6e78fe3c8d
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
735 lines
21 KiB
Python
735 lines
21 KiB
Python
#!/usr/bin/env python3
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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
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import os
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import random
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import sys
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from block_cache_pysim import (
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ARCCache,
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CacheEntry,
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GDSizeCache,
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HashTable,
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HyperbolicPolicy,
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LFUPolicy,
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LinUCBCache,
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LRUCache,
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LRUPolicy,
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MRUPolicy,
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OPTCache,
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OPTCacheEntry,
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ThompsonSamplingCache,
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TraceCache,
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TraceRecord,
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create_cache,
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kMicrosInSecond,
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kSampleSize,
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run,
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)
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def test_hash_table():
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print("Test hash table")
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table = HashTable()
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data_size = 10000
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for i in range(data_size):
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table.insert("k{}".format(i), i, "v{}".format(i))
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for i in range(data_size):
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assert table.lookup("k{}".format(i), i) is not None
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for i in range(data_size):
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table.delete("k{}".format(i), i)
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for i in range(data_size):
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assert table.lookup("k{}".format(i), i) is None
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truth_map = {}
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n = 1000000
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records = 100
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for i in range(n):
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key_id = random.randint(0, records)
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v = random.randint(0, records)
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key = "k{}".format(key_id)
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value = CacheEntry(v, v, v, v, v, v, v)
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action = random.randint(0, 10)
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assert len(truth_map) == table.elements, "{} {} {}".format(
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len(truth_map), table.elements, i
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)
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if action <= 8:
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if key in truth_map:
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assert table.lookup(key, key_id) is not None
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assert truth_map[key].value_size == table.lookup(key, key_id).value_size
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else:
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assert table.lookup(key, key_id) is None
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table.insert(key, key_id, value)
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truth_map[key] = value
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else:
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deleted = table.delete(key, key_id)
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if deleted:
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assert key in truth_map
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if key in truth_map:
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del truth_map[key]
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# Check all keys are unique in the sample set.
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for _i in range(10):
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samples = table.random_sample(kSampleSize)
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unique_keys = {}
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for sample in samples:
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unique_keys[sample.key] = True
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assert len(samples) == len(unique_keys)
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assert len(table) == len(truth_map)
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for key in truth_map:
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assert table.lookup(key, int(key[1:])) is not None
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assert truth_map[key].value_size == table.lookup(key, int(key[1:])).value_size
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print("Test hash table: Success")
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def assert_metrics(cache, expected_value, expected_value_size=1, custom_hashtable=True):
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assert cache.used_size == expected_value[0], "Expected {}, Actual {}".format(
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expected_value[0], cache.used_size
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)
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assert (
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cache.miss_ratio_stats.num_accesses == expected_value[1]
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), "Expected {}, Actual {}".format(
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expected_value[1], cache.miss_ratio_stats.num_accesses
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)
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assert (
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cache.miss_ratio_stats.num_misses == expected_value[2]
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), "Expected {}, Actual {}".format(
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expected_value[2], cache.miss_ratio_stats.num_misses
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)
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assert len(cache.table) == len(expected_value[3]) + len(
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expected_value[4]
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), "Expected {}, Actual {}".format(
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len(expected_value[3]) + len(expected_value[4]), cache.table.elements
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)
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for expeceted_k in expected_value[3]:
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if custom_hashtable:
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val = cache.table.lookup("b{}".format(expeceted_k), expeceted_k)
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else:
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val = cache.table["b{}".format(expeceted_k)]
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assert val is not None, "Expected {} Actual: Not Exist {}, Table: {}".format(
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expeceted_k, expected_value, cache.table
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)
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assert val.value_size == expected_value_size
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for expeceted_k in expected_value[4]:
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if custom_hashtable:
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val = cache.table.lookup("g0-{}".format(expeceted_k), expeceted_k)
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else:
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val = cache.table["g0-{}".format(expeceted_k)]
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assert val is not None
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assert val.value_size == expected_value_size
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# Access k1, k1, k2, k3, k3, k3, k4
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# When k4 is inserted,
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# LRU should evict k1.
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# LFU should evict k2.
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# MRU should evict k3.
