '%s cannot be used with the cluster partitioner (%s) because ' 'the relevant C extension for this driver was not compiled. ' 'See the installation instructions for details on building ' 'and installing the C extensions.' % (self.__class__.__name__, self._cluster_metadata.partitioner)) def distance(self, *args, **kwargs): return self._child_policy.distance(*args, **kwargs) def make_query_plan(self, working_keyspace=None, query=None): if query and query.keyspace: keyspace = query.keyspace else: keyspace = working_keyspace child = self._child_policy if query is None: for host in child.make_query_plan(keyspace, query): yield host else: routing_key = query.routing_key if routing_key is None or keyspace is None: for host in child.make_query_plan(keyspace, query): yield host else: replicas = self._cluster_metadata.get_replicas(keyspace, routing_key) if self.shuffle_replicas: shuffle(replicas) for replica in replicas: if replica.is_up and \ child.distance(replica) == HostDistance.LOCAL: yield replica for host in child.make_query_plan(keyspace, query): # skip if we've already listed this host if host not in replicas or \ child.distance(host) == HostDistance.REMOTE: yield host def on_up(self, *args, **kwargs): return self._child_policy.on_up(*args, **kwargs) def on_down(self, *args, **kwargs): return self._child_policy.on_down(*args, **kwargs) def on_add(self, *args, **kwargs): return self._child_policy.on_add(*args, **kwargs) def on_remove(self, *args, **kwargs): return self._child_policy.on_remove(*args, **kwargs)
[docs]class WhiteListRoundRobinPolicy(RoundRobinPolicy): """ A subclass of :class:`.RoundRobinPolicy` which evenly distributes queries across all nodes in the cluster, regardless of what datacenter the nodes may be in, but only if that node exists in the list of allowed nodes This policy is addresses the issue described in https://datastax-oss.atlassian.net/browse/JAVA-145 Where connection errors occur when connection attempts are made to private IP addresses remotely """ def __init__(self, hosts): """ The `hosts` parameter should be a sequence of hosts to permit connections to. """ self._allowed_hosts = hosts self._allowed_hosts_resolved = [endpoint[4][0] for a in self._allowed_hosts for endpoint in socket.getaddrinfo(a, None, socket.AF_UNSPEC, socket.SOCK_STREAM)] RoundRobinPolicy.__init__(self) def populate(self, cluster, hosts): self._live_hosts = frozenset(h for h in hosts if h.address in self._allowed_hosts_resolved) if len(hosts) <= 1: self._position = 0 else: self._position = randint(0, len(hosts) - 1) def distance(self, host): if host.address in self._allowed_hosts_resolved: return HostDistance.LOCAL else: return HostDistance.IGNORED def on_up(self, host): if host.address in self._allowed_hosts_resolved: RoundRobinPolicy.on_up(self, host) def on_add(self, host): if host.address in self._allowed_hosts_resolved: RoundRobinPolicy.on_add(self, host)
[docs]class HostFilterPolicy(LoadBalancingPolicy): """ A :class:`.LoadBalancingPolicy` subclass configured with a child policy, and a single-argument predicate. This policy defers to the child policy for hosts where ``predicate(host)`` is truthy. Hosts for which ``predicate(host)`` is falsey will be considered :attr:`.IGNORED`, and will not be used in a query plan. This can be used in the cases where you need a whitelist or blacklist policy, e.g. to prepare for decommissioning nodes or for testing: .. code-block:: python def address_is_ignored(host): return host.address in [ignored_address0, ignored_address1] blacklist_filter_policy = HostFilterPolicy( child_policy=RoundRobinPolicy(), predicate=address_is_ignored ) cluster = Cluster( primary_host, load_balancing_policy=blacklist_filter_policy, ) See the note in the :meth:`.make_query_plan` documentation for a caveat on how wrapping ordering polices (e.g. :class:`.RoundRobinPolicy`) may break desirable properties of the wrapped policy. Please note that whitelist and blacklist policies are not recommended for general, day-to-day use. You probably want something like :class:`.DCAwareRoundRobinPolicy`, which prefers a local DC but has fallbacks, over a brute-force method like whitelisting or blacklisting. """ def __init__(self, child_policy, predicate): """ :param child_policy: an instantiated :class:`.LoadBalancingPolicy` that this one will defer to. :param predicate: a one-parameter function that takes a :class:`.Host`. If it returns a falsey value, the :class:`.Host` will be :attr:`.IGNORED` and not returned in query plans. """ super(HostFilterPolicy, self).__init__() self._child_policy = child_policy self._predicate = predicate def on_up(self, host, *args, **kwargs): return self._child_policy.on_up(host, *args, **kwargs) def on_down(self, host, *args, **kwargs): return self._child_policy.on_down(host, *args, **kwargs) def on_add(self, host, *args, **kwargs): return self._child_policy.on_add(host, *args, **kwargs) def on_remove(self, host, *args, **kwargs): return self._child_policy.on_remove(host, *args, **kwargs) @property def predicate(self): """ A predicate, set on object initialization, that takes a :class:`.Host` and returns a value. If the value is falsy, the :class:`.Host` is :class:`~HostDistance.IGNORED`. If the value is truthy, :class:`.HostFilterPolicy` defers to the child policy to determine the host's distance. This is a read-only value set in ``__init__``, implemented as a ``property``. """ return self._predicate
