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// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
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// This source code is licensed under both the GPLv2 (found in the
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// COPYING file in the root directory) and Apache 2.0 License
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// (found in the LICENSE.Apache file in the root directory).
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//
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// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file. See the AUTHORS file for names of contributors.
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#include "cache/fast_lru_cache.h"
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#include <cassert>
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#include <cstdint>
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#include <cstdio>
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#include <functional>
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#include "monitoring/perf_context_imp.h"
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#include "monitoring/statistics.h"
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#include "port/lang.h"
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#include "util/distributed_mutex.h"
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#include "util/hash.h"
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#include "util/math.h"
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#include "util/random.h"
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namespace ROCKSDB_NAMESPACE {
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namespace fast_lru_cache {
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LRUHandleTable::LRUHandleTable(int hash_bits)
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: length_bits_(hash_bits),
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length_bits_mask_((uint32_t{1} << length_bits_) - 1),
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occupancy_(0),
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occupancy_limit_(static_cast<uint32_t>((uint32_t{1} << length_bits_) *
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kStrictLoadFactor)),
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array_(new LRUHandle[size_t{1} << length_bits_]) {
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assert(hash_bits <= 32);
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}
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LRUHandleTable::~LRUHandleTable() {
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ApplyToEntriesRange([](LRUHandle* h) { h->FreeData(); }, 0, GetTableSize());
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}
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LRUHandle* LRUHandleTable::Lookup(const Slice& key, uint32_t hash) {
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int probe = 0;
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int slot = FindVisibleElement(key, hash, probe, 0);
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return (slot == -1) ? nullptr : &array_[slot];
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}
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LRUHandle* LRUHandleTable::Insert(LRUHandle* h, LRUHandle** old) {
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int probe = 0;
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int slot = FindVisibleElementOrAvailableSlot(h->key(), h->hash, probe,
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1 /*displacement*/);
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*old = nullptr;
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if (slot == -1) {
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// TODO(Guido) Don't we need to roll back displacements here?
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return nullptr;
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}
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if (array_[slot].IsEmpty() || array_[slot].IsTombstone()) {
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bool empty = array_[slot].IsEmpty();
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Assign(slot, h);
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LRUHandle* new_entry = &array_[slot];
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if (empty) {
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// This used to be an empty slot.
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return new_entry;
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}
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// It used to be a tombstone, so there may already be a copy of the
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// key in the table.
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slot = FindVisibleElement(h->key(), h->hash, probe, 0 /*displacement*/);
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if (slot == -1) {
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// No existing copy of the key.
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return new_entry;
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}
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*old = &array_[slot];
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return new_entry;
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} else {
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// There is an existing copy of the key.
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*old = &array_[slot];
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// Find an available slot for the new element.
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array_[slot].displacements++;
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slot = FindAvailableSlot(h->key(), probe, 1 /*displacement*/);
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if (slot == -1) {
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// No available slots. Roll back displacements.
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probe = 0;
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slot = FindVisibleElement(h->key(), h->hash, probe, -1);
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array_[slot].displacements--;
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FindAvailableSlot(h->key(), probe, -1);
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return nullptr;
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}
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Assign(slot, h);
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return &array_[slot];
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}
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}
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void LRUHandleTable::Remove(LRUHandle* h) {
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assert(h->next == nullptr &&
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h->prev == nullptr); // Already off the LRU list.
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int probe = 0;
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FindSlot(
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h->key(), [&h](LRUHandle* e) { return e == h; }, probe,
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-1 /*displacement*/);
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h->SetIsVisible(false);
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h->SetIsElement(false);
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occupancy_--;
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}
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void LRUHandleTable::Assign(int slot, LRUHandle* h) {
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LRUHandle* dst = &array_[slot];
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uint32_t disp = dst->displacements;
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*dst = *h;
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dst->displacements = disp;
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dst->SetIsVisible(true);
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dst->SetIsElement(true);
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occupancy_++;
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}
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void LRUHandleTable::Exclude(LRUHandle* h) { h->SetIsVisible(false); }
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int LRUHandleTable::FindVisibleElement(const Slice& key, uint32_t hash,
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int& probe, int displacement) {
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return FindSlot(
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key,
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[&](LRUHandle* h) { return h->Matches(key, hash) && h->IsVisible(); },
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probe, displacement);
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}
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int LRUHandleTable::FindAvailableSlot(const Slice& key, int& probe,
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int displacement) {
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return FindSlot(
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key, [](LRUHandle* h) { return h->IsEmpty() || h->IsTombstone(); }, probe,
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displacement);
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}
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int LRUHandleTable::FindVisibleElementOrAvailableSlot(const Slice& key,
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uint32_t hash, int& probe,
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int displacement) {
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return FindSlot(
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key,
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[&](LRUHandle* h) {
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return h->IsEmpty() || h->IsTombstone() ||
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(h->Matches(key, hash) && h->IsVisible());
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},
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probe, displacement);
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}
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inline int LRUHandleTable::FindSlot(const Slice& key,
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std::function<bool(LRUHandle*)> cond,
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int& probe, int displacement) {
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uint32_t base = ModTableSize(Hash(key.data(), key.size(), kProbingSeed1));
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uint32_t increment =
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ModTableSize((Hash(key.data(), key.size(), kProbingSeed2) << 1) | 1);
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uint32_t current = ModTableSize(base + probe * increment);
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while (true) {
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LRUHandle* h = &array_[current];
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probe++;
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if (current == base && probe > 1) {
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// We looped back.
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return -1;
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}
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if (cond(h)) {
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return current;
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}
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if (h->IsEmpty()) {
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// We check emptyness after the condition, because
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// the condition may be emptyness.
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return -1;
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}
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h->displacements += displacement;
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current = ModTableSize(current + increment);
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}
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}
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LRUCacheShard::LRUCacheShard(size_t capacity, size_t estimated_value_size,
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bool strict_capacity_limit,
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CacheMetadataChargePolicy metadata_charge_policy)
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: CacheShardBase(metadata_charge_policy),
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Revamp, optimize new experimental clock cache (#10626)
Summary:
* Consolidates most metadata into a single word per slot so that more
can be accomplished with a single atomic update. In the common case,
Lookup was previously about 4 atomic updates, now just 1 atomic update.
