def generate_leader_raw_data(self):
dbm = data_block_manager.DataBlockManager(self.data_source_l, 0)
raw_data_dir = os.path.join(self.data_source_l.raw_data_dir,
common.partition_repr(0))
if gfile.Exists(raw_data_dir):
gfile.DeleteRecursively(raw_data_dir)
gfile.MakeDirs(raw_data_dir)
rdm = raw_data_visitor.RawDataManager(self.etcd, self.data_source_l, 0)
block_index = 0
builder = create_data_block_builder(
dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'),
self.data_source_l.raw_data_dir,
self.data_source_l.data_source_meta.name, 0, block_index, None)
process_index = 0
start_index = 0
for i in range(0, self.leader_end_index + 3):
if (i > 0 and i % 2048 == 0) or (i == self.leader_end_index + 2):
meta = builder.finish_data_block()
if meta is not None:
ofname = common.encode_data_block_fname(
self.data_source_l.data_source_meta.name, meta)
fpath = os.path.join(raw_data_dir, ofname)
self.manifest_manager.add_raw_data(0, [
dj_pb.RawDataMeta(
file_path=fpath,
timestamp=timestamp_pb2.Timestamp(seconds=3))
], False)
process_index += 1
start_index += len(meta.example_ids)
block_index += 1
builder = create_data_block_builder(
dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'),
self.data_source_l.raw_data_dir,
self.data_source_l.data_source_meta.name, 0, block_index,
None)
feat = {}
pt = i + 1 << 30
if i % 3 == 0:
pt = i // 3
example_id = '{}'.format(pt).encode()
feat['example_id'] = tf.train.Feature(
bytes_list=tf.train.BytesList(value=[example_id]))
event_time = 150000000 + pt
feat['event_time'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[event_time]))
example = tf.train.Example(features=tf.train.Features(
feature=feat))
builder.append_record(example.SerializeToString(), example_id,
event_time, i, i)
fpaths = [
os.path.join(raw_data_dir, f)
for f in gfile.ListDirectory(raw_data_dir)
if not gfile.IsDirectory(os.path.join(raw_data_dir, f))
]
for fpath in fpaths:
if not fpath.endswith(common.DataBlockSuffix):
gfile.Remove(fpath)
def _create_data_block(self, partition_id):
dbm = data_block_manager.DataBlockManager(self.data_source,
partition_id)
self.assertEqual(dbm.get_dumped_data_block_count(), 0)
self.assertEqual(dbm.get_lastest_data_block_meta(), None)
leader_index = 0
follower_index = 65536
for i in range(64):
builder = create_data_block_builder(
dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'),
self.data_source.data_block_dir,
self.data_source.data_source_meta.name, partition_id, i, None)
builder.set_data_block_manager(dbm)
for j in range(4):
feat = {}
example_id = '{}'.format(i * 1024 + j).encode()
feat['example_id'] = tf.train.Feature(
bytes_list=tf.train.BytesList(value=[example_id]))
event_time = random.randint(0, 10)
feat['event_time'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[event_time]))
feat['leader_index'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[leader_index]))
feat['follower_index'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[follower_index]))
example = tf.train.Example(features=tf.train.Features(
feature=feat))
builder.append_record(example.SerializeToString(), example_id,
event_time, leader_index, follower_index)
leader_index += 1
follower_index += 1
self.data_block_matas.append(builder.finish_data_block())
def _launch_workers(self):
worker_options = dj_pb.DataJoinWorkerOptions(
use_mock_etcd=True,
raw_data_options=dj_pb.RawDataOptions(raw_data_iter='CSV_DICT',
compressed_type=''),
example_id_dump_options=dj_pb.ExampleIdDumpOptions(
example_id_dump_interval=1, example_id_dump_threshold=1024),
example_joiner_options=dj_pb.ExampleJoinerOptions(
