cassandra.cluster
- Clusters and Sessions
class Cluster
The main class to use when interacting with a Cassandra cluster. Typically, one instance of this class will be created for each separate Cassandra cluster that your application interacts with.
Example usage:
>>> from cassandra.cluster import Cluster
>>> cluster = Cluster(['192.168.1.1', '192.168.1.2'])
>>> session = cluster.connect()
>>> session.execute("CREATE KEYSPACE ...")
>>> ...
>>> cluster.shutdown()
Cluster
and Session
also provide context management functions
which implicitly handle shutdown when leaving scope.
executor_threads
defines the number of threads in a pool for handling asynchronous tasks such as
extablishing connection pools or refreshing metadata.
Any of the mutable Cluster attributes may be set as keyword arguments to the constructor.
Attributes
contact_points
= [‘127.0.0.1’]The list of contact points to try connecting for cluster discovery.
Defaults to loopback interface.
Note: When using DCAwareLoadBalancingPolicy
with no explicit
local_dc set (as is the default), the DC is chosen from an arbitrary
host in contact_points. In this case, contact_points should contain
only nodes from a single, local DC.
Note: In the next major version, if you specify contact points, you will also be required to also explicitly specify a load-balancing policy. This change will help prevent cases where users had hard-to-debug issues surrounding unintuitive default load-balancing policy behavior.
port
= 9042The server-side port to open connections to. Defaults to 9042.
cql_version
= NoneIf a specific version of CQL should be used, this may be set to that string version. Otherwise, the highest CQL version supported by the server will be automatically used.
protocol_version
= 4The maximum version of the native protocol to use.
See ProtocolVersion
for more information about versions.
If not set in the constructor, the driver will automatically downgrade version based on a negotiation with the server, but it is most efficient to set this to the maximum supported by your version of Cassandra. Setting this will also prevent conflicting versions negotiated if your cluster is upgraded.
compression
= TrueControls compression for communications between the driver and Cassandra.
If left as the default of True
, either lz4 or snappy compression
may be used, depending on what is supported by both the driver
and Cassandra. If both are fully supported, lz4 will be preferred.
You may also set this to ‘snappy’ or ‘lz4’ to request that specific compression type.
Setting this to False
disables compression.
auth_provider
When protocol_version
is 2 or higher, this should
be an instance of a subclass of AuthProvider
,
such as PlainTextAuthProvider
.
When protocol_version
is 1, this should be
a function that accepts one argument, the IP address of a node,
and returns a dict of credentials for that node.
When not using authentication, this should be left as None
.
load_balancing_policy
An instance of policies.LoadBalancingPolicy
or
one of its subclasses.
Defaults to TokenAwarePolicy
(DCAwareRoundRobinPolicy
).
when using CPython (where the murmur3 extension is available). DCAwareRoundRobinPolicy
otherwise. Default local DC will be chosen from contact points.
Please see DCAwareRoundRobinPolicy
for a discussion on default behavior with respect to
DC locality and remote nodes.
reconnection_policy
= <cassandra.policies.ExponentialReconnectionPolicy object>An instance of policies.ReconnectionPolicy
. Defaults to an instance
of ExponentialReconnectionPolicy
with a base delay of one second and
a max delay of ten minutes.
default_retry_policy
= <cassandra.policies.RetryPolicy object>A default policies.RetryPolicy
instance to use for all
Statement
objects which do not have a retry_policy
explicitly set.
conviction_policy_factory
= <class ‘cassandra.policies.SimpleConvictionPolicy’>A factory function which creates instances of
policies.ConvictionPolicy
. Defaults to
policies.SimpleConvictionPolicy
.
address_translator
= <cassandra.policies.IdentityTranslator object>policies.AddressTranslator
instance to be used in translating server node addresses
to driver connection addresses.
metrics_enabled
= FalseWhether or not metric collection is enabled. If enabled, metrics
will be an instance of Metrics
.
metrics
= NoneAn instance of cassandra.metrics.Metrics
if metrics_enabled
is
True
, else None
.
ssl_options
= NoneA optional dict which will be used as kwargs for ssl.wrap_socket()
when new sockets are created. This should be used when client encryption
is enabled in Cassandra.
By default, a ca_certs
value should be supplied (the value should be
a string pointing to the location of the CA certs file), and you probably
want to specify ssl_version
as ssl.PROTOCOL_TLSv1
to match
Cassandra’s default protocol.