Common case Release was previously 1 atomic read + 1 atomic update,
now just 1 atomic update.
* Eliminate spins / waits / yields, which likely threaten some "lock free"
benefits. Compare-exchange loops are only used in explicit Erase, and
strict_capacity_limit=true Insert. Eviction uses opportunistic compare-
exchange.
* Relaxes some aggressiveness and guarantees. For example,
* Duplicate Inserts will sometimes go undetected and the shadow duplicate
will age out with eviction.
* In many cases, the older Inserted value for a given cache key will be kept
(i.e. Insert does not support overwrite).
* Entries explicitly erased (rather than evicted) might not be freed
immediately in some rare cases.
* With strict_capacity_limit=false, capacity limit is not tracked/enforced as
precisely as LRUCache, but is self-correcting and should only deviate by a
very small number of extra or fewer entries.
* Use smaller "computed default" number of cache shards in many cases,
because benefits to larger usage tracking / eviction pools outweigh the small
cost of more lock-free atomic contention. The improvement in CPU and I/O
is dramatic in some limit-memory cases.
* Even without the sharding change, the eviction algorithm is likely more
effective than LRU overall because it's more stateful, even though the
"hot path" state tracking for it is essentially free with ref counting. It
is like a generalized CLOCK with aging (see code comments). I don't have
performance numbers showing a specific improvement, but in theory, for a
Poisson access pattern to each block, keeping some state allows better
estimation of time to next access (Poisson interval) than strict LRU. The
bounded randomness in CLOCK can also reduce "cliff" effect for repeated
range scans approaching and exceeding cache size.
## Hot path algorithm comparison
Rough descriptions, focusing on number and kind of atomic operations:
* Old `Lookup()` (2-5 atomic updates per probe):
```
Loop:
Increment internal ref count at slot
If possible hit:
Check flags atomic (and non-atomic fields)
If cache hit:
Three distinct updates to 'flags' atomic
Increment refs for internal-to-external
Return
Decrement internal ref count
while atomic read 'displacements' > 0
```
* New `Lookup()` (1-2 atomic updates per probe):
```
Loop:
Increment acquire counter in meta word (optimistic)
If visible entry (already read meta word):
If match (read non-atomic fields):
Return
Else:
Decrement acquire counter in meta word
Else if invisible entry (rare, already read meta word):
Decrement acquire counter in meta word
while atomic read 'displacements' > 0
```
* Old `Release()` (1 atomic update, conditional on atomic read, rarely more):
```
Read atomic ref count
If last reference and invisible (rare):
Use CAS etc. to remove
Return
Else:
Decrement ref count
```
* New `Release()` (1 unconditional atomic update, rarely more):
```
Increment release counter in meta word
If last reference and invisible (rare):
Use CAS etc. to remove
Return
```
## Performance test setup
Build DB with
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16
```
Test with
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=readrandom -readonly -num=30000000 -bloom_bits=16 -cache_index_and_filter_blocks=1 -cache_size=${CACHE_MB}000000 -duration 60 -threads=$THREADS -statistics
```
Numbers on a single socket Skylake Xeon system with 48 hardware threads, DEBUG_LEVEL=0 PORTABLE=0. Very similar story on a dual socket system with 80 hardware threads. Using (every 2nd) Fibonacci MB cache sizes to sample the territory between powers of two. Configurations:
base: LRUCache before this change, but with db_bench change to default cache_numshardbits=-1 (instead of fixed at 6)
folly: LRUCache before this change, with folly enabled (distributed mutex) but on an old compiler (sorry)
gt_clock: experimental ClockCache before this change
new_clock: experimental ClockCache with this change
## Performance test results
First test "hot path" read performance, with block cache large enough for whole DB:
4181MB 1thread base -> kops/s: 47.761
4181MB 1thread folly -> kops/s: 45.877
4181MB 1thread gt_clock -> kops/s: 51.092
4181MB 1thread new_clock -> kops/s: 53.944
4181MB 16thread base -> kops/s: 284.567
4181MB 16thread folly -> kops/s: 249.015
4181MB 16thread gt_clock -> kops/s: 743.762
4181MB 16thread new_clock -> kops/s: 861.821
4181MB 24thread base -> kops/s: 303.415
4181MB 24thread folly -> kops/s: 266.548
4181MB 24thread gt_clock -> kops/s: 975.706
4181MB 24thread new_clock -> kops/s: 1205.64 (~= 24 * 53.944)
4181MB 32thread base -> kops/s: 311.251
4181MB 32thread folly -> kops/s: 274.952
4181MB 32thread gt_clock -> kops/s: 1045.98
4181MB 32thread new_clock -> kops/s: 1370.38
4181MB 48thread base -> kops/s: 310.504
4181MB 48thread folly -> kops/s: 268.322
4181MB 48thread gt_clock -> kops/s: 1195.65
4181MB 48thread new_clock -> kops/s: 1604.85 (~= 24 * 1.25 * 53.944)
4181MB 64thread base -> kops/s: 307.839
4181MB 64thread folly -> kops/s: 272.172
4181MB 64thread gt_clock -> kops/s: 1204.47
4181MB 64thread new_clock -> kops/s: 1615.37
4181MB 128thread base -> kops/s: 310.934
4181MB 128thread folly -> kops/s: 267.468
4181MB 128thread gt_clock -> kops/s: 1188.75
4181MB 128thread new_clock -> kops/s: 1595.46
Whether we have just one thread on a quiet system or an overload of threads, the new version wins every time in thousand-ops per second, sometimes dramatically so. Mutex-based implementation quickly becomes contention-limited. New clock cache shows essentially perfect scaling up to number of physical cores (24), and then each hyperthreaded core adding about 1/4 the throughput of an additional physical core (see 48 thread case). Block cache miss rates (omitted above) are negligible across the board. With partitioned instead of full filters, the maximum speed-up vs. base is more like 2.5x rather than 5x.