example_joiner='SORT_RUN_JOINER',
min_matching_window=64,
max_matching_window=256,
data_block_dump_interval=30,
data_block_dump_threshold=1000),
batch_processor_options=dj_pb.BatchProcessorOptions(
batch_size=1024, max_flying_item=4096),
data_block_builder_options=dj_pb.DataBlockBuilderOptions(
data_block_builder='CSV_DICT_DATABLOCK_BUILDER'))
self._worker_addrs_l = [
'localhost:4161', 'localhost:4162', 'localhost:4163',
'localhost:4164'
]
self._worker_addrs_f = [
'localhost:5161', 'localhost:5162', 'localhost:5163',
'localhost:5164'
]
self._workers_l = []
self._workers_f = []
for rank_id in range(4):
worker_addr_l = self._worker_addrs_l[rank_id]
worker_addr_f = self._worker_addrs_f[rank_id]
self._workers_l.append(
data_join_worker.DataJoinWorkerService(
int(worker_addr_l.split(':')[1]), worker_addr_f,
self._master_addr_l, rank_id, self._etcd_name,
self._etcd_base_dir_l, self._etcd_addrs, worker_options))
self._workers_f.append(
data_join_worker.DataJoinWorkerService(
int(worker_addr_f.split(':')[1]), worker_addr_l,
self._master_addr_f, rank_id, self._etcd_name,
self._etcd_base_dir_f, self._etcd_addrs, worker_options))
for w in self._workers_l:
w.start()
for w in self._workers_f:
w.start()
def generate_follower_data_block(self):
dbm = data_block_manager.DataBlockManager(self.data_source_f, 0)
self.assertEqual(dbm.get_dumped_data_block_count(), 0)
self.assertEqual(dbm.get_lastest_data_block_meta(), None)
leader_index = 0
follower_index = 65536
self.dumped_metas = []
for i in range(5):
builder = create_data_block_builder(
dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'),
self.data_source_f.data_block_dir,
self.data_source_f.data_source_meta.name, 0, i, None)
builder.set_data_block_manager(dbm)
for j in range(1024):
feat = {}
example_id = '{}'.format(i * 1024 + j).encode()
feat['example_id'] = tf.train.Feature(
bytes_list=tf.train.BytesList(value=[example_id]))
event_time = 150000000 + i * 1024 + j
feat['event_time'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[event_time]))
feat['leader_index'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[leader_index]))
feat['follower_index'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[follower_index]))
example = tf.train.Example(features=tf.train.Features(
feature=feat))
builder.append_record(example.SerializeToString(), example_id,
event_time, leader_index, follower_index)
leader_index += 3
follower_index += 1
meta = builder.finish_data_block()
self.dumped_metas.append(meta)
self.leader_start_index = 0
self.leader_end_index = leader_index
self.assertEqual(dbm.get_dumped_data_block_count(), 5)
for (idx, meta) in enumerate(self.dumped_metas):
self.assertEqual(dbm.get_data_block_meta_by_index(idx), meta)
def test_data_block_dumper(self):
self.generate_follower_data_block()
self.generate_leader_raw_data()
dbd = data_block_dumper.DataBlockDumperManager(
self.etcd,
self.data_source_l,
0,
dj_pb.RawDataOptions(raw_data_iter='TF_RECORD'),
dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'),
)
self.assertEqual(dbd.get_next_data_block_index(), 0)
for (idx, meta) in enumerate(self.dumped_metas):
success, next_index = dbd.add_synced_data_block_meta(meta)
self.assertTrue(success)
self.assertEqual(next_index, idx + 1)
self.assertTrue(dbd.need_dump())
self.assertEqual(dbd.get_next_data_block_index(),
len(self.dumped_metas))
with dbd.make_data_block_dumper() as dumper:
dumper()
dbm_f = data_block_manager.DataBlockManager(self.data_source_f, 0)
dbm_l = data_block_manager.DataBlockManager(self.data_source_l, 0)
