# Copyright 2013-2015 DataStax, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This module holds classes for working with prepared statements and
specifying consistency levels and retry policies for individual
queries.
"""
from collections import namedtuple
from datetime import datetime, timedelta
import re
import struct
import time
import six
from cassandra import ConsistencyLevel, OperationTimedOut
from cassandra.cqltypes import unix_time_from_uuid1
from cassandra.encoder import Encoder
import cassandra.encoder
from cassandra.util import OrderedDict
import logging
log = logging.getLogger(__name__)
NON_ALPHA_REGEX = re.compile('[^a-zA-Z0-9]')
START_BADCHAR_REGEX = re.compile('^[^a-zA-Z0-9]*')
END_BADCHAR_REGEX = re.compile('[^a-zA-Z0-9_]*$')
_clean_name_cache = {}
def _clean_column_name(name):
try:
return _clean_name_cache[name]
except KeyError:
clean = NON_ALPHA_REGEX.sub("_", START_BADCHAR_REGEX.sub("", END_BADCHAR_REGEX.sub("", name)))
_clean_name_cache[name] = clean
return clean
[docs]def tuple_factory(colnames, rows):
"""
Returns each row as a tuple
Example::
>>> from cassandra.query import tuple_factory
>>> session = cluster.connect('mykeyspace')
>>> session.row_factory = tuple_factory
>>> rows = session.execute("SELECT name, age FROM users LIMIT 1")
>>> print rows[0]
('Bob', 42)
.. versionchanged:: 2.0.0
moved from ``cassandra.decoder`` to ``cassandra.query``
"""
return rows
[docs]def named_tuple_factory(colnames, rows):
"""
Returns each row as a `namedtuple <https://docs.python.org/2/library/collections.html#collections.namedtuple>`_.
This is the default row factory.
Example::
>>> from cassandra.query import named_tuple_factory
>>> session = cluster.connect('mykeyspace')
>>> session.row_factory = named_tuple_factory
>>> rows = session.execute("SELECT name, age FROM users LIMIT 1")
>>> user = rows[0]
>>> # you can access field by their name:
>>> print "name: %s, age: %d" % (user.name, user.age)
name: Bob, age: 42
>>> # or you can access fields by their position (like a tuple)
>>> name, age = user
>>> print "name: %s, age: %d" % (name, age)
name: Bob, age: 42
>>> name = user[0]
>>> age = user[1]
>>> print "name: %s, age: %d" % (name, age)
name: Bob, age: 42
.. versionchanged:: 2.0.0
moved from ``cassandra.decoder`` to ``cassandra.query``
"""
clean_column_names = map(_clean_column_name, colnames)
try:
Row = namedtuple('Row', clean_column_names)
except Exception:
log.warning("Failed creating named tuple for results with column names %s (cleaned: %s) "
"(see Python 'namedtuple' documentation for details on name rules). "
"Results will be returned with positional names. "
"Avoid this by choosing different names, using SELECT \"<col name>\" AS aliases, "
"or specifying a different row_factory on your Session" %
(colnames, clean_column_names))
Row = namedtuple('Row', clean_column_names, rename=True)
return [Row(*row) for row in rows]
[docs]def dict_factory(colnames, rows):
"""
Returns each row as a dict.
Example::
>>> from cassandra.query import dict_factory
>>> session = cluster.connect('mykeyspace')
>>> session.row_factory = dict_factory
>>> rows = session.execute("SELECT name, age FROM users LIMIT 1")
>>> print rows[0]
{u'age': 42, u'name': u'Bob'}
.. versionchanged:: 2.0.0
moved from ``cassandra.decoder`` to ``cassandra.query``
"""
return [dict(zip(colnames, row)) for row in rows]
[docs]def ordered_dict_factory(colnames, rows):
"""
Like :meth:`~cassandra.query.dict_factory`, but returns each row as an OrderedDict,
so the order of the columns is preserved.