Now test a large block cache with low miss ratio, but some eviction is required:
1597MB 1thread base -> kops/s: 46.603 io_bytes/op: 1584.63 miss_ratio: 0.0201066 max_rss_mb: 1589.23
1597MB 1thread folly -> kops/s: 45.079 io_bytes/op: 1530.03 miss_ratio: 0.019872 max_rss_mb: 1550.43
1597MB 1thread gt_clock -> kops/s: 48.711 io_bytes/op: 1566.63 miss_ratio: 0.0198923 max_rss_mb: 1691.4
1597MB 1thread new_clock -> kops/s: 51.531 io_bytes/op: 1589.07 miss_ratio: 0.0201969 max_rss_mb: 1583.56
1597MB 32thread base -> kops/s: 301.174 io_bytes/op: 1439.52 miss_ratio: 0.0184218 max_rss_mb: 1656.59
1597MB 32thread folly -> kops/s: 273.09 io_bytes/op: 1375.12 miss_ratio: 0.0180002 max_rss_mb: 1586.8
1597MB 32thread gt_clock -> kops/s: 904.497 io_bytes/op: 1411.29 miss_ratio: 0.0179934 max_rss_mb: 1775.89
1597MB 32thread new_clock -> kops/s: 1182.59 io_bytes/op: 1440.77 miss_ratio: 0.0185449 max_rss_mb: 1636.45
1597MB 128thread base -> kops/s: 309.91 io_bytes/op: 1438.25 miss_ratio: 0.018399 max_rss_mb: 1689.98
1597MB 128thread folly -> kops/s: 267.605 io_bytes/op: 1394.16 miss_ratio: 0.0180286 max_rss_mb: 1631.91
1597MB 128thread gt_clock -> kops/s: 691.518 io_bytes/op: 9056.73 miss_ratio: 0.0186572 max_rss_mb: 1982.26
1597MB 128thread new_clock -> kops/s: 1406.12 io_bytes/op: 1440.82 miss_ratio: 0.0185463 max_rss_mb: 1685.63
610MB 1thread base -> kops/s: 45.511 io_bytes/op: 2279.61 miss_ratio: 0.0290528 max_rss_mb: 615.137
610MB 1thread folly -> kops/s: 43.386 io_bytes/op: 2217.29 miss_ratio: 0.0289282 max_rss_mb: 600.996
610MB 1thread gt_clock -> kops/s: 46.207 io_bytes/op: 2275.51 miss_ratio: 0.0290057 max_rss_mb: 637.934
610MB 1thread new_clock -> kops/s: 48.879 io_bytes/op: 2283.1 miss_ratio: 0.0291253 max_rss_mb: 613.5
610MB 32thread base -> kops/s: 306.59 io_bytes/op: 2250 miss_ratio: 0.0288721 max_rss_mb: 683.402
610MB 32thread folly -> kops/s: 269.176 io_bytes/op: 2187.86 miss_ratio: 0.0286938 max_rss_mb: 628.742
610MB 32thread gt_clock -> kops/s: 855.097 io_bytes/op: 2279.26 miss_ratio: 0.0288009 max_rss_mb: 733.062
610MB 32thread new_clock -> kops/s: 1121.47 io_bytes/op: 2244.29 miss_ratio: 0.0289046 max_rss_mb: 666.453
610MB 128thread base -> kops/s: 305.079 io_bytes/op: 2252.43 miss_ratio: 0.0288884 max_rss_mb: 723.457
610MB 128thread folly -> kops/s: 269.583 io_bytes/op: 2204.58 miss_ratio: 0.0287001 max_rss_mb: 676.426
610MB 128thread gt_clock -> kops/s: 53.298 io_bytes/op: 8128.98 miss_ratio: 0.0292452 max_rss_mb: 956.273
610MB 128thread new_clock -> kops/s: 1301.09 io_bytes/op: 2246.04 miss_ratio: 0.0289171 max_rss_mb: 788.812
The new version is still winning every time, sometimes dramatically so, and we can tell from the maximum resident memory numbers (which contain some noise, by the way) that the new cache is not cheating on memory usage. IMPORTANT: The previous generation experimental clock cache appears to hit a serious bottleneck in the higher thread count configurations, presumably due to some of its waiting functionality. (The same bottleneck is not seen with partitioned index+filters.)
Now we consider even smaller cache sizes, with higher miss ratios, eviction work, etc.