In addition to wrap_socket
kwargs, clients may also specify 'check_hostname': True
to verify the cert hostname
as outlined in RFC 2818 and RFC 6125. Note that this requires the certificate to be transferred, so
should almost always require the option 'cert_reqs': ssl.CERT_REQUIRED
. Note also that this functionality was not built into
Python standard library until (2.7.9, 3.2). To enable this mechanism in earlier versions, patch ssl.match_hostname
with a custom or back-ported function.
sockopts
= NoneAn optional list of tuples which will be used as arguments to
socket.setsockopt()
for all created sockets.
Note: some drivers find setting TCPNODELAY beneficial in the context of
their execution model. It was not found generally beneficial for this driver.
To try with your own workload, set sockopts = [(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)]
max_schema_agreement_wait
= 10The maximum duration (in seconds) that the driver will wait for schema agreement across the cluster. Defaults to ten seconds. If set <= 0, the driver will bypass schema agreement waits altogether.
metadata
= NoneAn instance of cassandra.metadata.Metadata
.
connection_class
= <class ‘cassandra.io.asyncorereactor.AsyncoreConnection’>This determines what event loop system will be used for managing I/O with Cassandra. These are the current options:
-
cassandra.io.libevreactor.LibevConnection
-
cassandra.io.eventletreactor.EventletConnection
(requires monkey-patching - see doc for details) -
cassandra.io.geventreactor.GeventConnection
(requires monkey-patching - see doc for details) -
EXPERIMENTAL:
cassandra.io.asyncioreactor.AsyncioConnection
By default, AsyncoreConnection
will be used, which uses
the asyncore
module in the Python standard library.
If libev
is installed, LibevConnection
will be used instead.
If gevent
or eventlet
monkey-patching is detected, the corresponding
connection class will be used automatically.
AsyncioConnection
, which uses the asyncio
module in the Python
standard library, is also available, but currently experimental. Note that
it requires asyncio
features that were only introduced in the 3.4 line
in 3.4.6, and in the 3.5 line in 3.5.1.
control_connection_timeout
= 2.0A timeout, in seconds, for queries made by the control connection, such
as querying the current schema and information about nodes in the cluster.
If set to None
, there will be no timeout for these queries.
idle_heartbeat_interval
= 30Interval, in seconds, on which to heartbeat idle connections. This helps keep connections open through network devices that expire idle connections. It also helps discover bad connections early in low-traffic scenarios. Setting to zero disables heartbeats.
idle_heartbeat_timeout
= 30Timeout, in seconds, on which the heartbeat wait for idle connection responses. Lowering this value can help to discover bad connections earlier.
schema_event_refresh_window
= 2Window, in seconds, within which a schema component will be refreshed after receiving a schema_change event.
The driver delays a random amount of time in the range [0.0, window) before executing the refresh. This serves two purposes:
1.) Spread the refresh for deployments with large fanout from C* to client tier, preventing a ‘thundering herd’ problem with many clients refreshing simultaneously.
2.) Remove redundant refreshes. Redundant events arriving within the delay period are discarded, and only one refresh is executed.
Setting this to zero will execute refreshes immediately.
Setting this negative will disable schema refreshes in response to push events (refreshes will still occur in response to schema change responses to DDL statements executed by Sessions of this Cluster).
topology_event_refresh_window
= 10Window, in seconds, within which the node and token list will be refreshed after receiving a topology_change event.
Setting this to zero will execute refreshes immediately.
Setting this negative will disable node refreshes in response to push events.
See schema_event_refresh_window
for discussion of rationale
status_event_refresh_window
= 2Window, in seconds, within which the driver will start the reconnect after receiving a status_change event.
Setting this to zero will connect immediately.
This is primarily used to avoid ‘thundering herd’ in deployments with large fanout from cluster to clients.
When nodes come up, clients attempt to reprepare prepared statements (depending on reprepare_on_up
), and
establish connection pools. This can cause a rush of connections and queries if not mitigated with this factor.
prepare_on_all_hosts
= TrueSpecifies whether statements should be prepared on all hosts, or just one.