self.assertEqual(dbm_f.get_dumped_data_block_count(),
len(self.dumped_metas))
self.assertEqual(dbm_f.get_dumped_data_block_count(),
dbm_l.get_dumped_data_block_count())
for (idx, meta) in enumerate(self.dumped_metas):
self.assertEqual(meta.data_block_index, idx)
self.assertEqual(dbm_l.get_data_block_meta_by_index(idx), meta)
self.assertEqual(dbm_f.get_data_block_meta_by_index(idx), meta)
meta_fpth_l = os.path.join(
self.data_source_l.data_block_dir, common.partition_repr(0),
common.encode_data_block_meta_fname(
self.data_source_l.data_source_meta.name, 0,
meta.data_block_index))
mitr = tf.io.tf_record_iterator(meta_fpth_l)
meta_l = text_format.Parse(next(mitr), dj_pb.DataBlockMeta())
self.assertEqual(meta_l, meta)
meta_fpth_f = os.path.join(
self.data_source_f.data_block_dir, common.partition_repr(0),
common.encode_data_block_meta_fname(
self.data_source_f.data_source_meta.name, 0,
meta.data_block_index))
mitr = tf.io.tf_record_iterator(meta_fpth_f)
meta_f = text_format.Parse(next(mitr), dj_pb.DataBlockMeta())
self.assertEqual(meta_f, meta)
data_fpth_l = os.path.join(
self.data_source_l.data_block_dir, common.partition_repr(0),
common.encode_data_block_fname(
self.data_source_l.data_source_meta.name, meta_l))
for (iidx,
record) in enumerate(tf.io.tf_record_iterator(data_fpth_l)):
example = tf.train.Example()
example.ParseFromString(record)
feat = example.features.feature
self.assertEqual(feat['example_id'].bytes_list.value[0],
meta.example_ids[iidx])
self.assertEqual(len(meta.example_ids), iidx + 1)
data_fpth_f = os.path.join(
self.data_source_f.data_block_dir, common.partition_repr(0),
common.encode_data_block_fname(
self.data_source_l.data_source_meta.name, meta_f))
for (iidx,
record) in enumerate(tf.io.tf_record_iterator(data_fpth_f)):
example = tf.train.Example()
example.ParseFromString(record)
feat = example.features.feature
self.assertEqual(feat['example_id'].bytes_list.value[0],
meta.example_ids[iidx])
self.assertEqual(len(meta.example_ids), iidx + 1)
args = parser.parse_args()
if args.tf_eager_mode:
import tensorflow
tensorflow.compat.v1.enable_eager_execution()
worker_options = dj_pb.DataJoinWorkerOptions(
use_mock_etcd=args.use_mock_etcd,
raw_data_options=dj_pb.RawDataOptions(
raw_data_iter=args.raw_data_iter,
compressed_type=args.compressed_type,
read_ahead_size=args.read_ahead_size),
example_joiner_options=dj_pb.ExampleJoinerOptions(
example_joiner=args.example_joiner,
min_matching_window=args.min_matching_window,
max_matching_window=args.max_matching_window,
data_block_dump_interval=args.data_block_dump_interval,
data_block_dump_threshold=args.data_block_dump_threshold,
),
example_id_dump_options=dj_pb.ExampleIdDumpOptions(
example_id_dump_interval=args.example_id_dump_interval,
example_id_dump_threshold=args.example_id_dump_threshold),
batch_processor_options=dj_pb.BatchProcessorOptions(
batch_size=args.example_id_batch_size,
max_flying_item=args.max_flying_example_id),
data_block_builder_options=dj_pb.DataBlockBuilderOptions(
data_block_builder=args.data_block_builder))
worker_srv = DataJoinWorkerService(args.listen_port, args.peer_addr,
args.master_addr, args.rank_id,
args.etcd_name, args.etcd_base_dir,
args.etcd_addrs, worker_options)
worker_srv.run()
def test_data_block_manager(self):
data_block_datas = []
data_block_metas = []
leader_index = 0
follower_index = 65536
for i in range(5):
fill_examples = []
builder = create_data_block_builder(
dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'),
self.data_source.data_block_dir,
self.data_source.data_source_meta.name, 0, i, None)
