rocksdb/tools/block_cache_analyzer/block_cache_pysim_test.py
haoyuhuang 6e78fe3c8d Pysim more algorithms (#5644)
Summary:
This PR adds four more eviction policies.
- OPT [1]
- Hyperbolic caching [2]
- ARC [3]
- GreedyDualSize [4]

[1] L. A. Belady. 1966. A Study of Replacement Algorithms for a Virtual-storage Computer. IBM Syst. J. 5, 2 (June 1966), 78-101. DOI=http://dx.doi.org/10.1147/sj.52.0078
[2] Aaron Blankstein, Siddhartha Sen, and Michael J. Freedman. 2017. Hyperbolic caching: flexible caching for web applications. In Proceedings of the 2017 USENIX Conference on Usenix Annual Technical Conference (USENIX ATC '17). USENIX Association, Berkeley, CA, USA, 499-511.
[3] Nimrod Megiddo and Dharmendra S. Modha. 2003. ARC: A Self-Tuning, Low Overhead Replacement Cache. In Proceedings of the 2nd USENIX Conference on File and Storage Technologies (FAST '03). USENIX Association, Berkeley, CA, USA, 115-130.
[4] N. Young. The k-server dual and loose competitiveness for paging. Algorithmica, June 1994, vol. 11,(no.6):525-41. Rewritten version of ''On-line caching as cache size varies'', in The 2nd Annual ACM-SIAM Symposium on Discrete Algorithms, 241-250, 1991.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5644

Differential Revision: D16548817

Pulled By: HaoyuHuang

fbshipit-source-id: 838f76db9179f07911abaab46c97e1c929cfcd63
2019-08-06 18:50:59 -07:00

735 lines
21 KiB
Python

#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import os
import random
import sys
from block_cache_pysim import (
ARCCache,
CacheEntry,
GDSizeCache,
HashTable,
HyperbolicPolicy,
LFUPolicy,
LinUCBCache,
LRUCache,
LRUPolicy,
MRUPolicy,
OPTCache,
OPTCacheEntry,
ThompsonSamplingCache,
TraceCache,
TraceRecord,
create_cache,
kMicrosInSecond,
kSampleSize,
run,
)
def test_hash_table():
print("Test hash table")
table = HashTable()
data_size = 10000
for i in range(data_size):
table.insert("k{}".format(i), i, "v{}".format(i))
for i in range(data_size):
assert table.lookup("k{}".format(i), i) is not None
for i in range(data_size):
table.delete("k{}".format(i), i)
for i in range(data_size):
assert table.lookup("k{}".format(i), i) is None
truth_map = {}
n = 1000000
records = 100
for i in range(n):
key_id = random.randint(0, records)
v = random.randint(0, records)
key = "k{}".format(key_id)
value = CacheEntry(v, v, v, v, v, v, v)
action = random.randint(0, 10)
assert len(truth_map) == table.elements, "{} {} {}".format(
len(truth_map), table.elements, i
)
if action <= 8:
if key in truth_map:
assert table.lookup(key, key_id) is not None
assert truth_map[key].value_size == table.lookup(key, key_id).value_size
else:
assert table.lookup(key, key_id) is None
table.insert(key, key_id, value)
truth_map[key] = value
else:
deleted = table.delete(key, key_id)
if deleted:
assert key in truth_map
if key in truth_map:
del truth_map[key]