This can reasonably be disabled on long-running applications with numerous clients preparing statements on startup, where a randomized initial condition of the load balancing policy can be expected to distribute prepares from different clients across the cluster.
reprepare_on_up
= TrueSpecifies whether all known prepared statements should be prepared on a node when it comes up.
May be used to avoid overwhelming a node on return, or if it is supposed that the node was only marked down due to network. If statements are not reprepared, they are prepared on the first execution, causing an extra roundtrip for one or more client requests.
connect_timeout
= 5Timeout, in seconds, for creating new connections.
This timeout covers the entire connection negotiation, including TCP establishment, options passing, and authentication.
schema_metadata_enabled
= TrueFlag indicating whether internal schema metadata is updated.
When disabled, the driver does not populate Cluster.metadata.keyspaces on connect, or on schema change events. This can be used to speed initial connection, and reduce load on client and server during operation. Turning this off gives away token aware request routing, and programmatic inspection of the metadata model.
token_metadata_enabled
= TrueFlag indicating whether internal token metadata is updated.
When disabled, the driver does not query node token information on connect, or on topology change events. This can be used to speed initial connection, and reduce load on client and server during operation. It is most useful in large clusters using vnodes, where the token map can be expensive to compute. Turning this off gives away token aware request routing, and programmatic inspection of the token ring.
timestamp_generator
= NoneAn object, shared between all sessions created by this cluster instance,
that generates timestamps when client-side timestamp generation is enabled.
By default, each Cluster
uses a new
MonotonicTimestampGenerator
.
Applications can set this value for custom timestamp behavior. See the
documentation for Session.timestamp_generator()
.
Methods
connect
(keyspace=None, wait_for_all_pools=False)Creates and returns a new Session
object. If keyspace
is specified, that keyspace will be the default keyspace for
operations on the Session
.
shutdown
()Closes all sessions and connection associated with this Cluster. To ensure all connections are properly closed, you should always call shutdown() on a Cluster instance when you are done with it.
Once shutdown, a Cluster should not be used for any purpose.
register_user_type
(keyspace, user_type, klass)Registers a class to use to represent a particular user-defined type. Query parameters for this user-defined type will be assumed to be instances of klass. Result sets for this user-defined type will be instances of klass. If no class is registered for a user-defined type, a namedtuple will be used for result sets, and non-prepared statements may not encode parameters for this type correctly.
keyspace is the name of the keyspace that the UDT is defined in.
user_type is the string name of the UDT to register the mapping for.
klass should be a class with attributes whose names match the fields of the user-defined type. The constructor must accepts kwargs for each of the fields in the UDT.
This method should only be called after the type has been created within Cassandra.
Example:
cluster = Cluster(protocol_version=3)
session = cluster.connect()
session.set_keyspace('mykeyspace')
session.execute("CREATE TYPE address (street text, zipcode int)")
session.execute("CREATE TABLE users (id int PRIMARY KEY, location address)")
# create a class to map to the "address" UDT
class Address(object):
def __init__(self, street, zipcode):
self.street = street
self.zipcode = zipcode
cluster.register_user_type('mykeyspace', 'address', Address)
# insert a row using an instance of Address
session.execute("INSERT INTO users (id, location) VALUES (%s, %s)",
(0, Address("123 Main St.", 78723)))
# results will include Address instances
results = session.execute("SELECT * FROM users")
row = results[0]
print row.id, row.location.street, row.location.zipcode
register_listener
(listener)Adds a cassandra.policies.HostStateListener
subclass instance to
the list of listeners to be notified when a host is added, removed,
marked up, or marked down.
unregister_listener
(listener)Removes a registered listener.
add_execution_profile
(name, profile, pool_wait_timeout=5)Adds an ExecutionProfile
to the cluster. This makes it available for use by name
in Session.execute()
and Session.execute_async()
. This method will raise if the profile already exists.
Normally profiles will be injected at cluster initialization via Cluster(execution_profiles)
. This method
provides a way of adding them dynamically.
Adding a new profile updates the connection pools according to the specified load_balancing_policy
. By default,
this method will wait up to five seconds for the pool creation to complete, so the profile can be used immediately
upon return. This behavior can be controlled using pool_wait_timeout
(see
concurrent.futures.wait
for timeout semantics).
set_max_requests_per_connection
(host_distance, max_requests)Sets a threshold for concurrent requests per connection, above which new
connections will be created to a host (up to max connections;
see set_max_connections_per_host()
).
