The document details benchmarking methodologies for the Cassandra Python driver in handling concurrency, particularly for pushing messages from a RabbitMQ queue into a Cassandra table. It outlines the structure of the message data, various configurations for submitting queries, and options for executing tests with different concurrency levels and consistency settings. The results of the benchmarking tests are formatted as JSON output.

2. Cassandra python driver
Benchmarking concurrency for nyt⨍aбrik
Michael.Laing@nytimes.com

12. A Global Mesh with a Memory
Message-based: WebSocket, AMQP, SockJS
If in doubt:
• Resend
• Reconnect
• Reread
Idempotent:
• Replicating
• Racy
• Resolving
Classes of service:
• Gold: replicate/race
• Silver: prioritize
• Bronze: queueable
Millions of users

14. Message: an event with data
CREATE TABLE source_data (
hash_key int, -- real ones are more complex
message_id timeuuid,
body blob, -- whatever
metadata text, -- JSON
PRIMARY KEY (hash_key, message_id)
);

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Synchronous:
C* Thrift or
CQL Native

20. Concurrent
Degree = 3
(using the
Libev event
Loop)
Asynchronous:
CQL Native only

21. More Concurrency
Can also try:
• DC Aware
• Token Aware
• Subprocessing

22. Build one
def build_message(self):
message = {
"message_id": str(uuid.uuid1()),
"hash_key": randint(0, self._hash_key_range), # int(e ** 8)
"app_id": self._app_id,
"timestamp": datetime.utcnow().isoformat() + 'Z',
"content_type": "application/binary",
"body": os.urandom(randint(1, self._body_range)) # int(e ** 9)
}

23. Kick-off
def push_message(self):
if self._submitted_count.next() < self._message_count:
message = self.build_message()
self.submit_query(message)
def push_initial_data(self):
self._start_time = time()
try:
with self._lock:
for i in range(
0, min(CONCURRENCY, self._message_count)
):
self.push_message()

24. Put it in the pipeline
def submit_query(self, message):
body = message.pop('body')
substitution_args = (
json.dumps(message, **JSON_DUMPS_ARGS),
body,
message['hash_key'],
uuid.UUID(message['message_id'])
)
future = self._cql_session.execute_async(
self._query, substitution_args
)
future.add_callback(self.push_or_finish)
future.add_errback(self.note_error)

25. Maintain concurrency or finish
def push_or_finish(self, _):
try:
if (
self._unfinished and
self._confirmed_count.next() < self._message_count
):
with self._lock:
self.push_message()
else:
self.finish()

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39. Push some messages
usage: bm_push.py [-h] [-c [CQL_HOST [CQL_HOST ...]]] [-d LOCAL_DC]
[--remote-dc-hosts REMOTE_DC_HOSTS] [-p PREFETCH_COUNT]
[-w WORKER_COUNT] [-a] [-t]
[-n {ONE, TWO, THREE, QUORUM, ALL, LOCAL_QUORUM,
EACH_QUORUM, SERIAL, LOCAL_SERIAL, LOCAL_ONE}]
[-r] [-j] [-l
{CRITICAL,ERROR,WARNING,INFO,DEBUG,NOTSET}]
Push messages from a RabbitMQ queue into a Cassandra table.

40. Push messages many times
usage: run_push.py [-h] [-c [CQL_HOST [CQL_HOST ...]]] [-i ITERATIONS]
[-d LOCAL_DC] [-w [worker_count [worker_count ...]]]
[-p [prefetch_count [prefetch_count ...]]]
[-n [level [level ...]]] [-a] [-t] [-m MESSAGE_EXPONENT]
[-b BODY_EXPONENT]
[-l {CRITICAL,ERROR,WARNING,INFO,DEBUG,NOTSET}]
Run multiple test cases based upon the product of worker_counts,
prefetch_counts, and consistency_levels. Each test case may be run with up to
4 variations reflecting the use or not of the dc_aware and token_aware
policies. The results are output to stdout as a JSON object.

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