233MB 1thread base -> kops/s: 10.557 io_bytes/op: 227040 miss_ratio: 0.0403105 max_rss_mb: 247.371
233MB 1thread folly -> kops/s: 15.348 io_bytes/op: 112007 miss_ratio: 0.0372238 max_rss_mb: 245.293
233MB 1thread gt_clock -> kops/s: 6.365 io_bytes/op: 244854 miss_ratio: 0.0413873 max_rss_mb: 259.844
233MB 1thread new_clock -> kops/s: 47.501 io_bytes/op: 2591.93 miss_ratio: 0.0330989 max_rss_mb: 242.461
233MB 32thread base -> kops/s: 96.498 io_bytes/op: 363379 miss_ratio: 0.0459966 max_rss_mb: 479.227
233MB 32thread folly -> kops/s: 109.95 io_bytes/op: 314799 miss_ratio: 0.0450032 max_rss_mb: 400.738
233MB 32thread gt_clock -> kops/s: 2.353 io_bytes/op: 385397 miss_ratio: 0.048445 max_rss_mb: 500.688
233MB 32thread new_clock -> kops/s: 1088.95 io_bytes/op: 2567.02 miss_ratio: 0.0330593 max_rss_mb: 303.402
233MB 128thread base -> kops/s: 84.302 io_bytes/op: 378020 miss_ratio: 0.0466558 max_rss_mb: 1051.84
233MB 128thread folly -> kops/s: 89.921 io_bytes/op: 338242 miss_ratio: 0.0460309 max_rss_mb: 812.785
233MB 128thread gt_clock -> kops/s: 2.588 io_bytes/op: 462833 miss_ratio: 0.0509158 max_rss_mb: 1109.94
233MB 128thread new_clock -> kops/s: 1299.26 io_bytes/op: 2565.94 miss_ratio: 0.0330531 max_rss_mb: 361.016
89MB 1thread base -> kops/s: 0.574 io_bytes/op: 5.35977e+06 miss_ratio: 0.274427 max_rss_mb: 91.3086
89MB 1thread folly -> kops/s: 0.578 io_bytes/op: 5.16549e+06 miss_ratio: 0.27276 max_rss_mb: 96.8984
89MB 1thread gt_clock -> kops/s: 0.512 io_bytes/op: 4.13111e+06 miss_ratio: 0.242817 max_rss_mb: 119.441
89MB 1thread new_clock -> kops/s: 48.172 io_bytes/op: 2709.76 miss_ratio: 0.0346162 max_rss_mb: 100.754
89MB 32thread base -> kops/s: 5.779 io_bytes/op: 6.14192e+06 miss_ratio: 0.320399 max_rss_mb: 311.812
89MB 32thread folly -> kops/s: 5.601 io_bytes/op: 5.83838e+06 miss_ratio: 0.313123 max_rss_mb: 252.418
89MB 32thread gt_clock -> kops/s: 0.77 io_bytes/op: 3.99236e+06 miss_ratio: 0.236296 max_rss_mb: 396.422
89MB 32thread new_clock -> kops/s: 1064.97 io_bytes/op: 2687.23 miss_ratio: 0.0346134 max_rss_mb: 155.293
89MB 128thread base -> kops/s: 4.959 io_bytes/op: 6.20297e+06 miss_ratio: 0.323945 max_rss_mb: 823.43
89MB 128thread folly -> kops/s: 4.962 io_bytes/op: 5.9601e+06 miss_ratio: 0.319857 max_rss_mb: 626.824
89MB 128thread gt_clock -> kops/s: 1.009 io_bytes/op: 4.1083e+06 miss_ratio: 0.242512 max_rss_mb: 1095.32
89MB 128thread new_clock -> kops/s: 1224.39 io_bytes/op: 2688.2 miss_ratio: 0.0346207 max_rss_mb: 218.223
^ Now something interesting has happened: the new clock cache has gained a dramatic lead in the single-threaded case, and this is because the cache is so small, and full filters are so big, that dividing the cache into 64 shards leads to significant (random) imbalances in cache shards and excessive churn in imbalanced shards. This new clock cache only uses two shards for this configuration, and that helps to ensure that entries are part of a sufficiently big pool that their eviction order resembles the single-shard order. (This effect is not seen with partitioned index+filters.)
Even smaller cache size:
34MB 1thread base -> kops/s: 0.198 io_bytes/op: 1.65342e+07 miss_ratio: 0.939466 max_rss_mb: 48.6914
34MB 1thread folly -> kops/s: 0.201 io_bytes/op: 1.63416e+07 miss_ratio: 0.939081 max_rss_mb: 45.3281
34MB 1thread gt_clock -> kops/s: 0.448 io_bytes/op: 4.43957e+06 miss_ratio: 0.266749 max_rss_mb: 100.523
34MB 1thread new_clock -> kops/s: 1.055 io_bytes/op: 1.85439e+06 miss_ratio: 0.107512 max_rss_mb: 75.3125
34MB 32thread base -> kops/s: 3.346 io_bytes/op: 1.64852e+07 miss_ratio: 0.93596 max_rss_mb: 180.48
34MB 32thread folly -> kops/s: 3.431 io_bytes/op: 1.62857e+07 miss_ratio: 0.935693 max_rss_mb: 137.531
34MB 32thread gt_clock -> kops/s: 1.47 io_bytes/op: 4.89704e+06 miss_ratio: 0.295081 max_rss_mb: 392.465
34MB 32thread new_clock -> kops/s: 8.19 io_bytes/op: 3.70456e+06 miss_ratio: 0.20826 max_rss_mb: 519.793
34MB 128thread base -> kops/s: 2.293 io_bytes/op: 1.64351e+07 miss_ratio: 0.931866 max_rss_mb: 449.484
34MB 128thread folly -> kops/s: 2.34 io_bytes/op: 1.6219e+07 miss_ratio: 0.932023 max_rss_mb: 396.457
34MB 128thread gt_clock -> kops/s: 1.798 io_bytes/op: 5.4241e+06 miss_ratio: 0.324881 max_rss_mb: 1104.41
34MB 128thread new_clock -> kops/s: 10.519 io_bytes/op: 2.39354e+06 miss_ratio: 0.136147 max_rss_mb: 1050.52
As the miss ratio gets higher (say, above 10%), the CPU time spent in eviction starts to erode the advantage of using fewer shards (13% miss rate much lower than 94%). LRU's O(1) eviction time can eventually pay off when there's enough block cache churn:
13MB 1thread base -> kops/s: 0.195 io_bytes/op: 1.65732e+07 miss_ratio: 0.946604 max_rss_mb: 45.6328
13MB 1thread folly -> kops/s: 0.197 io_bytes/op: 1.63793e+07 miss_ratio: 0.94661 max_rss_mb: 33.8633
13MB 1thread gt_clock -> kops/s: 0.519 io_bytes/op: 4.43316e+06 miss_ratio: 0.269379 max_rss_mb: 100.684
13MB 1thread new_clock -> kops/s: 0.176 io_bytes/op: 1.54148e+07 miss_ratio: 0.91545 max_rss_mb: 66.2383
13MB 32thread base -> kops/s: 3.266 io_bytes/op: 1.65544e+07 miss_ratio: 0.943386 max_rss_mb: 132.492
13MB 32thread folly -> kops/s: 3.396 io_bytes/op: 1.63142e+07 miss_ratio: 0.943243 max_rss_mb: 101.863
13MB 32thread gt_clock -> kops/s: 2.758 io_bytes/op: 5.13714e+06 miss_ratio: 0.310652 max_rss_mb: 396.121
13MB 32thread new_clock -> kops/s: 3.11 io_bytes/op: 1.23419e+07 miss_ratio: 0.708425 max_rss_mb: 321.758
13MB 128thread base -> kops/s: 2.31 io_bytes/op: 1.64823e+07 miss_ratio: 0.939543 max_rss_mb: 425.539
13MB 128thread folly -> kops/s: 2.339 io_bytes/op: 1.6242e+07 miss_ratio: 0.939966 max_rss_mb: 346.098
13MB 128thread gt_clock -> kops/s: 3.223 io_bytes/op: 5.76928e+06 miss_ratio: 0.345899 max_rss_mb: 1087.77
13MB 128thread new_clock -> kops/s: 2.984 io_bytes/op: 1.05341e+07 miss_ratio: 0.606198 max_rss_mb: 898.27
gt_clock is clearly blowing way past its memory budget for lower miss rates and best throughput. new_clock also seems to be exceeding budgets, and this warrants more investigation but is not the use case we are targeting with the new cache. With partitioned index+filter, the miss ratio is much better, and although still high enough that the eviction CPU time is definitely offsetting mutex contention:
13MB 1thread base -> kops/s: 16.326 io_bytes/op: 23743.9 miss_ratio: 0.205362 max_rss_mb: 65.2852
13MB 1thread folly -> kops/s: 15.574 io_bytes/op: 19415 miss_ratio: 0.184157 max_rss_mb: 56.3516
13MB 1thread gt_clock -> kops/s: 14.459 io_bytes/op: 22873 miss_ratio: 0.198355 max_rss_mb: 63.9688
13MB 1thread new_clock -> kops/s: 16.34 io_bytes/op: 24386.5 miss_ratio: 0.210512 max_rss_mb: 61.707
13MB 128thread base -> kops/s: 289.786 io_bytes/op: 23710.9 miss_ratio: 0.205056 max_rss_mb: 103.57
13MB 128thread folly -> kops/s: 185.282 io_bytes/op: 19433.1 miss_ratio: 0.184275 max_rss_mb: 116.219
13MB 128thread gt_clock -> kops/s: 354.451 io_bytes/op: 23150.6 miss_ratio: 0.200495 max_rss_mb: 102.871
13MB 128thread new_clock -> kops/s: 295.359 io_bytes/op: 24626.4 miss_ratio: 0.212452 max_rss_mb: 121.109
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10626
Test Plan: updated unit tests, stress/crash test runs including with TSAN, ASAN, UBSAN
Reviewed By: anand1976
Differential Revision: D39368406
Pulled By: pdillinger
fbshipit-source-id: 5afc44da4c656f8f751b44552bbf27bd3ca6fef9