.. versionchanged:: 2.0.0
moved from ``cassandra.decoder`` to ``cassandra.query``
"""
return [OrderedDict(zip(colnames, row)) for row in rows]
FETCH_SIZE_UNSET = object()
[docs]class Statement(object):
"""
An abstract class representing a single query. There are three subclasses:
:class:`.SimpleStatement`, :class:`.BoundStatement`, and :class:`.BatchStatement`.
These can be passed to :meth:`.Session.execute()`.
"""
retry_policy = None
"""
An instance of a :class:`cassandra.policies.RetryPolicy` or one of its
subclasses. This controls when a query will be retried and how it
will be retried.
"""
trace = None
"""
If :meth:`.Session.execute()` is run with `trace` set to :const:`True`,
this will be set to a :class:`.QueryTrace` instance.
"""
consistency_level = None
"""
The :class:`.ConsistencyLevel` to be used for this operation. Defaults
to :const:`None`, which means that the default consistency level for
the Session this is executed in will be used.
"""
fetch_size = FETCH_SIZE_UNSET
"""
How many rows will be fetched at a time. This overrides the default
of :attr:`.Session.default_fetch_size`
This only takes effect when protocol version 2 or higher is used.
See :attr:`.Cluster.protocol_version` for details.
.. versionadded:: 2.0.0
"""
keyspace = None
"""
The string name of the keyspace this query acts on. This is used when
:class:`~.TokenAwarePolicy` is configured for
:attr:`.Cluster.load_balancing_policy`
It is set implicitly on :class:`.BoundStatement`, and :class:`.BatchStatement`,
but must be set explicitly on :class:`.SimpleStatement`.
.. versionadded:: 2.1.3
"""
_serial_consistency_level = None
_routing_key = None
def __init__(self, retry_policy=None, consistency_level=None, routing_key=None,
serial_consistency_level=None, fetch_size=FETCH_SIZE_UNSET, keyspace=None):
self.retry_policy = retry_policy
if consistency_level is not None:
self.consistency_level = consistency_level
self._routing_key = routing_key
if serial_consistency_level is not None:
self.serial_consistency_level = serial_consistency_level
if fetch_size is not FETCH_SIZE_UNSET:
self.fetch_size = fetch_size
if keyspace is not None:
self.keyspace = keyspace
def _get_routing_key(self):
return self._routing_key
def _set_routing_key(self, key):
if isinstance(key, (list, tuple)):
self._routing_key = b"".join(struct.pack("HsB", len(component), component, 0)
for component in key)
else:
self._routing_key = key
def _del_routing_key(self):
self._routing_key = None
routing_key = property(
_get_routing_key,
_set_routing_key,
_del_routing_key,
"""
The :attr:`~.TableMetadata.partition_key` portion of the primary key,
which can be used to determine which nodes are replicas for the query.
If the partition key is a composite, a list or tuple must be passed in.
Each key component should be in its packed (binary) format, so all
components should be strings.
""")
def _get_serial_consistency_level(self):
return self._serial_consistency_level
def _set_serial_consistency_level(self, serial_consistency_level):
acceptable = (None, ConsistencyLevel.SERIAL, ConsistencyLevel.LOCAL_SERIAL)
if serial_consistency_level not in acceptable:
raise ValueError(
"serial_consistency_level must be either ConsistencyLevel.SERIAL "
"or ConsistencyLevel.LOCAL_SERIAL")
self._serial_consistency_level = serial_consistency_level
def _del_serial_consistency_level(self):
self._serial_consistency_level = None
serial_consistency_level = property(
_get_serial_consistency_level,
_set_serial_consistency_level,
_del_serial_consistency_level,
"""
The serial consistency level is only used by conditional updates
(``INSERT``, ``UPDATE`` and ``DELETE`` with an ``IF`` condition). For
those, the ``serial_consistency_level`` defines the consistency level of
the serial phase (or "paxos" phase) while the normal
:attr:`~.consistency_level` defines the consistency for the "learn" phase,
i.e. what type of reads will be guaranteed to see the update right away.