builder.set_data_block_manager(self.data_block_manager)
for j in range(1024):
feat = {}
example_id = '{}'.format(i * 1024 + j).encode()
feat['example_id'] = tf.train.Feature(
bytes_list=tf.train.BytesList(value=[example_id]))
event_time = 150000000 + i * 1024 + j
feat['event_time'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[event_time]))
feat['leader_index'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[leader_index]))
feat['follower_index'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[follower_index]))
example = tf.train.Example(features=tf.train.Features(
feature=feat))
builder.append_record(example.SerializeToString(), example_id,
event_time, leader_index, follower_index)
fill_examples.append((example, {
'example_id': example_id,
'event_time': event_time,
'leader_index': leader_index,
'follower_index': follower_index
}))
leader_index += 1
follower_index += 1
meta = builder.finish_data_block()
data_block_datas.append(fill_examples)
data_block_metas.append(meta)
self.assertEqual(self.data_block_manager.get_dumped_data_block_count(),
5)
self.assertEqual(self.data_block_manager.get_lastest_data_block_meta(),
data_block_metas[-1])
for (idx, meta) in enumerate(data_block_metas):
self.assertEqual(
self.data_block_manager.get_data_block_meta_by_index(idx),
meta)
self.assertEqual(
meta.block_id,
common.encode_block_id(self.data_source.data_source_meta.name,
meta))
self.assertEqual(
self.data_block_manager.get_data_block_meta_by_index(5), None)
data_block_dir = os.path.join(self.data_source.data_block_dir,
common.partition_repr(0))
for (i, meta) in enumerate(data_block_metas):
data_block_fpath = os.path.join(
data_block_dir, meta.block_id) + common.DataBlockSuffix
data_block_meta_fpath = os.path.join(
data_block_dir,
common.encode_data_block_meta_fname(
self.data_source.data_source_meta.name, 0,
meta.data_block_index))
self.assertTrue(gfile.Exists(data_block_fpath))
self.assertTrue(gfile.Exists(data_block_meta_fpath))
fiter = tf.io.tf_record_iterator(data_block_meta_fpath)
remote_meta = text_format.Parse(
next(fiter).decode(), dj_pb.DataBlockMeta())
self.assertEqual(meta, remote_meta)
for (j, record) in enumerate(
tf.io.tf_record_iterator(data_block_fpath)):
example = tf.train.Example()
example.ParseFromString(record)
stored_data = data_block_datas[i][j]
self.assertEqual(example, stored_data[0])
feat = example.features.feature
stored_feat = stored_data[1]
self.assertTrue('example_id' in feat)
self.assertTrue('example_id' in stored_feat)
self.assertEqual(stored_feat['example_id'],
'{}'.format(i * 1024 + j).encode())
self.assertEqual(stored_feat['example_id'],
feat['example_id'].bytes_list.value[0])
self.assertTrue('event_time' in feat)
self.assertTrue('event_time' in stored_feat)
self.assertEqual(stored_feat['event_time'],
feat['event_time'].int64_list.value[0])
self.assertTrue('leader_index' in feat)
self.assertTrue('leader_index' in stored_feat)
self.assertEqual(stored_feat['leader_index'],
feat['leader_index'].int64_list.value[0])
self.assertTrue('follower_index' in feat)
self.assertTrue('follower_index' in stored_feat)
self.assertEqual(stored_feat['follower_index'],
feat['follower_index'].int64_list.value[0])
self.assertEqual(j, 1023)
data_block_manager2 = data_block_manager.DataBlockManager(
self.data_source, 0)
self.assertEqual(self.data_block_manager.get_dumped_data_block_count(),
5)
def setUp(self):
etcd_name = 'test_etcd'
etcd_addrs = 'localhost:2379'
etcd_base_dir_l = 'byefl_l'
etcd_base_dir_f = 'byefl_f'
data_source_name = 'test_data_source'
etcd_l = EtcdClient(etcd_name, etcd_addrs, etcd_base_dir_l, True)