2 years ago
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capacity_(capacity),
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strict_capacity_limit_(strict_capacity_limit),
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table_(
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CalcHashBits(capacity, estimated_value_size, metadata_charge_policy)),
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usage_(0),
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lru_usage_(0) {
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// Make empty circular linked list.
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lru_.next = &lru_;
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lru_.prev = &lru_;
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lru_low_pri_ = &lru_;
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}
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void LRUCacheShard::EraseUnRefEntries() {
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autovector<LRUHandle> last_reference_list;
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{
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DMutexLock l(mutex_);
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while (lru_.next != &lru_) {
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LRUHandle* old = lru_.next;
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// LRU list contains only elements which can be evicted.
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assert(old->IsVisible() && !old->HasRefs());
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LRU_Remove(old);
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table_.Remove(old);
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assert(usage_ >= old->total_charge);
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usage_ -= old->total_charge;
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last_reference_list.push_back(*old);
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}
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}
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// Free the entries here outside of mutex for performance reasons.
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for (auto& h : last_reference_list) {
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h.FreeData();
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}
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}
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void LRUCacheShard::ApplyToSomeEntries(
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const std::function<void(const Slice& key, void* value, size_t charge,
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DeleterFn deleter)>& callback,
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size_t average_entries_per_lock, size_t* state) {
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// The state is essentially going to be the starting hash, which works
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// nicely even if we resize between calls because we use upper-most
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// hash bits for table indexes.
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DMutexLock l(mutex_);
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size_t length_bits = table_.GetLengthBits();
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size_t length = table_.GetTableSize();
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assert(average_entries_per_lock > 0);
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// Assuming we are called with same average_entries_per_lock repeatedly,
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// this simplifies some logic (index_end will not overflow).
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assert(average_entries_per_lock < length || *state == 0);
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size_t index_begin = *state >> (sizeof(size_t) * 8u - length_bits);
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size_t index_end = index_begin + average_entries_per_lock;
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if (index_end >= length) {
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// Going to end
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index_end = length;
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*state = SIZE_MAX;
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} else {
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*state = index_end << (sizeof(size_t) * 8u - length_bits);
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}
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table_.ApplyToEntriesRange(
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[callback,
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metadata_charge_policy = metadata_charge_policy_](LRUHandle* h) {
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callback(h->key(), h->value, h->GetCharge(metadata_charge_policy),
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h->deleter);
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},
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index_begin, index_end);
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}
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void LRUCacheShard::LRU_Remove(LRUHandle* h) {
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assert(h->next != nullptr);
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assert(h->prev != nullptr);
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h->next->prev = h->prev;
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h->prev->next = h->next;
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h->prev = h->next = nullptr;
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assert(lru_usage_ >= h->total_charge);
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lru_usage_ -= h->total_charge;
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}
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void LRUCacheShard::LRU_Insert(LRUHandle* h) {
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assert(h->next == nullptr);
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assert(h->prev == nullptr);
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// Insert h to head of LRU list.
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h->next = &lru_;
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h->prev = lru_.prev;
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h->prev->next = h;
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h->next->prev = h;
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lru_usage_ += h->total_charge;
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}
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void LRUCacheShard::EvictFromLRU(size_t charge,
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autovector<LRUHandle>* deleted) {
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while ((usage_ + charge) > capacity_ && lru_.next != &lru_) {
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LRUHandle* old = lru_.next;
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// LRU list contains only elements which can be evicted.
