def ht_zipf():
address = "frog.zoo.cs.yale.edu"
service_port = 9090
lease_port = 9091
num_blocks = 1
chain_length = 1
num_ops = 100000
data_size = 64
op_type_set = []
op_type_set.append("get")
path = "/tmp"
backing_path = "local://tmp"
file_name = './ht_zipf_with_cache.txt'
data = open(file_name, 'w+')
# Output all the configuration parameters:
print >> data, "host: ", address
print >> data, "service-port: ", service_port
print >> data, "lease-port: ", lease_port
print >> data, "num-blocks: ", num_blocks
print >> data, "chain-length: ", chain_length
print >> data, "num-ops: ", num_ops
print >> data, "data-size: ", data_size
print >> data, "path: ", path
print >> data, "backing-path: ", backing_path
num_clients = 1
loading = 0
client = JiffyClient(address, service_port, lease_port)
ht_clients = [None] * num_clients
for cache_size in range(num_ops // 20 * 64, num_ops * 64 + 1,
num_ops // 20 * 64):
ht_clients[0] = client.open_or_create_hash_table(
path, backing_path, num_blocks, chain_length, cache_size)
benchmark = GetBenchmark(ht_clients, data_size, num_clients, num_ops)
benchmark.run()
result = benchmark.wait()
client.remove(path)
print >> data, "===== ", "Zipf_ht_Benchmark, ", "Cache_Size= ", cache_size, " ======"
print >> data, "\t", num_ops, " requests completed in ", (
float(num_ops) / result[0]), " s"
print >> data, "\t", num_clients, " parallel clients"
print >> data, "\t", data_size, " payload"
print >> data, "\tAverage put latency: ", result[1], "us"
print >> data, "\tAverage get latency: ", result[2], "us"
print >> data, "\tAverage total latency: ", result[1] + result[2], "us"
print >> data, "\tThroughput: ", result[0], " requests per second"
print >> data, "\tHit_rate: ", round(result[3], 4), "%"
print >> data, "\n"
loading += 1
print("Loading -- ", round(float(loading * 100 / 20), 1), "%")
return 0
def run_scale_workload(d_host='127.0.0.1', d_port=9090, l_port=9091, data_path='/data/test', n_ops=100000,
value_size=102400, skew=0.0):
value = bytes(value_size)
keys = zipf_keys(skew, 512, n_ops)
client = JiffyClient(d_host, d_port, l_port)
kv = client.open_or_create(data_path, '/tmp')
logging.info("Generated {} keys".format(len(keys)))
for key in keys:
kv.put(key, value)
for key in keys:
kv.remove(key)
client.remove(data_path, RemoveMode.delete)
def file_cp():
address = "frog.zoo.cs.yale.edu"
service_port = 9090
lease_port = 9091
num_blocks = 1
chain_length = 1
num_ops = 100000
data_size = 64
op_type_set = []
op_type_set.append("write")
op_type_set.append("read")
path = "/tmp"
backing_path = "local://tmp"
# Output all the configuration parameters:
file_name = './file_cp.txt'
data = open(file_name, 'w+')
print >> data, "host: ", address
print >> data, "service-port: ", service_port
print >> data, "lease-port: ", lease_port
print >> data, "num-blocks: ", num_blocks
print >> data, "chain-length: ", chain_length
print >> data, "num-ops: ", num_ops
print >> data, "data-size: ", data_size
print >> data, "path: ", path
print >> data, "backing-path: ", backing_path
for op_type in op_type_set:
count = 1
while count <= 1:
loading = 0
num_clients = count
cache_block_size = 2000
client = JiffyClient(address, service_port, lease_port)
ht_clients = [None] * num_clients
for cache_size in range(100, 2101, 200):
for prefetch_size in range(5, 51, 5):
for i in range(num_clients):
ht_clients[i] = client.open_or_create_file(
path, backing_path, num_blocks, chain_length,
cache_size, cache_block_size, prefetch_size)
if (op_type == "write"):
benchmark = WriteBenchmark(ht_clients, data_size,
num_clients, num_ops)
if (op_type == "read"):
benchmark = ReadBenchmark(ht_clients, data_size,
num_clients, num_ops)
else:
print >> data, "Incorrect operation type for file: ", op_type
return 0
benchmark.run()
result = benchmark.wait()
client.remove(path)
print >> data, "===== ", "Cache_Size= ", cache_size, "Prefetch Size= ", prefetch_size, " ======"
print >> data, "\t", num_ops, " requests completed in ", (
float(num_ops) / result[0]), " s"
print >> data, "\t", num_clients, " parallel clients"
print >> data, "\t", data_size, " payload"
print >> data, "\tAverage write latency: ", result[1], "us"
print >> data, "\tAverage read latency: ", result[2], "us"
print >> data, "\tAverage total latency: ", result[
1] + result[2], "us"
print >> data, "\tThroughput: ", result[
0], " bytes per second"
print >> data, "\tHit_rate: ", round(result[3], 4), "%"
print >> data, "\n"
loading += 1
print("Loading -- ", round(float(loading * 100 / 110), 1),
"%")
count *= 2
data.close()
return 0