Pertains to connection pool management in protocol versions {1,2}.
get_max_requests_per_connection
(host_distance)set_min_requests_per_connection
(host_distance, min_requests)Sets a threshold for concurrent requests per connection, below which
connections will be considered for disposal (down to core connections;
see set_core_connections_per_host()
).
Pertains to connection pool management in protocol versions {1,2}.
get_min_requests_per_connection
(host_distance)get_core_connections_per_host
(host_distance)Gets the minimum number of connections per Session that will be opened
for each host with HostDistance
equal to host_distance.
The default is 2 for LOCAL
and 1 for
REMOTE
.
This property is ignored if protocol_version
is
3 or higher.
set_core_connections_per_host
(host_distance, core_connections)Sets the minimum number of connections per Session that will be opened
for each host with HostDistance
equal to host_distance.
The default is 2 for LOCAL
and 1 for
REMOTE
.
Protocol version 1 and 2 are limited in the number of concurrent requests they can send per connection. The driver implements connection pooling to support higher levels of concurrency.
If protocol_version
is set to 3 or higher, this
is not supported (there is always one connection per host, unless
the host is remote and connect_to_remote_hosts
is False
)
and using this will result in an UnsupporteOperation
.
get_max_connections_per_host
(host_distance)Gets the maximum number of connections per Session that will be opened
for each host with HostDistance
equal to host_distance.
The default is 8 for LOCAL
and 2 for
REMOTE
.
This property is ignored if protocol_version
is
3 or higher.
set_max_connections_per_host
(host_distance, max_connections)Sets the maximum number of connections per Session that will be opened
for each host with HostDistance
equal to host_distance.
The default is 2 for LOCAL
and 1 for
REMOTE
.
If protocol_version
is set to 3 or higher, this
is not supported (there is always one connection per host, unless
the host is remote and connect_to_remote_hosts
is False
)
and using this will result in an UnsupporteOperation
.
get_control_connection_host
()Returns the control connection host metadata.
refresh_schema_metadata
(max_schema_agreement_wait=None)Synchronously refresh all schema metadata.
By default, the timeout for this operation is governed by max_schema_agreement_wait
and control_connection_timeout
.
Passing max_schema_agreement_wait here overrides max_schema_agreement_wait
.
Setting max_schema_agreement_wait <= 0 will bypass schema agreement and refresh schema immediately.
An Exception is raised if schema refresh fails for any reason.
refresh_keyspace_metadata
(keyspace, max_schema_agreement_wait=None)Synchronously refresh keyspace metadata. This applies to keyspace-level information such as replication and durability settings. It does not refresh tables, types, etc. contained in the keyspace.
See refresh_schema_metadata()
for description of max_schema_agreement_wait
behavior
refresh_table_metadata
(keyspace, table, max_schema_agreement_wait=None)Synchronously refresh table metadata. This applies to a table, and any triggers or indexes attached to the table.
See refresh_schema_metadata()
for description of max_schema_agreement_wait
behavior
refresh_user_type_metadata
(keyspace, user_type, max_schema_agreement_wait=None)Synchronously refresh user defined type metadata.
See refresh_schema_metadata()
for description of max_schema_agreement_wait
behavior
refresh_user_function_metadata
(keyspace, function, max_schema_agreement_wait=None)Synchronously refresh user defined function metadata.
function
is a cassandra.UserFunctionDescriptor
.
See refresh_schema_metadata()
for description of max_schema_agreement_wait
behavior
refresh_user_aggregate_metadata
(keyspace, aggregate, max_schema_agreement_wait=None)Synchronously refresh user defined aggregate metadata.
aggregate
is a cassandra.UserAggregateDescriptor
.
See refresh_schema_metadata()
for description of max_schema_agreement_wait
behavior
refresh_nodes
(force_token_rebuild=False)Synchronously refresh the node list and token metadata
force_token_rebuild can be used to rebuild the token map metadata, even if no new nodes are discovered.
An Exception is raised if node refresh fails for any reason.
set_meta_refresh_enabled
(enabled)Deprecated: set schema_metadata_enabled
token_metadata_enabled
instead
Sets a flag to enable (True) or disable (False) all metadata refresh queries. This applies to both schema and node topology.
Disabling this is useful to minimize refreshes during multiple changes.