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assert(old->IsVisible() && !old->HasRefs());
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LRU_Remove(old);
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table_.Remove(old);
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assert(usage_ >= old->total_charge);
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usage_ -= old->total_charge;
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deleted->push_back(*old);
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}
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}
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size_t LRUCacheShard::CalcEstimatedHandleCharge(
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size_t estimated_value_size,
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CacheMetadataChargePolicy metadata_charge_policy) {
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LRUHandle h;
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h.CalcTotalCharge(estimated_value_size, metadata_charge_policy);
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return h.total_charge;
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}
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int LRUCacheShard::CalcHashBits(
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size_t capacity, size_t estimated_value_size,
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CacheMetadataChargePolicy metadata_charge_policy) {
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size_t handle_charge =
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CalcEstimatedHandleCharge(estimated_value_size, metadata_charge_policy);
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assert(handle_charge > 0);
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uint32_t num_entries =
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static_cast<uint32_t>(capacity / (kLoadFactor * handle_charge)) + 1;
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assert(num_entries <= uint32_t{1} << 31);
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return FloorLog2((num_entries << 1) - 1);
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}
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void LRUCacheShard::SetCapacity(size_t capacity) {
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autovector<LRUHandle> last_reference_list;
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{
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DMutexLock l(mutex_);
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if (capacity > capacity_) {
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assert(false); // Not supported.
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}
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capacity_ = capacity;
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EvictFromLRU(0, &last_reference_list);
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}
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// Free the entries here outside of mutex for performance reasons.
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for (auto& h : last_reference_list) {
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h.FreeData();
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}
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}
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void LRUCacheShard::SetStrictCapacityLimit(bool strict_capacity_limit) {
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|
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DMutexLock l(mutex_);
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strict_capacity_limit_ = strict_capacity_limit;
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}
|
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|
|
|
Status LRUCacheShard::Insert(const Slice& key, uint32_t hash, void* value,
|
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|
|
size_t charge, Cache::DeleterFn deleter,
|
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|
|
LRUHandle** handle, Cache::Priority /*priority*/) {
|
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|
|
if (key.size() != kCacheKeySize) {
|
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|
|
return Status::NotSupported("FastLRUCache only supports key size " +
|
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|
|
std::to_string(kCacheKeySize) + "B");
|
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|
|
}
|
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|
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|
|
LRUHandle tmp;
|
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|
tmp.value = value;
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|
|
tmp.deleter = deleter;
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|
tmp.hash = hash;
|
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|
|
tmp.CalcTotalCharge(charge, metadata_charge_policy_);
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|
for (int i = 0; i < kCacheKeySize; i++) {
|
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|
|
tmp.key_data[i] = key.data()[i];
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|
}
|
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|
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|
|
Status s = Status::OK();
|
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|
|
autovector<LRUHandle> last_reference_list;
|
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|
|
{
|
|
|
|
DMutexLock l(mutex_);
|
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|
|
assert(table_.GetOccupancy() <= table_.GetOccupancyLimit());
|
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|
|
|
|
|
|
// Free the space following strict LRU policy until enough space
|
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|
|
// is freed or the lru list is empty.
|
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|
|
EvictFromLRU(tmp.total_charge, &last_reference_list);
|
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|
|
if ((usage_ + tmp.total_charge > capacity_ &&
|
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|
|
(strict_capacity_limit_ || handle == nullptr)) ||
|
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|
|
table_.GetOccupancy() == table_.GetOccupancyLimit()) {
|
|
|
|
// There are two measures of capacity:
|
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|
|
// - Space (or charge) capacity: The maximum possible sum of the charges
|
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|
|
// of the elements.
|
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|
|
// - Table capacity: The number of slots in the hash table.
|
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|
|
// These are incomparable, in the sense that one doesn't imply the other.
|
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|
|
// Typically we will reach space capacity before table capacity---
|
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|
|
// if the user always inserts values with size equal to
|
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|
|
// estimated_value_size, then at most a kLoadFactor fraction of slots
|
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|
|
// will ever be occupied. But in some cases we may reach table capacity
|
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|
|
// before space capacity---if the user initially claims a very large
|
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|
|
// estimated_value_size but then inserts tiny values, more elements than
|
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|
// initially estimated will be inserted.
|
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|
|
|
|
|
|
// TODO(Guido) Some tests (at least two from cache_test, as well as the
|
|
|
|
// stress tests) currently assume the table capacity is unbounded.
|
|
|
|
if (handle == nullptr) {
|
|
|
|
// Don't insert the entry but still return ok, as if the entry inserted
|
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|
|
// into cache and get evicted immediately.
|
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|
last_reference_list.push_back(tmp);
|
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|
|
} else {
|
|
|
|
if (table_.GetOccupancy() == table_.GetOccupancyLimit()) {
|
|
|
|
// TODO: Consider using a distinct status for this case, but usually
|
|
|
|
// it will be handled the same way as reaching charge capacity limit
|
|
|
|
s = Status::MemoryLimit(
|
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|
|
"Insert failed because all slots in the hash table are full.");
|
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|
|
} else {
|
|
|
|
s = Status::MemoryLimit(
|
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|
|
"Insert failed because the total charge has exceeded the "
|
|
|
|
"capacity.");
|
|
|
|
}
|
|
|
|
}
|
|
|
|
} else {
|
|
|
|
// Insert into the cache. Note that the cache might get larger than its
|
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|
|
// capacity if not enough space was freed up.
|
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|
|
LRUHandle* old;
|
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|
|
LRUHandle* h = table_.Insert(&tmp, &old);
|
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|
|
assert(h != nullptr); // We're below occupancy, so this insertion should
|
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|
|
// never fail.
|
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|
|
usage_ += h->total_charge;
|
|
|
|
if (old != nullptr) {
|
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|
|
s = Status::OkOverwritten();
|
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|
|
assert(old->IsVisible());
|
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|
|
table_.Exclude(old);
|
|
|
|
if (!old->HasRefs()) {
|
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|
|
// old is on LRU because it's in cache and its reference count is 0.