etcd_f = EtcdClient(etcd_name, etcd_addrs, etcd_base_dir_f, True)
etcd_l.delete_prefix(data_source_name)
etcd_f.delete_prefix(data_source_name)
data_source_l = common_pb.DataSource()
self.raw_data_pub_dir_l = './raw_data_pub_dir_l'
data_source_l.raw_data_sub_dir = self.raw_data_pub_dir_l
data_source_l.role = common_pb.FLRole.Leader
data_source_l.state = common_pb.DataSourceState.Init
data_source_l.data_block_dir = "./data_block_l"
data_source_l.raw_data_dir = "./raw_data_l"
data_source_l.example_dumped_dir = "./example_dumped_l"
data_source_f = common_pb.DataSource()
self.raw_data_pub_dir_f = './raw_data_pub_dir_f'
data_source_f.role = common_pb.FLRole.Follower
data_source_f.raw_data_sub_dir = self.raw_data_pub_dir_f
data_source_f.state = common_pb.DataSourceState.Init
data_source_f.data_block_dir = "./data_block_f"
data_source_f.raw_data_dir = "./raw_data_f"
data_source_f.example_dumped_dir = "./example_dumped_f"
data_source_meta = common_pb.DataSourceMeta()
data_source_meta.name = data_source_name
data_source_meta.partition_num = 2
data_source_meta.start_time = 0
data_source_meta.end_time = 100000000
data_source_l.data_source_meta.MergeFrom(data_source_meta)
etcd_l.set_data(os.path.join(data_source_name, 'master'),
text_format.MessageToString(data_source_l))
data_source_f.data_source_meta.MergeFrom(data_source_meta)
etcd_f.set_data(os.path.join(data_source_name, 'master'),
text_format.MessageToString(data_source_f))
master_options = dj_pb.DataJoinMasterOptions(use_mock_etcd=True)
master_addr_l = 'localhost:4061'
master_addr_f = 'localhost:4062'
master_l = data_join_master.DataJoinMasterService(
int(master_addr_l.split(':')[1]),
master_addr_f,
data_source_name,
etcd_name,
etcd_base_dir_l,
etcd_addrs,
master_options,
)
master_l.start()
master_f = data_join_master.DataJoinMasterService(
int(master_addr_f.split(':')[1]), master_addr_l, data_source_name,
etcd_name, etcd_base_dir_f, etcd_addrs, master_options)
master_f.start()
channel_l = make_insecure_channel(master_addr_l, ChannelType.INTERNAL)
master_client_l = dj_grpc.DataJoinMasterServiceStub(channel_l)
channel_f = make_insecure_channel(master_addr_f, ChannelType.INTERNAL)
master_client_f = dj_grpc.DataJoinMasterServiceStub(channel_f)
while True:
req_l = dj_pb.DataSourceRequest(
data_source_meta=data_source_l.data_source_meta)
req_f = dj_pb.DataSourceRequest(
data_source_meta=data_source_f.data_source_meta)
dss_l = master_client_l.GetDataSourceStatus(req_l)
dss_f = master_client_f.GetDataSourceStatus(req_f)
self.assertEqual(dss_l.role, common_pb.FLRole.Leader)
self.assertEqual(dss_f.role, common_pb.FLRole.Follower)
if dss_l.state == common_pb.DataSourceState.Processing and \
dss_f.state == common_pb.DataSourceState.Processing:
break
else:
time.sleep(2)
self.master_client_l = master_client_l
self.master_client_f = master_client_f
self.master_addr_l = master_addr_l
self.master_addr_f = master_addr_f
self.etcd_l = etcd_l
self.etcd_f = etcd_f
self.data_source_l = data_source_l
self.data_source_f = data_source_f
self.master_l = master_l
self.master_f = master_f
self.data_source_name = data_source_name,
self.etcd_name = etcd_name
self.etcd_addrs = etcd_addrs
self.etcd_base_dir_l = etcd_base_dir_l
self.etcd_base_dir_f = etcd_base_dir_f
self.raw_data_publisher_l = raw_data_publisher.RawDataPublisher(
self.etcd_l, self.raw_data_pub_dir_l)
self.raw_data_publisher_f = raw_data_publisher.RawDataPublisher(
self.etcd_f, self.raw_data_pub_dir_f)
if gfile.Exists(data_source_l.data_block_dir):
gfile.DeleteRecursively(data_source_l.data_block_dir)