[docs] def distance(self, host): """ Checks if ``predicate(host)``, then returns :attr:`~HostDistance.IGNORED` if falsey, and defers to the child policy otherwise. """ if self.predicate(host): return self._child_policy.distance(host) else: return HostDistance.IGNORED
def populate(self, cluster, hosts): self._child_policy.populate(cluster=cluster, hosts=hosts)
[docs] def make_query_plan(self, working_keyspace=None, query=None): """ Defers to the child policy's :meth:`.LoadBalancingPolicy.make_query_plan` and filters the results. Note that this filtering may break desirable properties of the wrapped policy in some cases. For instance, imagine if you configure this policy to filter out ``host2``, and to wrap a round-robin policy that rotates through three hosts in the order ``host1, host2, host3``, ``host2, host3, host1``, ``host3, host1, host2``, repeating. This policy will yield ``host1, host3``, ``host3, host1``, ``host3, host1``, disproportionately favoring ``host3``. """ child_qp = self._child_policy.make_query_plan( working_keyspace=working_keyspace, query=query ) for host in child_qp: if self.predicate(host): yield host
def check_supported(self): return self._child_policy.check_supported()
[docs]class ConvictionPolicy(object): """ A policy which decides when hosts should be considered down based on the types of failures and the number of failures. If custom behavior is needed, this class may be subclassed. """ def __init__(self, host): """ `host` is an instance of :class:`.Host`. """ self.host = host
[docs] def add_failure(self, connection_exc): """ Implementations should return :const:`True` if the host should be convicted, :const:`False` otherwise. """ raise NotImplementedError()
[docs] def reset(self): """ Implementations should clear out any convictions or state regarding the host. """ raise NotImplementedError()
[docs]class SimpleConvictionPolicy(ConvictionPolicy): """ The default implementation of :class:`ConvictionPolicy`, which simply marks a host as down after the first failure of any kind. """ def add_failure(self, connection_exc): return not isinstance(connection_exc, OperationTimedOut) def reset(self): pass
[docs]class ReconnectionPolicy(object): """ This class and its subclasses govern how frequently an attempt is made to reconnect to nodes that are marked as dead. If custom behavior is needed, this class may be subclassed. """
[docs] def new_schedule(self): """ This should return a finite or infinite iterable of delays (each as a floating point number of seconds) inbetween each failed reconnection attempt. Note that if the iterable is finite, reconnection attempts will cease once the iterable is exhausted. """ raise NotImplementedError()
[docs]class ConstantReconnectionPolicy(ReconnectionPolicy): """ A :class:`.ReconnectionPolicy` subclass which sleeps for a fixed delay inbetween each reconnection attempt. """ def __init__(self, delay, max_attempts=64): """ `delay` should be a floating point number of seconds to wait inbetween each attempt. `max_attempts` should be a total number of attempts to be made before giving up, or :const:`None` to continue reconnection attempts forever. The default is 64. """ if delay < 0: raise ValueError("delay must not be negative") if max_attempts is not None and max_attempts < 0: raise ValueError("max_attempts must not be negative") self.delay = delay self.max_attempts = max_attempts def new_schedule(self): if self.max_attempts: return repeat(self.delay, self.max_attempts) return repeat(self.delay)