Meta refresh must be enabled for the driver to become aware of any cluster topology changes or schema updates.
class ExecutionProfile
Attributes
consistency_level
= LOCAL_ONEConsistencyLevel
used when not specified on a Statement
.
load_balancing_policy
= NoneAn instance of policies.LoadBalancingPolicy
or one of its subclasses.
Used in determining host distance for establishing connections, and routing requests.
Defaults to TokenAwarePolicy(DCAwareRoundRobinPolicy())
if not specified
retry_policy
= NoneAn instance of policies.RetryPolicy
instance used when Statement
objects do not have a
retry_policy
explicitly set.
Defaults to RetryPolicy
if not specified
serial_consistency_level
= NoneSerial ConsistencyLevel
used when not specified on a Statement
(for LWT conditional statements).
request_timeout
= 10.0Request timeout used when not overridden in Session.execute()
Static Methods
row_factory
(colnames, rows)A callable to format results, accepting (colnames, rows)
where colnames
is a list of column names, and
rows
is a list of tuples, with each tuple representing a row of parsed values.
Some example implementations:
cassandra.query.tuple_factory()
- return a result row as a tuple
cassandra.query.named_tuple_factory()
- return a result row as a named tuple
cassandra.query.dict_factory()
- return a result row as a dict
cassandra.query.ordered_dict_factory()
- return a result row as an OrderedDict
Attributes
speculative_execution_policy
= NoneAn instance of policies.SpeculativeExecutionPolicy
Defaults to NoSpeculativeExecutionPolicy
if not specified
Module Data
EXEC_PROFILE_DEFAULT
Key for the Cluster
default execution profile, used when no other profile is selected in
Session.execute(execution_profile)
.
Use this as the key in Cluster(execution_profiles)
to override the default profile.
class Session
A collection of connection pools for each host in the cluster.
Instances of this class should not be created directly, only
using Cluster.connect()
.
Queries and statements can be executed through Session
instances
using the execute()
and execute_async()
methods.
Example usage:
>>> session = cluster.connect()
>>> session.set_keyspace("mykeyspace")
>>> session.execute("SELECT * FROM mycf")
Attributes
default_timeout
= 10.0A default timeout, measured in seconds, for queries executed through
execute()
or execute_async()
. This default may be
overridden with the timeout parameter for either of those methods.
Setting this to None
will cause no timeouts to be set by default.
Please see ResponseFuture.result()
for details on the scope and
effect of this timeout.
default_consistency_level
= LOCAL_ONEThe default ConsistencyLevel
for operations executed through
this session. This default may be overridden by setting the
consistency_level
on individual statements.
default_serial_consistency_level
= NoneThe default ConsistencyLevel
for serial phase of conditional updates executed through
this session. This default may be overridden by setting the
serial_consistency_level
on individual statements.
Only valid for protocol_version >= 2
.
row_factory
= <function named_tuple_factory>The format to return row results in. By default, each returned row will be a named tuple. You can alternatively use any of the following:
cassandra.query.tuple_factory()
- return a result row as a tuple
cassandra.query.named_tuple_factory()
- return a result row as a named tuple
cassandra.query.dict_factory()
- return a result row as a dict
cassandra.query.ordered_dict_factory()
- return a result row as an OrderedDict
default_fetch_size
= 5000By default, this many rows will be fetched at a time. Setting
this to None
will disable automatic paging for large query
results. The fetch size can be also specified per-query through
Statement.fetch_size
.
This only takes effect when protocol version 2 or higher is used.
See Cluster.protocol_version
for details.
use_client_timestamp
= TrueWhen using protocol version 3 or higher, write timestamps may be supplied client-side at the protocol level. (Normally they are generated server-side by the coordinator node.) Note that timestamps specified within a CQL query will override this timestamp.
New in version 2.1.0.timestamp_generator
= NoneWhen use_client_timestamp
is set, sessions call this object and use
the result as the timestamp. (Note that timestamps specified within a CQL
query will override this timestamp.) By default, a new
MonotonicTimestampGenerator
is created for
each Cluster
instance.