For example, if a conditional write has a :attr:`~.consistency_level` of
:attr:`~.ConsistencyLevel.QUORUM` (and is successful), then a
:attr:`~.ConsistencyLevel.QUORUM` read is guaranteed to see that write.
But if the regular :attr:`~.consistency_level` of that write is
:attr:`~.ConsistencyLevel.ANY`, then only a read with a
:attr:`~.consistency_level` of :attr:`~.ConsistencyLevel.SERIAL` is
guaranteed to see it (even a read with consistency
:attr:`~.ConsistencyLevel.ALL` is not guaranteed to be enough).
The serial consistency can only be one of :attr:`~.ConsistencyLevel.SERIAL`
or :attr:`~.ConsistencyLevel.LOCAL_SERIAL`. While ``SERIAL`` guarantees full
linearizability (with other ``SERIAL`` updates), ``LOCAL_SERIAL`` only
guarantees it in the local data center.
The serial consistency level is ignored for any query that is not a
conditional update. Serial reads should use the regular
:attr:`consistency_level`.
Serial consistency levels may only be used against Cassandra 2.0+
and the :attr:`~.Cluster.protocol_version` must be set to 2 or higher.
.. versionadded:: 2.0.0
""")
[docs]class SimpleStatement(Statement):
"""
A simple, un-prepared query. All attributes of :class:`Statement` apply
to this class as well.
"""
def __init__(self, query_string, *args, **kwargs):
"""
`query_string` should be a literal CQL statement with the exception
of parameter placeholders that will be filled through the
`parameters` argument of :meth:`.Session.execute()`.
"""
Statement.__init__(self, *args, **kwargs)
self._query_string = query_string
@property
def query_string(self):
return self._query_string
def __str__(self):
consistency = ConsistencyLevel.value_to_name.get(self.consistency_level, 'Not Set')
return (u'<SimpleStatement query="%s", consistency=%s>' %
(self.query_string, consistency))
__repr__ = __str__
[docs]class PreparedStatement(object):
"""
A statement that has been prepared against at least one Cassandra node.
Instances of this class should not be created directly, but through
:meth:`.Session.prepare()`.
A :class:`.PreparedStatement` should be prepared only once. Re-preparing a statement
may affect performance (as the operation requires a network roundtrip).
"""
column_metadata = None
query_id = None
query_string = None
keyspace = None # change to prepared_keyspace in major release
routing_key_indexes = None
consistency_level = None
serial_consistency_level = None
protocol_version = None
fetch_size = FETCH_SIZE_UNSET
def __init__(self, column_metadata, query_id, routing_key_indexes, query, keyspace,
protocol_version, consistency_level=None, serial_consistency_level=None,
fetch_size=FETCH_SIZE_UNSET):
self.column_metadata = column_metadata
self.query_id = query_id
self.routing_key_indexes = routing_key_indexes
self.query_string = query
self.keyspace = keyspace
self.protocol_version = protocol_version
self.consistency_level = consistency_level
self.serial_consistency_level = serial_consistency_level
if fetch_size is not FETCH_SIZE_UNSET:
self.fetch_size = fetch_size
@classmethod
def from_message(cls, query_id, column_metadata, cluster_metadata, query, prepared_keyspace, protocol_version):
if not column_metadata:
return PreparedStatement(column_metadata, query_id, None, query, prepared_keyspace, protocol_version)
partition_key_columns = None
routing_key_indexes = None
ks_name, table_name, _, _ = column_metadata[0]
ks_meta = cluster_metadata.keyspaces.get(ks_name)
if ks_meta:
table_meta = ks_meta.tables.get(table_name)
if table_meta:
partition_key_columns = table_meta.partition_key
# make a map of {column_name: index} for each column in the statement
statement_indexes = dict((c[2], i) for i, c in enumerate(column_metadata))
# a list of which indexes in the statement correspond to partition key items
try:
routing_key_indexes = [statement_indexes[c.name]
for c in partition_key_columns]
except KeyError: # we're missing a partition key component in the prepared
pass # statement; just leave routing_key_indexes as None
return PreparedStatement(column_metadata, query_id, routing_key_indexes,
query, prepared_keyspace, protocol_version)
[docs] def bind(self, values):
"""
Creates and returns a :class:`BoundStatement` instance using `values`.