[docs]class ExponentialReconnectionPolicy(ReconnectionPolicy): """ A :class:`.ReconnectionPolicy` subclass which exponentially increases the length of the delay inbetween each reconnection attempt up to a set maximum delay. """ # TODO: max_attempts is 64 to preserve legacy default behavior # consider changing to None in major release to prevent the policy # giving up forever def __init__(self, base_delay, max_delay, max_attempts=64): """ `base_delay` and `max_delay` should be in floating point units of seconds. `max_attempts` should be a total number of attempts to be made before giving up, or :const:`None` to continue reconnection attempts forever. The default is 64. """ if base_delay < 0 or max_delay < 0: raise ValueError("Delays may not be negative") if max_delay < base_delay: raise ValueError("Max delay must be greater than base delay") if max_attempts is not None and max_attempts < 0: raise ValueError("max_attempts must not be negative") self.base_delay = base_delay self.max_delay = max_delay self.max_attempts = max_attempts def new_schedule(self): i, overflowed = 0, False while self.max_attempts is None or i < self.max_attempts: if overflowed: yield self.max_delay else: try: yield min(self.base_delay * (2 ** i), self.max_delay) except OverflowError: overflowed = True yield self.max_delay i += 1
[docs]class WriteType(object): """ For usage with :class:`.RetryPolicy`, this describe a type of write operation. """ SIMPLE = 0 """ A write to a single partition key. Such writes are guaranteed to be atomic and isolated. """ BATCH = 1 """ A write to multiple partition keys that used the distributed batch log to ensure atomicity. """ UNLOGGED_BATCH = 2 """ A write to multiple partition keys that did not use the distributed batch log. Atomicity for such writes is not guaranteed. """ COUNTER = 3 """ A counter write (for one or multiple partition keys). Such writes should not be replayed in order to avoid overcount. """ BATCH_LOG = 4 """ The initial write to the distributed batch log that Cassandra performs internally before a BATCH write. """ CAS = 5 """ A lighweight-transaction write, such as "DELETE ... IF EXISTS". """ VIEW = 6 """ This WriteType is only seen in results for requests that were unable to complete MV operations. """ CDC = 7 """ This WriteType is only seen in results for requests that were unable to complete CDC operations. """
WriteType.name_to_value = { 'SIMPLE': WriteType.SIMPLE, 'BATCH': WriteType.BATCH, 'UNLOGGED_BATCH': WriteType.UNLOGGED_BATCH, 'COUNTER': WriteType.COUNTER, 'BATCH_LOG': WriteType.BATCH_LOG, 'CAS': WriteType.CAS, 'VIEW': WriteType.VIEW, 'CDC': WriteType.CDC }
[docs]class RetryPolicy(object): """ A policy that describes whether to retry, rethrow, or ignore coordinator timeout and unavailable failures. These are failures reported from the server side. Timeouts are configured by `settings in cassandra.yaml <https://github.com/apache/cassandra/blob/cassandra-2.1.4/conf/cassandra.yaml#L568-L584>`_. Unavailable failures occur when the coordinator cannot acheive the consistency level for a request. For further information see the method descriptions below. To specify a default retry policy, set the :attr:`.Cluster.default_retry_policy` attribute to an instance of this class or one of its subclasses. To specify a retry policy per query, set the :attr:`.Statement.retry_policy` attribute to an instance of this class or one of its subclasses. If custom behavior is needed for retrying certain operations, this class may be subclassed. """ RETRY = 0 """ This should be returned from the below methods if the operation should be retried on the same connection. """ RETHROW = 1 """ This should be returned from the below methods if the failure should be propagated and no more retries attempted. """ IGNORE = 2 """ This should be returned from the below methods if the failure should be ignored but no more retries should be attempted. """ RETRY_NEXT_HOST = 3 """ This should be returned from the below methods if the operation should be retried on another connection. """
[docs] def on_read_timeout(self, query, consistency, required_responses, received_responses, data_retrieved, retry_num): """ This is called when a read operation times out from the coordinator's perspective (i.e. a replica did not respond to the coordinator in time). It should return a tuple with two items: one of the class enums (such as :attr:`.RETRY`) and a :class:`.ConsistencyLevel` to retry the operation at or :const:`None` to keep the same consistency level. `query` is the :class:`.Statement` that timed out. `consistency` is the :class:`.ConsistencyLevel` that the operation was attempted at. The `required_responses` and `received_responses` parameters describe how many replicas needed to respond to meet the requested consistency level and how many actually did respond before the coordinator timed out the request. `data_retrieved` is a boolean indicating whether any of those responses contained data (as opposed to just a digest). `retry_num` counts how many times the operation has been retried, so the first time this method is called, `retry_num` will be 0. By default, operations will be retried at most once, and only if a sufficient number of replicas responded (with data digests). """ if retry_num != 0: return self.RETHROW, None elif received_responses >= required_responses and not data_retrieved: return self.RETRY, consistency else: return self.RETHROW, None