# Check all keys are unique in the sample set.
for _i in range(10):
samples = table.random_sample(kSampleSize)
unique_keys = {}
for sample in samples:
unique_keys[sample.key] = True
assert len(samples) == len(unique_keys)
assert len(table) == len(truth_map)
for key in truth_map:
assert table.lookup(key, int(key[1:])) is not None
assert truth_map[key].value_size == table.lookup(key, int(key[1:])).value_size
print("Test hash table: Success")
def assert_metrics(cache, expected_value, expected_value_size=1, custom_hashtable=True):
assert cache.used_size == expected_value[0], "Expected {}, Actual {}".format(
expected_value[0], cache.used_size
)
assert (
cache.miss_ratio_stats.num_accesses == expected_value[1]
), "Expected {}, Actual {}".format(
expected_value[1], cache.miss_ratio_stats.num_accesses
)
assert (
cache.miss_ratio_stats.num_misses == expected_value[2]
), "Expected {}, Actual {}".format(
expected_value[2], cache.miss_ratio_stats.num_misses
)
assert len(cache.table) == len(expected_value[3]) + len(
expected_value[4]
), "Expected {}, Actual {}".format(
len(expected_value[3]) + len(expected_value[4]), cache.table.elements
)
for expeceted_k in expected_value[3]:
if custom_hashtable:
val = cache.table.lookup("b{}".format(expeceted_k), expeceted_k)
else:
val = cache.table["b{}".format(expeceted_k)]
assert val is not None, "Expected {} Actual: Not Exist {}, Table: {}".format(
expeceted_k, expected_value, cache.table
)
assert val.value_size == expected_value_size
for expeceted_k in expected_value[4]:
if custom_hashtable:
val = cache.table.lookup("g0-{}".format(expeceted_k), expeceted_k)
else:
val = cache.table["g0-{}".format(expeceted_k)]
assert val is not None
assert val.value_size == expected_value_size
# Access k1, k1, k2, k3, k3, k3, k4
# When k4 is inserted,
# LRU should evict k1.
# LFU should evict k2.
# MRU should evict k3.
def test_cache(cache, expected_value, custom_hashtable=True):
k1 = TraceRecord(
access_time=0,
block_id=1,
block_type=1,
block_size=1,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=1,
key_id=1,
kv_size=5,
is_hit=1,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=0,
)
k2 = TraceRecord(
access_time=1,
block_id=2,
block_type=1,
block_size=1,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=1,
key_id=1,
kv_size=5,
is_hit=1,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=0,
)
k3 = TraceRecord(
access_time=2,
block_id=3,
block_type=1,
block_size=1,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=1,
key_id=1,
kv_size=5,
is_hit=1,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=0,
)
k4 = TraceRecord(
access_time=3,
block_id=4,
block_type=1,
block_size=1,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=1,
key_id=1,
kv_size=5,
is_hit=1,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=0,
)
sequence = [k1, k1, k2, k3, k3, k3]
index = 0
expected_values = []
# Access k1, miss.
expected_values.append([1, 1, 1, [1], []])
# Access k1, hit.
expected_values.append([1, 2, 1, [1], []])
# Access k2, miss.
expected_values.append([2, 3, 2, [1, 2], []])
# Access k3, miss.
expected_values.append([3, 4, 3, [1, 2, 3], []])
# Access k3, hit.
expected_values.append([3, 5, 3, [1, 2, 3], []])