|
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|
|
LRU_Remove(old);
|
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|
|
table_.Remove(old);
|
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|
|
assert(usage_ >= old->total_charge);
|
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|
|
usage_ -= old->total_charge;
|
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|
|
last_reference_list.push_back(*old);
|
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|
|
}
|
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|
|
}
|
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|
|
if (handle == nullptr) {
|
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|
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LRU_Insert(h);
|
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|
|
} else {
|
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|
|
// If caller already holds a ref, no need to take one here.
|
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|
|
if (!h->HasRefs()) {
|
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h->Ref();
|
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|
}
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*handle = h;
|
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}
|
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|
|
}
|
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|
|
}
|
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|
|
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|
|
|
// Free the entries here outside of mutex for performance reasons.
|
|
|
|
for (auto& h : last_reference_list) {
|
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|
|
h.FreeData();
|
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|
|
}
|
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|
|
|
|
|
|
return s;
|
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|
|
}
|
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|
|
|
|
|
|
LRUHandle* LRUCacheShard::Lookup(const Slice& key, uint32_t hash) {
|
|
|
|
LRUHandle* h = nullptr;
|
|
|
|
{
|
|
|
|
DMutexLock l(mutex_);
|
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|
|
h = table_.Lookup(key, hash);
|
|
|
|
if (h != nullptr) {
|
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|
|
assert(h->IsVisible());
|
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|
|
if (!h->HasRefs()) {
|
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|
|
// The entry is in LRU since it's in hash and has no external
|
|
|
|
// references.
|
|
|
|
LRU_Remove(h);
|
|
|
|
}
|
|
|
|
h->Ref();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
return h;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool LRUCacheShard::Ref(LRUHandle* h) {
|
|
|
|
DMutexLock l(mutex_);
|
|
|
|
// To create another reference - entry must be already externally referenced.
|
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|
|
assert(h->HasRefs());
|
|
|
|
h->Ref();
|
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|
|
return true;
|
|
|
|
}
|
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|
|
|
|
|
|
bool LRUCacheShard::Release(LRUHandle* h, bool erase_if_last_ref) {
|
|
|
|
if (h == nullptr) {
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
LRUHandle copy;
|
|
|
|
bool last_reference = false;
|
|
|
|
{
|
|
|
|
DMutexLock l(mutex_);
|
|
|
|
last_reference = h->Unref();
|
|
|
|
if (last_reference && h->IsVisible()) {
|
|
|
|
// The item is still in cache, and nobody else holds a reference to it.
|
|
|
|
if (usage_ > capacity_ || erase_if_last_ref) {
|
|
|
|
// The LRU list must be empty since the cache is full.
|
|
|
|
assert(lru_.next == &lru_ || erase_if_last_ref);
|
|
|
|
// Take this opportunity and remove the item.
|
|
|
|
table_.Remove(h);
|
|
|
|
} else {
|
|
|
|
// Put the item back on the LRU list, and don't free it.
|
|
|
|
LRU_Insert(h);
|
|
|
|
last_reference = false;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
// If it was the last reference, then decrement the cache usage.
|
|
|
|
if (last_reference) {
|
|
|
|
assert(usage_ >= h->total_charge);
|
|
|
|
usage_ -= h->total_charge;
|
|
|
|
copy = *h;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Free the entry here outside of mutex for performance reasons.
|
|
|
|
if (last_reference) {
|
|
|
|
copy.FreeData();
|
|
|
|
}
|
|
|
|
return last_reference;
|
|
|
|
}
|
|
|
|
|
|
|
|
void LRUCacheShard::Erase(const Slice& key, uint32_t hash) {
|
|
|
|
LRUHandle copy;
|
|
|
|
bool last_reference = false;
|
|
|
|
{
|
|
|
|
DMutexLock l(mutex_);
|
|
|
|
LRUHandle* h = table_.Lookup(key, hash);
|
|
|
|
if (h != nullptr) {
|
|
|
|
table_.Exclude(h);
|
|
|
|
if (!h->HasRefs()) {
|
|
|
|
// The entry is in LRU since it's in cache and has no external
|
|
|
|
// references.
|
|
|
|
LRU_Remove(h);
|
|
|
|
table_.Remove(h);
|
|
|
|
assert(usage_ >= h->total_charge);
|
|
|
|
usage_ -= h->total_charge;
|
|
|
|
last_reference = true;
|
|
|
|
copy = *h;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
// Free the entry here outside of mutex for performance reasons.
|
|
|
|
// last_reference will only be true if e != nullptr.
|
|
|
|
if (last_reference) {
|
|
|
|
copy.FreeData();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
size_t LRUCacheShard::GetUsage() const {
|
|
|
|
DMutexLock l(mutex_);
|
|
|
|
return usage_;
|
|
|
|
}
|
|
|
|
|
|
|
|
size_t LRUCacheShard::GetPinnedUsage() const {
|
|
|
|
DMutexLock l(mutex_);
|
|
|
|
assert(usage_ >= lru_usage_);
|
|
|
|
return usage_ - lru_usage_;
|
|
|
|
}
|
|
|
|
|
Revamp, optimize new experimental clock cache (#10626)
Summary:
* Consolidates most metadata into a single word per slot so that more
can be accomplished with a single atomic update. In the common case,
Lookup was previously about 4 atomic updates, now just 1 atomic update.
Common case Release was previously 1 atomic read + 1 atomic update,
now just 1 atomic update.
* Eliminate spins / waits / yields, which likely threaten some "lock free"
benefits. Compare-exchange loops are only used in explicit Erase, and
strict_capacity_limit=true Insert. Eviction uses opportunistic compare-
exchange.
* Relaxes some aggressiveness and guarantees. For example,
* Duplicate Inserts will sometimes go undetected and the shadow duplicate
will age out with eviction.
* In many cases, the older Inserted value for a given cache key will be kept
(i.e. Insert does not support overwrite).
* Entries explicitly erased (rather than evicted) might not be freed
immediately in some rare cases.
* With strict_capacity_limit=false, capacity limit is not tracked/enforced as
precisely as LRUCache, but is self-correcting and should only deviate by a
very small number of extra or fewer entries.