[docs] def on_write_timeout(self, query, consistency, write_type, required_responses, received_responses, retry_num): """ This is called when a write operation times out from the coordinator's perspective (i.e. a replica did not respond to the coordinator in time). `query` is the :class:`.Statement` that timed out. `consistency` is the :class:`.ConsistencyLevel` that the operation was attempted at. `write_type` is one of the :class:`.WriteType` enums describing the type of write operation. The `required_responses` and `received_responses` parameters describe how many replicas needed to acknowledge the write to meet the requested consistency level and how many replicas actually did acknowledge the write before the coordinator timed out the request. `retry_num` counts how many times the operation has been retried, so the first time this method is called, `retry_num` will be 0. By default, failed write operations will retried at most once, and they will only be retried if the `write_type` was :attr:`~.WriteType.BATCH_LOG`. """ if retry_num != 0: return self.RETHROW, None elif write_type == WriteType.BATCH_LOG: return self.RETRY, consistency else: return self.RETHROW, None
[docs] def on_unavailable(self, query, consistency, required_replicas, alive_replicas, retry_num): """ This is called when the coordinator node determines that a read or write operation cannot be successful because the number of live replicas are too low to meet the requested :class:`.ConsistencyLevel`. This means that the read or write operation was never forwared to any replicas. `query` is the :class:`.Statement` that failed. `consistency` is the :class:`.ConsistencyLevel` that the operation was attempted at. `required_replicas` is the number of replicas that would have needed to acknowledge the operation to meet the requested consistency level. `alive_replicas` is the number of replicas that the coordinator considered alive at the time of the request. `retry_num` counts how many times the operation has been retried, so the first time this method is called, `retry_num` will be 0. By default, no retries will be attempted and the error will be re-raised. """ return (self.RETRY_NEXT_HOST, consistency) if retry_num == 0 else (self.RETHROW, None)
[docs]class FallthroughRetryPolicy(RetryPolicy): """ A retry policy that never retries and always propagates failures to the application. """ def on_read_timeout(self, *args, **kwargs): return self.RETHROW, None def on_write_timeout(self, *args, **kwargs): return self.RETHROW, None def on_unavailable(self, *args, **kwargs): return self.RETHROW, None
[docs]class DowngradingConsistencyRetryPolicy(RetryPolicy): """ A retry policy that sometimes retries with a lower consistency level than the one initially requested. **BEWARE**: This policy may retry queries using a lower consistency level than the one initially requested. By doing so, it may break consistency guarantees. In other words, if you use this retry policy, there are cases (documented below) where a read at :attr:`~.QUORUM` *may not* see a preceding write at :attr:`~.QUORUM`. Do not use this policy unless you have understood the cases where this can happen and are ok with that. It is also recommended to subclass this class so that queries that required a consistency level downgrade can be recorded (so that repairs can be made later, etc). This policy implements the same retries as :class:`.RetryPolicy`, but on top of that, it also retries in the following cases: * On a read timeout: if the number of replicas that responded is greater than one but lower than is required by the requested consistency level, the operation is retried at a lower consistency level. * On a write timeout: if the operation is an :attr:`~.UNLOGGED_BATCH` and at least one replica acknowledged the write, the operation is retried at a lower consistency level. Furthermore, for other write types, if at least one replica acknowledged the write, the timeout is ignored. * On an unavailable exception: if at least one replica is alive, the operation is retried at a lower consistency level. The reasoning behind this retry policy is as follows: if, based on the information the Cassandra coordinator node returns, retrying the operation with the initially requested consistency has a chance to succeed, do it. Otherwise, if based on that information we know the initially requested consistency level cannot be achieved currently, then: * For writes, ignore the exception (thus silently failing the consistency requirement) if we know the write has been persisted on