Applications can set this value for custom timestamp behavior. For
example, an application could share a timestamp generator across
Cluster
objects to guarantee that the application will use unique,
increasing timestamps across clusters, or set it to to lambda:
int(time.time() * 1e6)
if losing records over clock inconsistencies is
acceptable for the application. Custom timestamp_generator
s should
be callable, and calling them should return an integer representing microseconds
since some point in time, typically UNIX epoch.
encoder
= NoneA Encoder
instance that will be used when
formatting query parameters for non-prepared statements. This is not used
for prepared statements (because prepared statements give the driver more
information about what CQL types are expected, allowing it to accept a
wider range of python types).
The encoder uses a mapping from python types to encoder methods (for
specific CQL types). This mapping can be be modified by users as they see
fit. Methods of Encoder
should be used for mapping
values if possible, because they take precautions to avoid injections and
properly sanitize data.
Example:
cluster = Cluster()
session = cluster.connect("mykeyspace")
session.encoder.mapping[tuple] = session.encoder.cql_encode_tuple
session.execute("CREATE TABLE mytable (k int PRIMARY KEY, col tuple<int, ascii>)")
session.execute("INSERT INTO mytable (k, col) VALUES (%s, %s)", [0, (123, 'abc')])
New in version 2.1.0.
client_protocol_handler
= <class ‘cassandra.protocol._ProtocolHandler’>Specifies a protocol handler that will be used for client-initiated requests (i.e. no internal driver requests). This can be used to override or extend features such as message or type ser/des.
The default pure python implementation is cassandra.protocol.ProtocolHandler
.
When compiled with Cython, there are also built-in faster alternatives. See Faster Deserialization
Methods
execute
(statement[, parameters][, timeout][, trace][, custom_payload])Execute the given query and synchronously wait for the response.
If an error is encountered while executing the query, an Exception will be raised.
query may be a query string or an instance of cassandra.query.Statement
.
parameters may be a sequence or dict of parameters to bind. If a
sequence is used, %s
should be used the placeholder for each
argument. If a dict is used, %(name)s
style placeholders must
be used.
timeout should specify a floating-point timeout (in seconds) after
which an OperationTimedOut
exception will be raised if the query
has not completed. If not set, the timeout defaults to
default_timeout
. If set to None
, there is
no timeout. Please see ResponseFuture.result()
for details on
the scope and effect of this timeout.
If trace is set to True
, the query will be sent with tracing enabled.
The trace details can be obtained using the returned ResultSet
object.
custom_payload is a Custom Payloads dict to be passed to the server. If query is a Statement with its own custom_payload. The message payload will be a union of the two, with the values specified here taking precedence.
execution_profile is the execution profile to use for this request. It can be a key to a profile configured
via Cluster.add_execution_profile()
or an instance (from Session.execution_profile_clone_update()
,
for example
paging_state is an optional paging state, reused from a previous ResultSet
.
execute_async
(statement[, parameters][, trace][, custom_payload])Execute the given query and return a ResponseFuture
object
which callbacks may be attached to for asynchronous response
delivery. You may also call result()
on the ResponseFuture
to synchronously block for results at
any time.
See Session.execute()
for parameter definitions.
Example usage:
>>> session = cluster.connect()
>>> future = session.execute_async("SELECT * FROM mycf")
>>> def log_results(results):
... for row in results:
... log.info("Results: %s", row)
>>> def log_error(exc):
>>> log.error("Operation failed: %s", exc)
>>> future.add_callbacks(log_results, log_error)
Async execution with blocking wait for results:
>>> future = session.execute_async("SELECT * FROM mycf")
>>> # do other stuff...
>>> try:
... results = future.result()
... except Exception:
... log.exception("Operation failed:")
prepare
(statement)Prepares a query string, returning a PreparedStatement
instance which can be used as follows:
>>> session = cluster.connect("mykeyspace")
>>> query = "INSERT INTO users (id, name, age) VALUES (?, ?, ?)"