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def test_cache(cache, expected_value, custom_hashtable=True):
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k1 = TraceRecord(
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access_time=0,
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block_id=1,
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block_type=1,
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block_size=1,
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cf_id=0,
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cf_name="",
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level=0,
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fd=0,
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caller=1,
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no_insert=0,
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get_id=1,
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key_id=1,
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kv_size=5,
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is_hit=1,
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referenced_key_exist_in_block=1,
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num_keys_in_block=0,
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table_id=0,
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seq_number=0,
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block_key_size=0,
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key_size=0,
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block_offset_in_file=0,
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next_access_seq_no=0,
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)
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k2 = TraceRecord(
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access_time=1,
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block_id=2,
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block_type=1,
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block_size=1,
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cf_id=0,
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cf_name="",
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level=0,
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fd=0,
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caller=1,
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no_insert=0,
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get_id=1,
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key_id=1,
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kv_size=5,
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is_hit=1,
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referenced_key_exist_in_block=1,
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num_keys_in_block=0,
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table_id=0,
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seq_number=0,
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block_key_size=0,
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key_size=0,
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block_offset_in_file=0,
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next_access_seq_no=0,
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)
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k3 = TraceRecord(
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access_time=2,
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block_id=3,
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block_type=1,
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block_size=1,
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cf_id=0,
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cf_name="",
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level=0,
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fd=0,
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caller=1,
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no_insert=0,
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get_id=1,
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key_id=1,
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kv_size=5,
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is_hit=1,
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referenced_key_exist_in_block=1,
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num_keys_in_block=0,
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table_id=0,
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seq_number=0,
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block_key_size=0,
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key_size=0,
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block_offset_in_file=0,
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next_access_seq_no=0,
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)
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k4 = TraceRecord(
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access_time=3,
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block_id=4,
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block_type=1,
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block_size=1,
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cf_id=0,
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cf_name="",
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level=0,
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fd=0,
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caller=1,
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no_insert=0,
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get_id=1,
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key_id=1,
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kv_size=5,
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is_hit=1,
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referenced_key_exist_in_block=1,
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num_keys_in_block=0,
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table_id=0,
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seq_number=0,
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block_key_size=0,
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key_size=0,
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block_offset_in_file=0,
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next_access_seq_no=0,
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)
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sequence = [k1, k1, k2, k3, k3, k3]
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index = 0
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expected_values = []
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# Access k1, miss.
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expected_values.append([1, 1, 1, [1], []])
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# Access k1, hit.
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expected_values.append([1, 2, 1, [1], []])
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# Access k2, miss.
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expected_values.append([2, 3, 2, [1, 2], []])
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# Access k3, miss.
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expected_values.append([3, 4, 3, [1, 2, 3], []])
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# Access k3, hit.
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expected_values.append([3, 5, 3, [1, 2, 3], []])
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# Access k3, hit.
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expected_values.append([3, 6, 3, [1, 2, 3], []])
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access_time = 0
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for access in sequence:
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access.access_time = access_time
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cache.access(access)
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assert_metrics(
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cache,
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expected_values[index],
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expected_value_size=1,
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custom_hashtable=custom_hashtable,
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)
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access_time += 1
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index += 1
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k4.access_time = access_time
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cache.access(k4)
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assert_metrics(
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cache, expected_value, expected_value_size=1, custom_hashtable=custom_hashtable
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)
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def test_lru_cache(cache, custom_hashtable):
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print("Test LRU cache")
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# Access k4, miss. evict k1
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test_cache(cache, [3, 7, 4, [2, 3, 4], []], custom_hashtable)
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print("Test LRU cache: Success")
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def test_mru_cache():
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print("Test MRU cache")
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policies = []
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policies.append(MRUPolicy())
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# Access k4, miss. evict k3
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test_cache(
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ThompsonSamplingCache(3, False, policies, cost_class_label=None),
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[3, 7, 4, [1, 2, 4], []],
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)
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print("Test MRU cache: Success")
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def test_lfu_cache():
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print("Test LFU cache")
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policies = []
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policies.append(LFUPolicy())
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# Access k4, miss. evict k2
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test_cache(
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ThompsonSamplingCache(3, False, policies, cost_class_label=None),
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[3, 7, 4, [1, 3, 4], []],
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)
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print("Test LFU cache: Success")
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def test_mix(cache):
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print("Test Mix {} cache".format(cache.cache_name()))
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n = 100000
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records = 100
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block_size_table = {}
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trace_num_misses = 0
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for i in range(n):
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key_id = random.randint(0, records)
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vs = random.randint(0, 10)
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now = i * kMicrosInSecond
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block_size = vs
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if key_id in block_size_table:
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block_size = block_size_table[key_id]
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else:
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block_size_table[key_id] = block_size
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is_hit = key_id % 2
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if is_hit == 0:
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trace_num_misses += 1
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k = TraceRecord(
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access_time=now,
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block_id=key_id,
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block_type=1,
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block_size=block_size,
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cf_id=0,
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cf_name="",
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level=0,
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fd=0,
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caller=1,
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no_insert=0,
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get_id=key_id,
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key_id=key_id,
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kv_size=5,
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is_hit=is_hit,
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referenced_key_exist_in_block=1,
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num_keys_in_block=0,
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table_id=0,
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seq_number=0,
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block_key_size=0,
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key_size=0,
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block_offset_in_file=0,
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next_access_seq_no=vs,
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)
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cache.access(k)
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assert cache.miss_ratio_stats.miss_ratio() > 0
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if cache.cache_name() == "Trace":
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assert cache.miss_ratio_stats.num_accesses == n
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assert cache.miss_ratio_stats.num_misses == trace_num_misses
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else:
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assert cache.used_size <= cache.cache_size
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all_values = cache.table.values()
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cached_size = 0
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for value in all_values:
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cached_size += value.value_size
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assert cached_size == cache.used_size, "Expeced {} Actual {}".format(
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cache.used_size, cached_size
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)
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print("Test Mix {} cache: Success".format(cache.cache_name()))
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def test_end_to_end():
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print("Test All caches")
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n = 100000
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nblocks = 1000
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block_size = 16 * 1024
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ncfs = 7
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nlevels = 6
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nfds = 100000
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trace_file_path = "test_trace"
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# All blocks are of the same size so that OPT must achieve the lowest miss
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# ratio.
