def large_batch(self, app, mutations, entity_changes, txn):
""" Insert or delete multiple rows across tables in an atomic statement.
Args:
app: A string containing the application ID.
mutations: A list of dictionaries representing mutations.
entity_changes: A list of changes at the entity level.
txn: A transaction ID handler.
Raises:
FailedBatch if a concurrent process modifies the batch status.
AppScaleDBConnectionError if a database connection error was encountered.
"""
self.logger.debug('Large batch: transaction {}, {} mutations'.format(
txn, len(mutations)))
large_batch = LargeBatch(self.session, app, txn)
try:
yield large_batch.start()
except FailedBatch as batch_error:
raise BatchNotApplied(str(batch_error))
insert_item = ('INSERT INTO batches (app, transaction, namespace, '
' path, old_value, new_value) '
'VALUES (?, ?, ?, ?, ?, ?)')
insert_statement = self.session.prepare(insert_item)
statements_and_params = []
for entity_change in entity_changes:
old_value = None
if entity_change['old'] is not None:
old_value = bytearray(entity_change['old'].Encode())
new_value = None
if entity_change['new'] is not None:
new_value = bytearray(entity_change['new'].Encode())
parameters = (app, txn, entity_change['key'].name_space(),
bytearray(entity_change['key'].path().Encode()),
old_value, new_value)
statements_and_params.append((insert_statement, parameters))
try:
yield [
self.tornado_cassandra.execute(statement, parameters=params)
for statement, params in statements_and_params
]
except dbconstants.TRANSIENT_CASSANDRA_ERRORS:
message = 'Unable to write large batch log'
logger.exception(message)
raise BatchNotApplied(message)
# Since failing after this point is expensive and time consuming, retry
# operations to make a failure less likely.
custom_retry_coroutine = retry_raw_coroutine(
backoff_threshold=5,
retrying_timeout=10,
retry_on_exception=dbconstants.TRANSIENT_CASSANDRA_ERRORS)
persistent_apply_batch = custom_retry_coroutine(
large_batch.set_applied)
try:
yield persistent_apply_batch()
except FailedBatch as batch_error:
raise AppScaleDBConnectionError(str(batch_error))
persistent_apply_mutations = custom_retry_coroutine(
self.apply_mutations)
try:
yield persistent_apply_mutations(mutations, txn)
except dbconstants.TRANSIENT_CASSANDRA_ERRORS:
message = 'Exception during large batch'
logger.exception(message)
raise AppScaleDBConnectionError(message)
try:
yield large_batch.cleanup()
except FailedBatch:
# This should not raise an exception since the batch is already applied.
logger.exception('Unable to clear batch status')
clear_batch = ('DELETE FROM batches '
'WHERE app = %(app)s AND transaction = %(transaction)s')
parameters = {'app': app, 'transaction': txn}
try:
yield self.tornado_cassandra.execute(clear_batch, parameters)
except dbconstants.TRANSIENT_CASSANDRA_ERRORS:
logger.exception('Unable to clear batch log')
def large_batch(self, app, mutations, entity_changes, txn):
""" Insert or delete multiple rows across tables in an atomic statement.
Args:
app: A string containing the application ID.
mutations: A list of dictionaries representing mutations.
entity_changes: A list of changes at the entity level.
txn: A transaction ID handler.
Raises:
FailedBatch if a concurrent process modifies the batch status.
AppScaleDBConnectionError if a database connection error was encountered.
"""
self.logger.debug('Large batch: transaction {}, {} mutations'.
format(txn, len(mutations)))
large_batch = LargeBatch(self.session, app, txn)
try:
yield large_batch.start()
except FailedBatch as batch_error:
raise BatchNotApplied(str(batch_error))
insert_item = (
'INSERT INTO batches (app, transaction, namespace, '
' path, old_value, new_value) '
'VALUES (?, ?, ?, ?, ?, ?)'
)
insert_statement = self.session.prepare(insert_item)
statements_and_params = []
for entity_change in entity_changes:
old_value = None
if entity_change['old'] is not None:
old_value = bytearray(entity_change['old'].Encode())
new_value = None
if entity_change['new'] is not None:
new_value = bytearray(entity_change['new'].Encode())
parameters = (app, txn, entity_change['key'].name_space(),
bytearray(entity_change['key'].path().Encode()), old_value,
new_value)
statements_and_params.append((insert_statement, parameters))
try:
yield [
self.tornado_cassandra.execute(statement, parameters=params)
for statement, params in statements_and_params
]
except dbconstants.TRANSIENT_CASSANDRA_ERRORS:
message = 'Unable to write large batch log'
logger.exception(message)
raise BatchNotApplied(message)
# Since failing after this point is expensive and time consuming, retry
# operations to make a failure less likely.
custom_retry_coroutine = retry_raw_coroutine(
backoff_threshold=5, retrying_timeout=10,
retry_on_exception=dbconstants.TRANSIENT_CASSANDRA_ERRORS)
persistent_apply_batch = custom_retry_coroutine(large_batch.set_applied)
try:
yield persistent_apply_batch()
except FailedBatch as batch_error:
raise AppScaleDBConnectionError(str(batch_error))
persistent_apply_mutations = custom_retry_coroutine(self.apply_mutations)
try:
yield persistent_apply_mutations(mutations, txn)
except dbconstants.TRANSIENT_CASSANDRA_ERRORS:
message = 'Exception during large batch'
logger.exception(message)
raise AppScaleDBConnectionError(message)
try:
yield large_batch.cleanup()
except FailedBatch:
# This should not raise an exception since the batch is already applied.
logger.exception('Unable to clear batch status')
clear_batch = (
'DELETE FROM batches '
'WHERE app = %(app)s AND transaction = %(transaction)s'
)
parameters = {'app': app, 'transaction': txn}
try:
yield self.tornado_cassandra.execute(clear_batch, parameters)
except dbconstants.TRANSIENT_CASSANDRA_ERRORS:
logger.exception('Unable to clear batch log')