# Access k3, hit.
expected_values.append([3, 6, 3, [1, 2, 3], []])
access_time = 0
for access in sequence:
access.access_time = access_time
cache.access(access)
assert_metrics(
cache,
expected_values[index],
expected_value_size=1,
custom_hashtable=custom_hashtable,
)
access_time += 1
index += 1
k4.access_time = access_time
cache.access(k4)
assert_metrics(
cache, expected_value, expected_value_size=1, custom_hashtable=custom_hashtable
)
def test_lru_cache(cache, custom_hashtable):
print("Test LRU cache")
# Access k4, miss. evict k1
test_cache(cache, [3, 7, 4, [2, 3, 4], []], custom_hashtable)
print("Test LRU cache: Success")
def test_mru_cache():
print("Test MRU cache")
policies = []
policies.append(MRUPolicy())
# Access k4, miss. evict k3
test_cache(
ThompsonSamplingCache(3, False, policies, cost_class_label=None),
[3, 7, 4, [1, 2, 4], []],
)
print("Test MRU cache: Success")
def test_lfu_cache():
print("Test LFU cache")
policies = []
policies.append(LFUPolicy())
# Access k4, miss. evict k2
test_cache(
ThompsonSamplingCache(3, False, policies, cost_class_label=None),
[3, 7, 4, [1, 3, 4], []],
)
print("Test LFU cache: Success")
def test_mix(cache):
print("Test Mix {} cache".format(cache.cache_name()))
n = 100000
records = 100
block_size_table = {}
trace_num_misses = 0
for i in range(n):
key_id = random.randint(0, records)
vs = random.randint(0, 10)
now = i * kMicrosInSecond
block_size = vs
if key_id in block_size_table:
block_size = block_size_table[key_id]
else:
block_size_table[key_id] = block_size
is_hit = key_id % 2
if is_hit == 0:
trace_num_misses += 1
k = TraceRecord(
access_time=now,
block_id=key_id,
block_type=1,
block_size=block_size,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=key_id,
key_id=key_id,
kv_size=5,
is_hit=is_hit,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=vs,
)
cache.access(k)
assert cache.miss_ratio_stats.miss_ratio() > 0
if cache.cache_name() == "Trace":
assert cache.miss_ratio_stats.num_accesses == n
assert cache.miss_ratio_stats.num_misses == trace_num_misses
else:
assert cache.used_size <= cache.cache_size
all_values = cache.table.values()
cached_size = 0
for value in all_values:
cached_size += value.value_size
assert cached_size == cache.used_size, "Expeced {} Actual {}".format(
cache.used_size, cached_size
)
print("Test Mix {} cache: Success".format(cache.cache_name()))
def test_end_to_end():
print("Test All caches")
n = 100000
nblocks = 1000
block_size = 16 * 1024
ncfs = 7
nlevels = 6
nfds = 100000
trace_file_path = "test_trace"
# All blocks are of the same size so that OPT must achieve the lowest miss
# ratio.
with open(trace_file_path, "w+") as trace_file:
access_records = ""
for i in range(n):
key_id = random.randint(0, nblocks)
cf_id = random.randint(0, ncfs)
level = random.randint(0, nlevels)
fd = random.randint(0, nfds)
now = i * kMicrosInSecond
access_record = ""
access_record += "{},".format(now)
access_record += "{},".format(key_id)
access_record += "{},".format(9) # block type
access_record += "{},".format(block_size) # block size
access_record += "{},".format(cf_id)
access_record += "cf_{},".format(cf_id)
access_record += "{},".format(level)
access_record += "{},".format(fd)
access_record += "{},".format(key_id % 3) # caller
access_record += "{},".format(0) # no insert
access_record += "{},".format(i) # get_id
access_record += "{},".format(i) # key_id
access_record += "{},".format(100) # kv_size
access_record += "{},".format(1) # is_hit
access_record += "{},".format(1) # referenced_key_exist_in_block
access_record += "{},".format(10) # num_keys_in_block
access_record += "{},".format(1) # table_id
access_record += "{},".format(0) # seq_number
access_record += "{},".format(10) # block key size
access_record += "{},".format(20) # key size
access_record += "{},".format(0) # block offset
access_record = access_record[:-1]
access_records += access_record + "\n"
trace_file.write(access_records)
print("Test All caches: Start testing caches")
cache_size = block_size * nblocks / 10
downsample_size = 1
cache_ms = {}
for cache_type in [
"ts",
"opt",
"lru",
"pylru",
"linucb",
"gdsize",
"pyccbt",
"pycctbbt",
]:
cache = create_cache(cache_type, cache_size, downsample_size)
run(trace_file_path, cache_type, cache, 0, -1, "all")
cache_ms[cache_type] = cache
assert cache.miss_ratio_stats.num_accesses == n
for cache_type in cache_ms:
cache = cache_ms[cache_type]
ms = cache.miss_ratio_stats.miss_ratio()
assert ms <= 100.0 and ms >= 0.0
# OPT should perform the best.
assert cache_ms["opt"].miss_ratio_stats.miss_ratio() <= ms
assert cache.used_size <= cache.cache_size
all_values = cache.table.values()
cached_size = 0
for value in all_values:
cached_size += value.value_size
assert cached_size == cache.used_size, "Expeced {} Actual {}".format(
cache.used_size, cached_size
)
print("Test All {}: Success".format(cache.cache_name()))
os.remove(trace_file_path)
print("Test All: Success")
def test_hybrid(cache):
print("Test {} cache".format(cache.cache_name()))
k = TraceRecord(
access_time=0,
block_id=1,
block_type=1,
block_size=1,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=1, # the first get request.
key_id=1,
kv_size=0, # no size.
is_hit=1,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=0,
)
cache.access(k) # Expect a miss.