The `values` parameter **must** be a sequence, such as a tuple or list,
even if there is only one value to bind.
"""
return BoundStatement(self).bind(values)
def __str__(self):
consistency = ConsistencyLevel.value_to_name.get(self.consistency_level, 'Not Set')
return (u'<PreparedStatement query="%s", consistency=%s>' %
(self.query_string, consistency))
__repr__ = __str__
[docs]class BoundStatement(Statement):
"""
A prepared statement that has been bound to a particular set of values.
These may be created directly or through :meth:`.PreparedStatement.bind()`.
All attributes of :class:`Statement` apply to this class as well.
"""
prepared_statement = None
"""
The :class:`PreparedStatement` instance that this was created from.
"""
values = None
"""
The sequence of values that were bound to the prepared statement.
"""
def __init__(self, prepared_statement, *args, **kwargs):
"""
`prepared_statement` should be an instance of :class:`PreparedStatement`.
All other ``*args`` and ``**kwargs`` will be passed to :class:`.Statement`.
"""
self.prepared_statement = prepared_statement
self.consistency_level = prepared_statement.consistency_level
self.serial_consistency_level = prepared_statement.serial_consistency_level
self.fetch_size = prepared_statement.fetch_size
self.values = []
meta = prepared_statement.column_metadata
if meta:
self.keyspace = meta[0][0]
Statement.__init__(self, *args, **kwargs)
[docs] def bind(self, values):
"""
Binds a sequence of values for the prepared statement parameters
and returns this instance. Note that `values` *must* be:
* a sequence, even if you are only binding one value, or
* a dict that relates 1-to-1 between dict keys and columns
"""
if values is None:
values = ()
col_meta = self.prepared_statement.column_metadata
proto_version = self.prepared_statement.protocol_version
# special case for binding dicts
if isinstance(values, dict):
dict_values = values
values = []
# sort values accordingly
for col in col_meta:
try:
values.append(dict_values[col[2]])
except KeyError:
raise KeyError(
'Column name `%s` not found in bound dict.' %
(col[2]))
# ensure a 1-to-1 dict keys to columns relationship
if len(dict_values) != len(col_meta):
# find expected columns
columns = set()
for col in col_meta:
columns.add(col[2])
# generate error message
if len(dict_values) > len(col_meta):
difference = set(dict_values.keys()).difference(columns)
msg = "Too many arguments provided to bind() (got %d, expected %d). " + \
"Unexpected keys %s."
else:
difference = set(columns).difference(dict_values.keys())
msg = "Too few arguments provided to bind() (got %d, expected %d). " + \
"Expected keys %s."