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with open(trace_file_path, "w+") as trace_file:
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access_records = ""
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for i in range(n):
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key_id = random.randint(0, nblocks)
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cf_id = random.randint(0, ncfs)
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level = random.randint(0, nlevels)
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fd = random.randint(0, nfds)
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now = i * kMicrosInSecond
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access_record = ""
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access_record += "{},".format(now)
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access_record += "{},".format(key_id)
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access_record += "{},".format(9) # block type
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access_record += "{},".format(block_size) # block size
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access_record += "{},".format(cf_id)
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access_record += "cf_{},".format(cf_id)
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access_record += "{},".format(level)
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access_record += "{},".format(fd)
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access_record += "{},".format(key_id % 3) # caller
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access_record += "{},".format(0) # no insert
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access_record += "{},".format(i) # get_id
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access_record += "{},".format(i) # key_id
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access_record += "{},".format(100) # kv_size
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access_record += "{},".format(1) # is_hit
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access_record += "{},".format(1) # referenced_key_exist_in_block
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access_record += "{},".format(10) # num_keys_in_block
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access_record += "{},".format(1) # table_id
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access_record += "{},".format(0) # seq_number
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access_record += "{},".format(10) # block key size
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access_record += "{},".format(20) # key size
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access_record += "{},".format(0) # block offset
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access_record = access_record[:-1]
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access_records += access_record + "\n"
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trace_file.write(access_records)
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print("Test All caches: Start testing caches")
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cache_size = block_size * nblocks / 10
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downsample_size = 1
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cache_ms = {}
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for cache_type in [
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"ts",
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"opt",
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"lru",
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"pylru",
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"linucb",
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"gdsize",
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"pyccbt",
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"pycctbbt",
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]:
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cache = create_cache(cache_type, cache_size, downsample_size)
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run(trace_file_path, cache_type, cache, 0, -1, "all")
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cache_ms[cache_type] = cache
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assert cache.miss_ratio_stats.num_accesses == n
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for cache_type in cache_ms:
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cache = cache_ms[cache_type]
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ms = cache.miss_ratio_stats.miss_ratio()
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assert ms <= 100.0 and ms >= 0.0
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# OPT should perform the best.
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assert cache_ms["opt"].miss_ratio_stats.miss_ratio() <= ms
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assert cache.used_size <= cache.cache_size
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all_values = cache.table.values()
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cached_size = 0
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for value in all_values:
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cached_size += value.value_size
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assert cached_size == cache.used_size, "Expeced {} Actual {}".format(
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cache.used_size, cached_size
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)
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print("Test All {}: Success".format(cache.cache_name()))
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os.remove(trace_file_path)
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print("Test All: Success")
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def test_hybrid(cache):
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print("Test {} cache".format(cache.cache_name()))
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k = TraceRecord(
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access_time=0,
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block_id=1,
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block_type=1,
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block_size=1,
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cf_id=0,
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cf_name="",
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level=0,
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fd=0,
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caller=1,
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no_insert=0,
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get_id=1, # the first get request.
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key_id=1,
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kv_size=0, # no size.
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is_hit=1,
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referenced_key_exist_in_block=1,
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num_keys_in_block=0,
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table_id=0,
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seq_number=0,
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block_key_size=0,
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key_size=0,
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block_offset_in_file=0,
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next_access_seq_no=0,
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)
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cache.access(k) # Expect a miss.
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# used size, num accesses, num misses, hash table size, blocks, get keys.
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assert_metrics(cache, [1, 1, 1, [1], []])
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k.access_time += 1
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k.kv_size = 1
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k.block_id = 2
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cache.access(k) # k should be inserted.
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assert_metrics(cache, [3, 2, 2, [1, 2], [1]])
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k.access_time += 1
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k.block_id = 3
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cache.access(k) # k should not be inserted again.
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assert_metrics(cache, [4, 3, 3, [1, 2, 3], [1]])
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# A second get request referencing the same key.
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k.access_time += 1
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k.get_id = 2
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k.block_id = 4
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k.kv_size = 0
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cache.access(k) # k should observe a hit. No block access.
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|
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()
|