# used size, num accesses, num misses, hash table size, blocks, get keys.
assert_metrics(cache, [1, 1, 1, [1], []])
k.access_time += 1
k.kv_size = 1
k.block_id = 2
cache.access(k) # k should be inserted.
assert_metrics(cache, [3, 2, 2, [1, 2], [1]])
k.access_time += 1
k.block_id = 3
cache.access(k) # k should not be inserted again.
assert_metrics(cache, [4, 3, 3, [1, 2, 3], [1]])
# A second get request referencing the same key.
k.access_time += 1
k.get_id = 2
k.block_id = 4
k.kv_size = 0
cache.access(k) # k should observe a hit. No block access.
assert_metrics(cache, [4, 4, 3, [1, 2, 3], [1]])
# A third get request searches three files, three different keys.
# And the second key observes a hit.
k.access_time += 1
k.kv_size = 1
k.get_id = 3
k.block_id = 3
k.key_id = 2
cache.access(k) # k should observe a miss. block 3 observes a hit.
assert_metrics(cache, [5, 5, 3, [1, 2, 3], [1, 2]])
k.access_time += 1
k.kv_size = 1
k.get_id = 3
k.block_id = 4
k.kv_size = 1
k.key_id = 1
cache.access(k) # k1 should observe a hit.
assert_metrics(cache, [5, 6, 3, [1, 2, 3], [1, 2]])
k.access_time += 1
k.kv_size = 1
k.get_id = 3
k.block_id = 4
k.kv_size = 1
k.key_id = 3
# k3 should observe a miss.
# However, as the get already complete, we should not access k3 any more.
cache.access(k)
assert_metrics(cache, [5, 7, 3, [1, 2, 3], [1, 2]])
# A fourth get request searches one file and two blocks. One row key.
k.access_time += 1
k.get_id = 4
k.block_id = 5
k.key_id = 4
k.kv_size = 1
cache.access(k)
assert_metrics(cache, [7, 8, 4, [1, 2, 3, 5], [1, 2, 4]])
# A bunch of insertions which evict cached row keys.
for i in range(6, 100):
k.access_time += 1
k.get_id = 0
k.block_id = i
cache.access(k)
k.get_id = 4
k.block_id = 100 # A different block.
k.key_id = 4 # Same row key and should not be inserted again.
k.kv_size = 1
cache.access(k)
assert_metrics(
cache, [kSampleSize, 103, 99, [i for i in range(101 - kSampleSize, 101)], []]
)
print("Test {} cache: Success".format(cache.cache_name()))
def test_opt_cache():
print("Test OPT cache")
cache = OPTCache(3)
# seq: 0, 1, 2, 3, 4, 5, 6, 7, 8
# key: k1, k2, k3, k4, k5, k6, k7, k1, k8
# next_access: 7, 19, 18, M, M, 17, 16, 25, M
k = TraceRecord(
access_time=0,
block_id=1,
block_type=1,
block_size=1,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=1, # the first get request.
key_id=1,
kv_size=0, # no size.
is_hit=1,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=7,
)
cache.access(k)
assert_metrics(
cache, [1, 1, 1, [1], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 2
k.next_access_seq_no = 19
cache.access(k)
assert_metrics(
cache, [2, 2, 2, [1, 2], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 3
k.next_access_seq_no = 18
cache.access(k)
assert_metrics(
cache, [3, 3, 3, [1, 2, 3], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 4
k.next_access_seq_no = sys.maxsize # Never accessed again.
