def _generate_workers(self, files, state, start_utc_secs, end_utc_secs):
"""Generate the threads that tails the data sources and put the fetched
entries to the files"""
# Create working threads to handle to track/dump mongodb activities
workers_info = []
doc_queue = Queue.Queue()
# Writer thread, we only have one writer since we assume all files will
# be written to the same device (disk or SSD), as a result it yields
# not much benefit to have multiple writers.
workers_info.append({
"name": "write-all-docs-to-file",
"thread": Thread(
target=MongoQueryRecorder._process_doc_queue,
args=(doc_queue, files, state))
})
tailer = utils.get_oplog_tailer(self.oplog_client,
# we are only interested in "insert"
["i"],
self.config["target_databases"],
self.config["target_collections"],
Timestamp(start_utc_secs, 0))
oplog_cursor_id = tailer.cursor_id
workers_info.append({
"name": "tailing-oplogs",
"on_close":
lambda: self.oplog_client.kill_cursors([oplog_cursor_id]),
"thread": Thread(
target=tail_to_queue,
args=(tailer, "oplog", doc_queue, state,
Timestamp(end_utc_secs, 0)))
})
start_datetime = datetime.utcfromtimestamp(start_utc_secs)
end_datetime = datetime.utcfromtimestamp(end_utc_secs)
for profiler_name,client in self.profiler_clients.items():
# create a profile collection tailer for each db
for db in self.config["target_databases"]:
tailer = utils.get_profiler_tailer(client,
db,
self.config["target_collections"],
start_datetime)
tailer_id = "%s_%s" % (db, profiler_name)
profiler_cursor_id = tailer.cursor_id
workers_info.append({
"name": "tailing-profiler for %s on %s" % (db, profiler_name),
"on_close":
lambda: self.profiler_client.kill_cursors([profiler_cursor_id]),
"thread": Thread(
target=tail_to_queue,
args=(tailer, tailer_id, doc_queue, state,
end_datetime))
})
for worker_info in workers_info:
utils.LOG.info("Starting thread: %s", worker_info["name"])
worker_info["thread"].setDaemon(True)
worker_info["thread"].start()
return workers_info
def _generate_workers(self, files, state, start_utc_secs, end_utc_secs):
"""Generate the threads that tail the data sources and put the fetched
entries to the files"""
# Initialize a thread-safe queue that we'll put the docs into
doc_queue = Queue.Queue()
# Initialize a list that will keep track of all the worker threads that
# handle tracking/dumping of mongodb activities
workers_info = []
# Writer thread, we only have one writer since we assume all files will
# be written to the same device (disk or SSD), as a result it yields
# not much benefit to have multiple writers.
workers_info.append({
"name":
WRITER_THREAD_NAME,
"thread":
Thread(target=MongoQueryRecorder._process_doc_queue,
args=(doc_queue, files, state))
})
# For each server in the "oplog_servers" config...
for server_string, mongo_client in self.oplog_clients.items():
# Create a tailing cursor (aka a tailer) on an oplog collection.
# "i" stands for the only op type we care about, which is an insert
tailer = utils.get_oplog_tailer(mongo_client, ["i"],
self.config["target_databases"],
self.config["target_collections"],
Timestamp(start_utc_secs, 0))
# Create a new thread and add some metadata to it
workers_info.append({
"name":
"tailing-oplogs on %s" % server_string,
"on_close":
lambda: self.oplog_client.kill_cursors([tailer.cursor_id]),
"thread":
Thread(target=tail_to_queue,
args=(tailer, "oplog", doc_queue, state,
Timestamp(end_utc_secs, 0)))
})
start_datetime = datetime.utcfromtimestamp(start_utc_secs)
end_datetime = datetime.utcfromtimestamp(end_utc_secs)
# For each server in the "profiler_servers" config...
for server_string, mongo_client in self.profiler_clients.items():
# For each database in the "target_databases" config...
for db in self.config["target_databases"]:
# Create a tailing cursor (aka a tailer) on a profile collection
tailer = utils.get_profiler_tailer(
mongo_client, db, self.config["target_collections"],
start_datetime)
# Create a new thread and add some metadata to it
tailer_id = "%s_%s" % (db, server_string)
workers_info.append({
"name":
"tailing-profiler for %s on %s" % (db, server_string),
"on_close":
lambda: self.profiler_client.kill_cursors(
[tailer.cursor_id]),
"thread":
Thread(target=tail_to_queue,
args=(tailer, tailer_id, doc_queue, state,
end_datetime))
})
# Deamonize each thread and start it
for worker_info in workers_info:
utils.LOG.info("Starting thread: %s", worker_info["name"])
worker_info["thread"].setDaemon(True)
worker_info["thread"].start()
# Return the list of all the started threads
return workers_info
def _generate_workers(self, files, state, start_utc_secs, end_utc_secs):
"""Generate the threads that tail the data sources and put the fetched
entries to the files"""
# Initialize a thread-safe queue that we'll put the docs into
doc_queue = Queue.Queue()
# Initialize a list that will keep track of all the worker threads that
# handle tracking/dumping of mongodb activities
workers_info = []