# exit with error message
msg = msg % (len(values), len(col_meta), difference)
raise ValueError(msg)
if len(values) > len(col_meta):
raise ValueError(
"Too many arguments provided to bind() (got %d, expected %d)" %
(len(values), len(col_meta)))
if self.prepared_statement.routing_key_indexes and \
len(values) < len(self.prepared_statement.routing_key_indexes):
raise ValueError(
"Too few arguments provided to bind() (got %d, required %d for routing key)" %
(len(values), len(self.prepared_statement.routing_key_indexes)))
self.raw_values = values
self.values = []
for value, col_spec in zip(values, col_meta):
if value is None:
self.values.append(None)
else:
col_type = col_spec[-1]
try:
self.values.append(col_type.serialize(value, proto_version))
except (TypeError, struct.error) as exc:
col_name = col_spec[2]
expected_type = col_type
actual_type = type(value)
message = ('Received an argument of invalid type for column "%s". '
'Expected: %s, Got: %s; (%s)' % (col_name, expected_type, actual_type, exc))
raise TypeError(message)
return self
@property
def routing_key(self):
if not self.prepared_statement.routing_key_indexes:
return None
if self._routing_key is not None:
return self._routing_key
routing_indexes = self.prepared_statement.routing_key_indexes
if len(routing_indexes) == 1:
self._routing_key = self.values[routing_indexes[0]]
else:
components = []
for statement_index in routing_indexes:
val = self.values[statement_index]
l = len(val)
components.append(struct.pack(">H%dsB" % l, l, val, 0))
self._routing_key = b"".join(components)
return self._routing_key
def __str__(self):
consistency = ConsistencyLevel.value_to_name.get(self.consistency_level, 'Not Set')
return (u'<BoundStatement query="%s", values=%s, consistency=%s>' %
(self.prepared_statement.query_string, self.raw_values, consistency))
__repr__ = __str__
[docs]class BatchType(object):
"""
A BatchType is used with :class:`.BatchStatement` instances to control
the atomicity of the batch operation.
.. versionadded:: 2.0.0
"""
LOGGED = None
"""
Atomic batch operation.
"""
UNLOGGED = None
"""
Non-atomic batch operation.
"""
COUNTER = None
"""
Batches of counter operations.
"""
def __init__(self, name, value):
self.name = name
self.value = value
def __str__(self):
return self.name
def __repr__(self):
return "BatchType.%s" % (self.name, )
BatchType.LOGGED = BatchType("LOGGED", 0)
BatchType.UNLOGGED = BatchType("UNLOGGED", 1)
BatchType.COUNTER = BatchType("COUNTER", 2)
[docs]class BatchStatement(Statement):
"""
A protocol-level batch of operations which are applied atomically
by default.
.. versionadded:: 2.0.0
"""
batch_type = None
"""
The :class:`.BatchType` for the batch operation. Defaults to
:attr:`.BatchType.LOGGED`.
"""
serial_consistency_level = None
"""
The same as :attr:`.Statement.serial_consistency_level`, but is only
supported when using protocol version 3 or higher.
"""
_statements_and_parameters = None
_session = None
def __init__(self, batch_type=BatchType.LOGGED, retry_policy=None,
consistency_level=None, serial_consistency_level=None, session=None):
"""
`batch_type` specifies The :class:`.BatchType` for the batch operation.
Defaults to :attr:`.BatchType.LOGGED`.
`retry_policy` should be a :class:`~.RetryPolicy` instance for
controlling retries on the operation.
`consistency_level` should be a :class:`~.ConsistencyLevel` value
to be used for all operations in the batch.
Example usage:
.. code-block:: python
insert_user = session.prepare("INSERT INTO users (name, age) VALUES (?, ?)")
batch = BatchStatement(consistency_level=ConsistencyLevel.QUORUM)
for (name, age) in users_to_insert:
batch.add(insert_user, (name, age))
session.execute(batch)
You can also mix different types of operations within a batch:
.. code-block:: python
batch = BatchStatement()
batch.add(SimpleStatement("INSERT INTO users (name, age) VALUES (%s, %s)"), (name, age))
batch.add(SimpleStatement("DELETE FROM pending_users WHERE name=%s"), (name,))
session.execute(batch)
.. versionadded:: 2.0.0
.. versionchanged:: 2.1.0
Added `serial_consistency_level` as a parameter
"""
self.batch_type = batch_type
self._statements_and_parameters = []
self._session = session
Statement.__init__(self, retry_policy=retry_policy, consistency_level=consistency_level,
serial_consistency_level=serial_consistency_level)
[docs] def add(self, statement, parameters=None):
"""
Adds a :class:`.Statement` and optional sequence of parameters
to be used with the statement to the batch.