cache.access(k)
# Evict 2 since its next access 19 is the furthest in the future.
assert_metrics(
cache, [3, 4, 4, [1, 3, 4], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 5
k.next_access_seq_no = sys.maxsize # Never accessed again.
cache.access(k)
# Evict 4 since its next access MAXINT is the furthest in the future.
assert_metrics(
cache, [3, 5, 5, [1, 3, 5], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 6
k.next_access_seq_no = 17
cache.access(k)
# Evict 5 since its next access MAXINT is the furthest in the future.
assert_metrics(
cache, [3, 6, 6, [1, 3, 6], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 7
k.next_access_seq_no = 16
cache.access(k)
# Evict 3 since its next access 18 is the furthest in the future.
assert_metrics(
cache, [3, 7, 7, [1, 6, 7], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 1
k.next_access_seq_no = 25
cache.access(k)
assert_metrics(
cache, [3, 8, 7, [1, 6, 7], []], expected_value_size=1, custom_hashtable=False
)
k.access_time += 1
k.block_id = 8
k.next_access_seq_no = sys.maxsize
cache.access(k)
# Evict 1 since its next access 25 is the furthest in the future.
assert_metrics(
cache, [3, 9, 8, [6, 7, 8], []], expected_value_size=1, custom_hashtable=False
)
# Insert a large kv pair to evict all keys.
k.access_time += 1
k.block_id = 10
k.block_size = 3
k.next_access_seq_no = sys.maxsize
cache.access(k)
assert_metrics(
cache, [3, 10, 9, [10], []], expected_value_size=3, custom_hashtable=False
)
print("Test OPT cache: Success")
def test_trace_cache():
print("Test trace cache")
cache = TraceCache(0)
k = TraceRecord(
access_time=0,
block_id=1,
block_type=1,
block_size=1,
cf_id=0,
cf_name="",
level=0,
fd=0,
caller=1,
no_insert=0,
get_id=1,
key_id=1,
kv_size=0,
is_hit=1,
referenced_key_exist_in_block=1,
num_keys_in_block=0,
table_id=0,
seq_number=0,
block_key_size=0,
key_size=0,
block_offset_in_file=0,
next_access_seq_no=7,
)
cache.access(k)
assert cache.miss_ratio_stats.num_accesses == 1
assert cache.miss_ratio_stats.num_misses == 0
k.is_hit = 0
cache.access(k)
assert cache.miss_ratio_stats.num_accesses == 2
assert cache.miss_ratio_stats.num_misses == 1
print("Test trace cache: Success")
if __name__ == "__main__":
test_hash_table()
test_trace_cache()
test_opt_cache()
test_lru_cache(
ThompsonSamplingCache(
3, enable_cache_row_key=0, policies=[LRUPolicy()], cost_class_label=None
),
custom_hashtable=True,
)
test_lru_cache(LRUCache(3, enable_cache_row_key=0), custom_hashtable=False)
test_mru_cache()
test_lfu_cache()
test_hybrid(
ThompsonSamplingCache(
kSampleSize,
enable_cache_row_key=1,
policies=[LRUPolicy()],
cost_class_label=None,
)
)
test_hybrid(
LinUCBCache(
kSampleSize,
enable_cache_row_key=1,
policies=[LRUPolicy()],
cost_class_label=None,
)
)
for cache_type in [
"ts",
"opt",
"arc",
"pylfu",
"pymru",
"trace",
"pyhb",
"lru",
"pylru",
"linucb",
"gdsize",
"pycctbbt",
"pycctb",
"pyccbt",
]:
for enable_row_cache in [0, 1, 2]:
cache_type_str = cache_type
if cache_type != "opt" and cache_type != "trace":
if enable_row_cache == 1:
cache_type_str += "_hybrid"
elif enable_row_cache == 2:
cache_type_str += "_hybridn"
test_mix(create_cache(cache_type_str, cache_size=100, downsample_size=1))
test_end_to_end()