if gfile.Exists(data_source_l.example_dumped_dir):
gfile.DeleteRecursively(data_source_l.example_dumped_dir)
if gfile.Exists(data_source_l.raw_data_dir):
gfile.DeleteRecursively(data_source_l.raw_data_dir)
if gfile.Exists(data_source_f.data_block_dir):
gfile.DeleteRecursively(data_source_f.data_block_dir)
if gfile.Exists(data_source_f.example_dumped_dir):
gfile.DeleteRecursively(data_source_f.example_dumped_dir)
if gfile.Exists(data_source_f.raw_data_dir):
gfile.DeleteRecursively(data_source_f.raw_data_dir)
self.worker_options = dj_pb.DataJoinWorkerOptions(
use_mock_etcd=True,
raw_data_options=dj_pb.RawDataOptions(raw_data_iter='TF_RECORD',
compressed_type=''),
example_id_dump_options=dj_pb.ExampleIdDumpOptions(
example_id_dump_interval=1, example_id_dump_threshold=1024),
example_joiner_options=dj_pb.ExampleJoinerOptions(
example_joiner='STREAM_JOINER',
min_matching_window=64,
max_matching_window=256,
data_block_dump_interval=30,
data_block_dump_threshold=1000),
batch_processor_options=dj_pb.BatchProcessorOptions(
batch_size=512, max_flying_item=2048),
data_block_builder_options=dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'))
self.total_index = 1 << 13
def generate_raw_data(self, etcd, rdp, data_source, partition_id,
block_size, shuffle_win_size, feat_key_fmt,
feat_val_fmt):
dbm = data_block_manager.DataBlockManager(data_source, partition_id)
raw_data_dir = os.path.join(data_source.raw_data_dir,
common.partition_repr(partition_id))
if gfile.Exists(raw_data_dir):
gfile.DeleteRecursively(raw_data_dir)
gfile.MakeDirs(raw_data_dir)
useless_index = 0
new_raw_data_fnames = []
for block_index in range(self.total_index // block_size):
builder = create_data_block_builder(
dj_pb.DataBlockBuilderOptions(
data_block_builder='TF_RECORD_DATABLOCK_BUILDER'),
data_source.raw_data_dir, data_source.data_source_meta.name,
partition_id, block_index, None)
cands = list(
range(block_index * block_size,
(block_index + 1) * block_size))
start_index = cands[0]
for i in range(len(cands)):
if random.randint(1, 4) > 2:
continue
a = random.randint(i - shuffle_win_size, i + shuffle_win_size)
b = random.randint(i - shuffle_win_size, i + shuffle_win_size)
if a < 0:
a = 0
if a >= len(cands):
a = len(cands) - 1
if b < 0:
b = 0
if b >= len(cands):
b = len(cands) - 1
if (abs(cands[a] - i - start_index) <= shuffle_win_size and
abs(cands[b] - i - start_index) <= shuffle_win_size):
cands[a], cands[b] = cands[b], cands[a]
for example_idx in cands:
feat = {}
example_id = '{}'.format(example_idx).encode()
feat['example_id'] = tf.train.Feature(
bytes_list=tf.train.BytesList(value=[example_id]))
event_time = 150000000 + example_idx
feat['event_time'] = tf.train.Feature(
int64_list=tf.train.Int64List(value=[event_time]))
feat[feat_key_fmt.format(example_idx)] = tf.train.Feature(
bytes_list=tf.train.BytesList(
value=[feat_val_fmt.format(example_idx).encode()]))
example = tf.train.Example(features=tf.train.Features(
feature=feat))
builder.append_record(example.SerializeToString(), example_id,
event_time, useless_index, useless_index)
useless_index += 1
meta = builder.finish_data_block()
fname = common.encode_data_block_fname(
data_source.data_source_meta.name, meta)
new_raw_data_fnames.append(os.path.join(raw_data_dir, fname))
fpaths = [
os.path.join(raw_data_dir, f)
for f in gfile.ListDirectory(raw_data_dir)
if not gfile.IsDirectory(os.path.join(raw_data_dir, f))
]
for fpath in fpaths:
if fpath.endswith(common.DataBlockMetaSuffix):
gfile.Remove(fpath)
rdp.publish_raw_data(partition_id, new_raw_data_fnames)