Like with other statements, parameters must be a sequence, even
if there is only one item.
"""
if isinstance(statement, six.string_types):
if parameters:
encoder = Encoder() if self._session is None else self._session.encoder
statement = bind_params(statement, parameters, encoder)
self._statements_and_parameters.append((False, statement, ()))
elif isinstance(statement, PreparedStatement):
query_id = statement.query_id
bound_statement = statement.bind(() if parameters is None else parameters)
self._maybe_set_routing_attributes(bound_statement)
self._statements_and_parameters.append(
(True, query_id, bound_statement.values))
elif isinstance(statement, BoundStatement):
if parameters:
raise ValueError(
"Parameters cannot be passed with a BoundStatement "
"to BatchStatement.add()")
self._maybe_set_routing_attributes(statement)
self._statements_and_parameters.append(
(True, statement.prepared_statement.query_id, statement.values))
else:
# it must be a SimpleStatement
query_string = statement.query_string
if parameters:
encoder = Encoder() if self._session is None else self._session.encoder
query_string = bind_params(query_string, parameters, encoder)
self._maybe_set_routing_attributes(statement)
self._statements_and_parameters.append((False, query_string, ()))
return self
[docs] def add_all(self, statements, parameters):
"""
Adds a sequence of :class:`.Statement` objects and a matching sequence
of parameters to the batch. :const:`None` can be used in place of
parameters when no parameters are needed.
"""
for statement, value in zip(statements, parameters):
self.add(statement, parameters)
def _maybe_set_routing_attributes(self, statement):
if self.routing_key is None:
if statement.keyspace and statement.routing_key:
self.routing_key = statement.routing_key
self.keyspace = statement.keyspace
def __str__(self):
consistency = ConsistencyLevel.value_to_name.get(self.consistency_level, 'Not Set')
return (u'<BatchStatement type=%s, statements=%d, consistency=%s>' %
(self.batch_type, len(self._statements_and_parameters), consistency))
__repr__ = __str__
ValueSequence = cassandra.encoder.ValueSequence
"""
A wrapper class that is used to specify that a sequence of values should
be treated as a CQL list of values instead of a single column collection when used
as part of the `parameters` argument for :meth:`.Session.execute()`.
This is typically needed when supplying a list of keys to select.
For example::
>>> my_user_ids = ('alice', 'bob', 'charles')
>>> query = "SELECT * FROM users WHERE user_id IN %s"
>>> session.execute(query, parameters=[ValueSequence(my_user_ids)])
"""
def bind_params(query, params, encoder):
if isinstance(params, dict):
return query % dict((k, encoder.cql_encode_all_types(v)) for k, v in six.iteritems(params))
else:
return query % tuple(encoder.cql_encode_all_types(v) for v in params)
[docs]class TraceUnavailable(Exception):
"""
Raised when complete trace details cannot be fetched from Cassandra.
"""
pass
[docs]class QueryTrace(object):
"""
A trace of the duration and events that occurred when executing
an operation.
"""
trace_id = None
"""
:class:`uuid.UUID` unique identifier for this tracing session. Matches
the ``session_id`` column in ``system_traces.sessions`` and
``system_traces.events``.
"""
request_type = None
"""
A string that very generally describes the traced operation.
"""
duration = None
"""
A :class:`datetime.timedelta` measure of the duration of the query.
"""
coordinator = None
"""
The IP address of the host that acted as coordinator for this request.
"""
parameters = None
"""
A :class:`dict` of parameters for the traced operation, such as the
specific query string.
"""
started_at = None
"""
A UTC :class:`datetime.datetime` object describing when the operation
was started.
"""
events = None
"""
A chronologically sorted list of :class:`.TraceEvent` instances
representing the steps the traced operation went through. This
corresponds to the rows in ``system_traces.events`` for this tracing
session.