>>> prepared = session.prepare(query)
>>> session.execute(prepared, (user.id, user.name, user.age))
Or you may bind values to the prepared statement ahead of time:
>>> prepared = session.prepare(query)
>>> bound_stmt = prepared.bind((user.id, user.name, user.age))
>>> session.execute(bound_stmt)
Of course, prepared statements may (and should) be reused:
>>> prepared = session.prepare(query)
>>> for user in users:
... bound = prepared.bind((user.id, user.name, user.age))
... session.execute(bound)
Alternatively, if protocol_version
is 5 or higher
(requires Cassandra 4.0+), the keyspace can be specified as a
parameter. This will allow you to avoid specifying the keyspace in the
query without specifying a keyspace in connect()
. It
even will let you prepare and use statements against a keyspace other
than the one originally specified on connection:
Important: PreparedStatements should be prepared only once. Preparing the same query more than once will likely affect performance.
custom_payload is a key value map to be passed along with the prepare message. See Custom Payloads.
shutdown
()Close all connections. Session
instances should not be used
for any purpose after being shutdown.
set_keyspace
(keyspace)Set the default keyspace for all queries made through this Session. This operation blocks until complete.
execution_profile_clone_update
(ep, **kwargs)Returns a clone of the ep
profile. kwargs
can be specified to update attributes
of the returned profile.
This is a shallow clone, so any objects referenced by the profile are shared. This means Load Balancing Policy is maintained by inclusion in the active profiles. It also means updating any other rich objects will be seen by the active profile. In cases where this is not desirable, be sure to replace the instance instead of manipulating the shared object.
add_request_init_listener
(fn, *args, **kwargs)Adds a callback with arguments to be called when any request is created.
It will be invoked as fn(response_future, *args, **kwargs) after each client request is created, and before the request is sent*. This can be used to create extensions by adding result callbacks to the response future.
* where response_future is the ResponseFuture
for the request.
Note that the init callback is done on the client thread creating the request, so you may need to consider
synchronization if you have multiple threads. Any callbacks added to the response future will be executed
on the event loop thread, so the normal advice about minimizing cycles and avoiding blocking apply (see Note in
ResponseFuture.add_callbacks()
.
See this example in the source tree for an example.
remove_request_init_listener
(fn, *args, **kwargs)Removes a callback and arguments from the list.
class ResponseFuture
An asynchronous response delivery mechanism that is returned from calls
to Session.execute_async()
.
- There are two ways for results to be delivered:
-
-
Synchronously, by calling
result()
-
Asynchronously, by attaching callback and errback functions via
add_callback()
,add_errback()
, andadd_callbacks()
.
-
Attributes
query
= NoneThe Statement
instance that is being executed through this
ResponseFuture
.
Methods
result
()Return the final result or raise an Exception if errors were encountered. If the final result or error has not been set yet, this method will block until it is set, or the timeout set for the request expires.
Timeout is specified in the Session request execution functions.
If the timeout is exceeded, an cassandra.OperationTimedOut
will be raised.
This is a client-side timeout. For more information
about server-side coordinator timeouts, see policies.RetryPolicy
.
Example usage:
>>> future = session.execute_async("SELECT * FROM mycf")
>>> # do other stuff...
>>> try:
... rows = future.result()
... for row in rows:
... ... # process results
... except Exception:
... log.exception("Operation failed:")
get_query_trace
()Fetches and returns the query trace of the last response, or None if tracing was not enabled.
Note that this may raise an exception if there are problems retrieving the trace
details from Cassandra. If the trace is not available after max_wait,
cassandra.query.TraceUnavailable
will be raised.
If the ResponseFuture is not done (async execution) and you try to retrieve the trace,
cassandra.query.TraceUnavailable
will be raised.
query_cl is the consistency level used to poll the trace tables.
get_all_query_traces
()Fetches and returns the query traces for all query pages, if tracing was enabled.
See note in get_query_trace()
regarding possible exceptions.
Attributes
custom_payload
The custom payload returned from the server, if any. This will only be set by Cassandra servers implementing a custom QueryHandler, and only for protocol_version 4+.
Ensure the future is complete before trying to access this property
(call result()
, or after callback is invoked).
Otherwise it may throw if the response has not been received.
- Returns
is_schema_agreed
= TrueFor DDL requests, this may be set False
if the schema agreement poll after the response fails.
Always True
for non-DDL requests.
has_more_pages
Returns True
if there are more pages left in the
query results, False
otherwise. This should only
be checked after the first page has been returned.
warnings
Warnings returned from the server, if any. This will only be set for protocol_version 4+.
Warnings may be returned for such things as oversized batches, or too many tombstones in slice queries.
Ensure the future is complete before trying to access this property
(call result()
, or after callback is invoked).
Otherwise it may throw if the response has not been received.