at least one replica. * For reads, try reading at a lower consistency level (thus silently failing the consistency requirement). In other words, this policy implements the idea that if the requested consistency level cannot be achieved, the next best thing for writes is to make sure the data is persisted, and that reading something is better than reading nothing, even if there is a risk of reading stale data. """ def _pick_consistency(self, num_responses): if num_responses >= 3: return self.RETRY, ConsistencyLevel.THREE elif num_responses >= 2: return self.RETRY, ConsistencyLevel.TWO elif num_responses >= 1: return self.RETRY, ConsistencyLevel.ONE else: return self.RETHROW, None def on_read_timeout(self, query, consistency, required_responses, received_responses, data_retrieved, retry_num): if retry_num != 0: return self.RETHROW, None elif received_responses < required_responses: return self._pick_consistency(received_responses) elif not data_retrieved: return self.RETRY, consistency else: return self.RETHROW, None def on_write_timeout(self, query, consistency, write_type, required_responses, received_responses, retry_num): if retry_num != 0: return self.RETHROW, None if write_type in (WriteType.SIMPLE, WriteType.BATCH, WriteType.COUNTER): if received_responses > 0: # persisted on at least one replica return self.IGNORE, None else: return self.RETHROW, None elif write_type == WriteType.UNLOGGED_BATCH: return self._pick_consistency(received_responses) elif write_type == WriteType.BATCH_LOG: return self.RETRY, consistency return self.RETHROW, None def on_unavailable(self, query, consistency, required_replicas, alive_replicas, retry_num): if retry_num != 0: return self.RETHROW, None else: return self._pick_consistency(alive_replicas)
[docs]class AddressTranslator(object): """ Interface for translating cluster-defined endpoints. The driver discovers nodes using server metadata and topology change events. Normally, the endpoint defined by the server is the right way to connect to a node. In some environments, these addresses may not be reachable, or not preferred (public vs. private IPs in cloud environments, suboptimal routing, etc). This interface allows for translating from server defined endpoints to preferred addresses for driver connections. *Note:* :attr:`~Cluster.contact_points` provided while creating the :class:`~.Cluster` instance are not translated using this mechanism -- only addresses received from Cassandra nodes are. """
[docs] def translate(self, addr): """ Accepts the node ip address, and returns a translated address to be used connecting to this node. """ raise NotImplementedError()
[docs]class IdentityTranslator(AddressTranslator): """ Returns the endpoint with no translation """ def translate(self, addr): return addr
[docs]class EC2MultiRegionTranslator(AddressTranslator): """ Resolves private ips of the hosts in the same datacenter as the client, and public ips of hosts in other datacenters. """
[docs] def translate(self, addr): """ Reverse DNS the public broadcast_address, then lookup that hostname to get the AWS-resolved IP, which will point to the private IP address within the same datacenter. """ # get family of this address so we translate to the same family = socket.getaddrinfo(addr, 0, socket.AF_UNSPEC, socket.SOCK_STREAM)[0][0] host = socket.getfqdn(addr) for a in socket.getaddrinfo(host, 0, family, socket.SOCK_STREAM): try: return a[4][0] except Exception: pass return addr
[docs]class SpeculativeExecutionPolicy(object): """ Interface for specifying speculative execution plans """
[docs] def new_plan(self, keyspace, statement): """ Returns :param keyspace: :param statement: :return: """ raise NotImplementedError()
class SpeculativeExecutionPlan(object): def next_execution(self, host): raise NotImplementedError() class NoSpeculativeExecutionPlan(SpeculativeExecutionPlan): def next_execution(self, host): return -1 class NoSpeculativeExecutionPolicy(SpeculativeExecutionPolicy): def new_plan(self, keyspace, statement): return NoSpeculativeExecutionPlan()
[docs]class ConstantSpeculativeExecutionPolicy(SpeculativeExecutionPolicy): """ A speculative execution policy that sends a new query every X seconds (**delay**) for a maximum of Y attempts (**max_attempts**). """ def __init__(self, delay, max_attempts): self.delay = delay self.max_attempts = max_attempts class ConstantSpeculativeExecutionPlan(SpeculativeExecutionPlan): def __init__(self, delay, max_attempts): self.delay = delay self.remaining = max_attempts def next_execution(self, host): if self.remaining > 0: self.remaining -= 1 return self.delay else: return -1 def new_plan(self, keyspace, statement): return self.ConstantSpeculativeExecutionPlan(self.delay, self.max_attempts)