"""
_session = None
_SELECT_SESSIONS_FORMAT = "SELECT * FROM system_traces.sessions WHERE session_id = %s"
_SELECT_EVENTS_FORMAT = "SELECT * FROM system_traces.events WHERE session_id = %s"
_BASE_RETRY_SLEEP = 0.003
def __init__(self, trace_id, session):
self.trace_id = trace_id
self._session = session
[docs] def populate(self, max_wait=2.0):
"""
Retrieves the actual tracing details from Cassandra and populates the
attributes of this instance. Because tracing details are stored
asynchronously by Cassandra, this may need to retry the session
detail fetch. If the trace is still not available after `max_wait`
seconds, :exc:`.TraceUnavailable` will be raised; if `max_wait` is
:const:`None`, this will retry forever.
"""
attempt = 0
start = time.time()
while True:
time_spent = time.time() - start
if max_wait is not None and time_spent >= max_wait:
raise TraceUnavailable(
"Trace information was not available within %f seconds. Consider raising Session.max_trace_wait." % (max_wait,))
log.debug("Attempting to fetch trace info for trace ID: %s", self.trace_id)
session_results = self._execute(
self._SELECT_SESSIONS_FORMAT, (self.trace_id,), time_spent, max_wait)
if not session_results or session_results[0].duration is None:
time.sleep(self._BASE_RETRY_SLEEP * (2 ** attempt))
attempt += 1
continue
log.debug("Fetched trace info for trace ID: %s", self.trace_id)
session_row = session_results[0]
self.request_type = session_row.request
self.duration = timedelta(microseconds=session_row.duration)
self.started_at = session_row.started_at
self.coordinator = session_row.coordinator
self.parameters = session_row.parameters
log.debug("Attempting to fetch trace events for trace ID: %s", self.trace_id)
time_spent = time.time() - start
event_results = self._execute(
self._SELECT_EVENTS_FORMAT, (self.trace_id,), time_spent, max_wait)
log.debug("Fetched trace events for trace ID: %s", self.trace_id)
self.events = tuple(TraceEvent(r.activity, r.event_id, r.source, r.source_elapsed, r.thread)
for r in event_results)
break
def _execute(self, query, parameters, time_spent, max_wait):
# in case the user switched the row factory, set it to namedtuple for this query
future = self._session._create_response_future(query, parameters, trace=False)
future.row_factory = named_tuple_factory
future.send_request()
timeout = (max_wait - time_spent) if max_wait is not None else None
try:
return future.result(timeout=timeout)
except OperationTimedOut:
raise TraceUnavailable("Trace information was not available within %f seconds" % (max_wait,))
def __str__(self):
return "%s [%s] coordinator: %s, started at: %s, duration: %s, parameters: %s" \
% (self.request_type, self.trace_id, self.coordinator, self.started_at,
self.duration, self.parameters)
[docs]class TraceEvent(object):
"""
Representation of a single event within a query trace.
"""
description = None
"""
A brief description of the event.
"""
datetime = None
"""
A UTC :class:`datetime.datetime` marking when the event occurred.
"""
source = None
"""
The IP address of the node this event occurred on.
"""
source_elapsed = None
"""
A :class:`datetime.timedelta` measuring the amount of time until
this event occurred starting from when :attr:`.source` first
received the query.
"""
thread_name = None
"""
The name of the thread that this event occurred on.
"""
def __init__(self, description, timeuuid, source, source_elapsed, thread_name):
self.description = description
self.datetime = datetime.utcfromtimestamp(unix_time_from_uuid1(timeuuid))
self.source = source
if source_elapsed is not None:
self.source_elapsed = timedelta(microseconds=source_elapsed)
else:
self.source_elapsed = None
self.thread_name = thread_name
def __str__(self):
return "%s on %s[%s] at %s" % (self.description, self.source, self.thread_name, self.datetime)