# Writer thread, we only have one writer since we assume all files will
# be written to the same device (disk or SSD), as a result it yields
# not much benefit to have multiple writers.
workers_info.append({
"name": "write-all-docs-to-file",
"thread": Thread(
target=MongoQueryRecorder._process_doc_queue,
args=(doc_queue, files, state))
})
# For each server in the "oplog_servers" config...
for server_string, mongo_client in self.oplog_clients.items():
# Create a tailing cursor (aka a tailer) on an oplog collection.
# "i" stands for the only op type we care about, which is an insert
tailer = utils.get_oplog_tailer(mongo_client, ["i"],
self.config["target_databases"],
self.config["target_collections"],
Timestamp(start_utc_secs, 0))
# Create a new thread and add some metadata to it
workers_info.append({
"name": "tailing-oplogs on %s" % server_string,
"on_close":
lambda: self.oplog_client.kill_cursors([tailer.cursor_id]),
"thread": Thread(
target=tail_to_queue,
args=(tailer, "oplog", doc_queue, state,
Timestamp(end_utc_secs, 0)))
})
start_datetime = datetime.utcfromtimestamp(start_utc_secs)
end_datetime = datetime.utcfromtimestamp(end_utc_secs)
# For each server in the "profiler_servers" config...
for server_string, mongo_client in self.profiler_clients.items():
# For each database in the "target_databases" config...
for db in self.config["target_databases"]:
# Create a tailing cursor (aka a tailer) on a profile collection
tailer = utils.get_profiler_tailer(mongo_client, db,
self.config["target_collections"],
start_datetime)
# Create a new thread and add some metadata to it
tailer_id = "%s_%s" % (db, server_string)
workers_info.append({
"name": "tailing-profiler for %s on %s" % (db, server_string),
"on_close":
lambda: self.profiler_client.kill_cursors([tailer.cursor_id]),
"thread": Thread(
target=tail_to_queue,
args=(tailer, tailer_id, doc_queue, state,
end_datetime))
})
# Deamonize each thread and start it
for worker_info in workers_info:
utils.LOG.info("Starting thread: %s", worker_info["name"])
worker_info["thread"].setDaemon(True)
worker_info["thread"].start()
# Return the list of all the started threads
return workers_info
def _generate_workers(self, files, state, start_utc_secs, end_utc_secs):
"""Generate the threads that tails the data sources and put the fetched
entries to the files"""
# Create working threads to handle to track/dump mongodb activities
workers_info = []
doc_queue = Queue.Queue()
# Writer thread, we only have one writer since we assume all files will
# be written to the same device (disk or SSD), as a result it yields
# not much benefit to have multiple writers.
workers_info.append({
"name":
"write-all-docs-to-file",
"thread":
Thread(target=MongoQueryRecorder._process_doc_queue,
args=(doc_queue, files, state))
})
tailer = utils.get_oplog_tailer(
self.oplog_client,
# we are only interested in "insert"
["i"],
self.config["target_databases"],
self.config["target_collections"],
Timestamp(start_utc_secs, 0))
oplog_cursor_id = tailer.cursor_id
workers_info.append({
"name":
"tailing-oplogs",
"on_close":
lambda: self.oplog_client.kill_cursors([oplog_cursor_id]),
"thread":
Thread(target=tail_to_queue,
args=(tailer, "oplog", doc_queue, state,
Timestamp(end_utc_secs, 0)))
})
start_datetime = datetime.utcfromtimestamp(start_utc_secs)
end_datetime = datetime.utcfromtimestamp(end_utc_secs)
for profiler_name, client in self.profiler_clients.items():
# create a profile collection tailer for each db
for db in self.config["target_databases"]:
tailer = utils.get_profiler_tailer(
client, db, self.config["target_collections"],
start_datetime)
tailer_id = "%s_%s" % (db, profiler_name)
profiler_cursor_id = tailer.cursor_id
workers_info.append({
"name":
"tailing-profiler for %s on %s" % (db, profiler_name),
"on_close":
lambda: self.profiler_client.kill_cursors(
[profiler_cursor_id]),
"thread":
Thread(target=tail_to_queue,
args=(tailer, tailer_id, doc_queue, state,
end_datetime))
})
for worker_info in workers_info:
utils.LOG.info("Starting thread: %s", worker_info["name"])
worker_info["thread"].setDaemon(True)
worker_info["thread"].start()
return workers_info