Methods
start_fetching_next_page
()If there are more pages left in the query result, this asynchronously
starts fetching the next page. If there are no pages left, QueryExhausted
is raised. Also see has_more_pages
.
This should only be called after the first page has been returned.
New in version 2.0.0.add_callback
(fn, *args, **kwargs)Attaches a callback function to be called when the final results arrive.
By default, fn will be called with the results as the first and only argument. If *args or **kwargs are supplied, they will be passed through as additional positional or keyword arguments to fn.
If an error is hit while executing the operation, a callback attached
here will not be called. Use add_errback()
or add_callbacks()
if you wish to handle that case.
If the final result has already been seen when this method is called, the callback will be called immediately (before this method returns).
Note: in the case that the result is not available when the callback is added, the callback is executed by IO event thread. This means that the callback should not block or attempt further synchronous requests, because no further IO will be processed until the callback returns.
Important: if the callback you attach results in an exception being raised, the exception will be ignored, so please ensure your callback handles all error cases that you care about.
Usage example:
>>> session = cluster.connect("mykeyspace")
>>> def handle_results(rows, start_time, should_log=False):
... if should_log:
... log.info("Total time: %f", time.time() - start_time)
... ...
>>> future = session.execute_async("SELECT * FROM users")
>>> future.add_callback(handle_results, time.time(), should_log=True)
add_errback
(fn, *args, **kwargs)Like add_callback()
, but handles error cases.
An Exception instance will be passed as the first positional argument
to fn.
add_callbacks
(callback, errback, callback_args=(), callback_kwargs=None, errback_args=(), errback_args=None)A convenient combination of add_callback()
and
add_errback()
.
Example usage:
>>> session = cluster.connect()
>>> query = "SELECT * FROM mycf"
>>> future = session.execute_async(query)
>>> def log_results(results, level='debug'):
... for row in results:
... log.log(level, "Result: %s", row)
>>> def log_error(exc, query):
... log.error("Query '%s' failed: %s", query, exc)
>>> future.add_callbacks(
... callback=log_results, callback_kwargs={'level': 'info'},
... errback=log_error, errback_args=(query,))
class ResultSet
An iterator over the rows from a query result. Also supplies basic equality and indexing methods for backward-compatability. These methods materialize the entire result set (loading all pages), and should only be used if the total result size is understood. Warnings are emitted when paged results are materialized in this fashion.
You can treat this as a normal iterator over rows:
>>> from cassandra.query import SimpleStatement
>>> statement = SimpleStatement("SELECT * FROM users", fetch_size=10)
>>> for user_row in session.execute(statement):
... process_user(user_row)
Whenever there are no more rows in the current page, the next page will
be fetched transparently. However, note that it is possible for
an Exception
to be raised while fetching the next page, just
like you might see on a normal call to session.execute()
.
Attributes
has_more_pages
True if the last response indicated more pages; False otherwise
current_rows
The list of current page rows. May be empty if the result was empty, or this is the last page.
Methods
fetch_next_page
()Manually, synchronously fetch the next page. Supplied for manually retrieving pages
and inspecting current_page()
. It is not necessary to call this when iterating
through results; paging happens implicitly in iteration.
get_query_trace
(max_wait_sec=None)Gets the last query trace from the associated future.
See ResponseFuture.get_query_trace()
for details.
get_all_query_traces
(max_wait_sec_per=None)Gets all query traces from the associated future.
See ResponseFuture.get_all_query_traces()
for details.
Attributes
was_applied
For LWT results, returns whether the transaction was applied.
Result is indeterminate if called on a result that was not an LWT request.
Only valid when one of tne of the internal row factories is in use.
paging_state
Server paging state of the query. Can be None if the query was not paged.
The driver treats paging state as opaque, but it may contain primary key data, so applications may want to avoid sending this to untrusted parties.
exception QueryExhausted
Raised when ResponseFuture.start_fetching_next_page()
is called and
there are no more pages. You can check ResponseFuture.has_more_pages
before calling to avoid this.
exception NoHostAvailable
Raised when an operation is attempted but all connections are busy, defunct, closed, or resulted in errors when used.
Attributes
errors
= NoneA map of the form {ip: exception}
which details the particular
Exception that was caught for each host the operation was attempted
against.
exception UserTypeDoesNotExist
An attempt was made to use a user-defined type that does not exist.
New in version 2.1.0.