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The batch interface allows insert, update, and remove operations to be performed
in batches. This allows a convenient mechanism for streaming updates or doing a
large number of operations while reducing number of RPC roundtrips.
Batch mutator objects are synchronized and can be safely passed around threads.
.. code-block:: python
>>> b = cf.batch(queue_size=10)
>>> b.insert('key1', {'col1':'value11', 'col2':'value21'})
>>> b.insert('key2', {'col1':'value12', 'col2':'value22'}, ttl=15)
>>> b.remove('key1', ['col2'])
>>> b.remove('key2')
>>> b.send()
One can use the `queue_size` argument to control how many mutations will be
queued before an automatic :meth:`send` is performed. This allows simple streaming
of updates. If set to ``None``, automatic checkpoints are disabled. Default is 100.
Supercolumns are supported:
.. code-block:: python
>>> b = scf.batch()
>>> b.insert('key1', {'supercol1': {'colA':'value1a', 'colB':'value1b'}
... {'supercol2': {'colA':'value2a', 'colB':'value2b'}})
>>> b.remove('key1', ['colA'], 'supercol1')
>>> b.send()
You may also create a :class:`.Mutator` directly, allowing operations
on multiple column families:
.. code-block:: python
>>> b = Mutator(pool)
>>> b.insert(cf, 'key1', {'col1':'value1', 'col2':'value2'})
>>> b.insert(supercf, 'key1', {'subkey1': {'col1':'value1', 'col2':'value2'}})
>>> b.send()
.. note:: This interface does not implement atomic operations across column
families. All the limitations of the `batch_mutate` Thrift API call
applies. Remember, a mutation in Cassandra is always atomic per key per
column family only.
.. note:: If a single operation in a batch fails, the whole batch fails.
In Python >= 2.5, mutators can be used as context managers, where an implicit
:meth:`send` will be called upon exit.
.. code-block:: python
>>> with cf.batch() as b:
... b.insert('key1', {'col1':'value11', 'col2':'value21'})
... b.insert('key2', {'col1':'value12', 'col2':'value22'})
Calls to :meth:`insert` and :meth:`remove` can also be chained:
.. code-block:: python
>>> cf.batch().remove('foo').remove('bar').send()
import threading
from pycassa.cassandra.ttypes import (ConsistencyLevel, Deletion, Mutation, SlicePredicate)
__all__ = ['Mutator', 'CfMutator']
class Mutator(object):
Batch update convenience mechanism.
Queues insert/update/remove operations and executes them when the queue
is full or `send` is called explicitly.
def __init__(self, pool, queue_size=100, write_consistency_level=None, allow_retries=True):
`pool` is the :class:`~pycassa.pool.ConnectionPool` that will be used
for operations.
After `queue_size` operations, :meth:`send()` will be executed
automatically. Use 0 to disable automatic sends.
self._buffer = []
self._lock = threading.RLock()
self.pool = pool
self.limit = queue_size
self.allow_retries = allow_retries
if write_consistency_level is None:
self.write_consistency_level = ConsistencyLevel.ONE
self.write_consistency_level = write_consistency_level
def __enter__(self):
return self
def __exit__(self, exc_type, exc_value, traceback):
def _enqueue(self, key, column_family, mutations):
mutation = (key, column_family.column_family, mutations)
if self.limit and len(self._buffer) >= self.limit:
return self
def send(self, write_consistency_level=None):
""" Sends all operations currently in the batch and clears the batch. """
if write_consistency_level is None:
write_consistency_level = self.write_consistency_level
mutations = {}
conn = None
for key, column_family, cols in self._buffer:
mutations.setdefault(key, {}).setdefault(column_family, []).extend(cols)
if mutations:
conn = self.pool.get()
conn.batch_mutate(mutations, write_consistency_level,
self._buffer = []
if conn:
def insert(self, column_family, key, columns, timestamp=None, ttl=None):
Adds a single row insert to the batch.
`column_family` is the :class:`~pycassa.columnfamily.ColumnFamily`
that the insert will be executed on.
If this is used on a counter column family, integers may be used for
column values, and they will be taken as counter adjustments.
if columns:
if timestamp is None:
timestamp = column_family.timestamp()
packed_key = column_family._pack_key(key)
mut_list = column_family._make_mutation_list(columns, timestamp, ttl)
self._enqueue(packed_key, column_family, mut_list)
return self
def remove(self, column_family, key, columns=None, super_column=None, timestamp=None):
Adds a single row remove to the batch.
`column_family` is the :class:`~pycassa.columnfamily.ColumnFamily`
that the remove will be executed on.
if timestamp is None:
timestamp = column_family.timestamp()
deletion = Deletion(timestamp=timestamp)
_pack_name = column_family._pack_name
if super_column is not None:
deletion.super_column = _pack_name(super_column, True)
if columns is not None:
is_super = column_family.super and super_column is None
packed_cols = [_pack_name(col, is_super) for col in columns]
deletion.predicate = SlicePredicate(column_names=packed_cols)
mutation = Mutation(deletion=deletion)
packed_key = column_family._pack_key(key)
self._enqueue(packed_key, column_family, (mutation,))
return self
class CfMutator(Mutator):
A :class:`~pycassa.batch.Mutator` that deals only with one column family.
def __init__(self, column_family, queue_size=100, write_consistency_level=None,
`column_family` is the :class:`~pycassa.columnfamily.ColumnFamily`
that all operations will be executed on.
wcl = write_consistency_level or column_family.write_consistency_level
Mutator.__init__(self, column_family.pool, queue_size, wcl, allow_retries)
self._column_family = column_family
def insert(self, key, cols, timestamp=None, ttl=None):
""" Adds a single row insert to the batch. """
return Mutator.insert(self, self._column_family, key, cols, timestamp, ttl)
def remove(self, key, columns=None, super_column=None, timestamp=None):
""" Adds a single row remove to the batch. """
return Mutator.remove(self, self._column_family, key,
columns, super_column, timestamp)
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