* Use smaller "computed default" number of cache shards in many cases,
because benefits to larger usage tracking / eviction pools outweigh the small
cost of more lock-free atomic contention. The improvement in CPU and I/O
is dramatic in some limit-memory cases.
* Even without the sharding change, the eviction algorithm is likely more
effective than LRU overall because it's more stateful, even though the
"hot path" state tracking for it is essentially free with ref counting. It
is like a generalized CLOCK with aging (see code comments). I don't have
performance numbers showing a specific improvement, but in theory, for a
Poisson access pattern to each block, keeping some state allows better
estimation of time to next access (Poisson interval) than strict LRU. The
bounded randomness in CLOCK can also reduce "cliff" effect for repeated
range scans approaching and exceeding cache size.
## Hot path algorithm comparison
Rough descriptions, focusing on number and kind of atomic operations:
* Old `Lookup()` (2-5 atomic updates per probe):
```
Loop:
Increment internal ref count at slot
If possible hit:
Check flags atomic (and non-atomic fields)
If cache hit:
Three distinct updates to 'flags' atomic
Increment refs for internal-to-external
Return
Decrement internal ref count
while atomic read 'displacements' > 0
```
* New `Lookup()` (1-2 atomic updates per probe):
```
Loop:
Increment acquire counter in meta word (optimistic)
If visible entry (already read meta word):
If match (read non-atomic fields):
Return
Else:
Decrement acquire counter in meta word
Else if invisible entry (rare, already read meta word):
Decrement acquire counter in meta word
while atomic read 'displacements' > 0
```
* Old `Release()` (1 atomic update, conditional on atomic read, rarely more):
```
Read atomic ref count
If last reference and invisible (rare):
Use CAS etc. to remove
Return
Else:
Decrement ref count
```
* New `Release()` (1 unconditional atomic update, rarely more):
```
Increment release counter in meta word
If last reference and invisible (rare):
Use CAS etc. to remove
Return
```
## Performance test setup
Build DB with
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16
```
Test with
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=readrandom -readonly -num=30000000 -bloom_bits=16 -cache_index_and_filter_blocks=1 -cache_size=${CACHE_MB}000000 -duration 60 -threads=$THREADS -statistics
```
Numbers on a single socket Skylake Xeon system with 48 hardware threads, DEBUG_LEVEL=0 PORTABLE=0. Very similar story on a dual socket system with 80 hardware threads. Using (every 2nd) Fibonacci MB cache sizes to sample the territory between powers of two. Configurations:
base: LRUCache before this change, but with db_bench change to default cache_numshardbits=-1 (instead of fixed at 6)
folly: LRUCache before this change, with folly enabled (distributed mutex) but on an old compiler (sorry)
gt_clock: experimental ClockCache before this change
new_clock: experimental ClockCache with this change
## Performance test results
First test "hot path" read performance, with block cache large enough for whole DB:
4181MB 1thread base -> kops/s: 47.761
4181MB 1thread folly -> kops/s: 45.877
4181MB 1thread gt_clock -> kops/s: 51.092
4181MB 1thread new_clock -> kops/s: 53.944
4181MB 16thread base -> kops/s: 284.567
4181MB 16thread folly -> kops/s: 249.015
4181MB 16thread gt_clock -> kops/s: 743.762
4181MB 16thread new_clock -> kops/s: 861.821
4181MB 24thread base -> kops/s: 303.415
4181MB 24thread folly -> kops/s: 266.548
4181MB 24thread gt_clock -> kops/s: 975.706
4181MB 24thread new_clock -> kops/s: 1205.64 (~= 24 * 53.944)
4181MB 32thread base -> kops/s: 311.251
4181MB 32thread folly -> kops/s: 274.952
4181MB 32thread gt_clock -> kops/s: 1045.98
4181MB 32thread new_clock -> kops/s: 1370.38
4181MB 48thread base -> kops/s: 310.504
4181MB 48thread folly -> kops/s: 268.322
4181MB 48thread gt_clock -> kops/s: 1195.65
4181MB 48thread new_clock -> kops/s: 1604.85 (~= 24 * 1.25 * 53.944)
4181MB 64thread base -> kops/s: 307.839
4181MB 64thread folly -> kops/s: 272.172
4181MB 64thread gt_clock -> kops/s: 1204.47
4181MB 64thread new_clock -> kops/s: 1615.37
4181MB 128thread base -> kops/s: 310.934
4181MB 128thread folly -> kops/s: 267.468
4181MB 128thread gt_clock -> kops/s: 1188.75
4181MB 128thread new_clock -> kops/s: 1595.46
Whether we have just one thread on a quiet system or an overload of threads, the new version wins every time in thousand-ops per second, sometimes dramatically so. Mutex-based implementation quickly becomes contention-limited. New clock cache shows essentially perfect scaling up to number of physical cores (24), and then each hyperthreaded core adding about 1/4 the throughput of an additional physical core (see 48 thread case). Block cache miss rates (omitted above) are negligible across the board. With partitioned instead of full filters, the maximum speed-up vs. base is more like 2.5x rather than 5x.
Now test a large block cache with low miss ratio, but some eviction is required:
1597MB 1thread base -> kops/s: 46.603 io_bytes/op: 1584.63 miss_ratio: 0.0201066 max_rss_mb: 1589.23
1597MB 1thread folly -> kops/s: 45.079 io_bytes/op: 1530.03 miss_ratio: 0.019872 max_rss_mb: 1550.43
1597MB 1thread gt_clock -> kops/s: 48.711 io_bytes/op: 1566.63 miss_ratio: 0.0198923 max_rss_mb: 1691.4
1597MB 1thread new_clock -> kops/s: 51.531 io_bytes/op: 1589.07 miss_ratio: 0.0201969 max_rss_mb: 1583.56
1597MB 32thread base -> kops/s: 301.174 io_bytes/op: 1439.52 miss_ratio: 0.0184218 max_rss_mb: 1656.59
1597MB 32thread folly -> kops/s: 273.09 io_bytes/op: 1375.12 miss_ratio: 0.0180002 max_rss_mb: 1586.8
1597MB 32thread gt_clock -> kops/s: 904.497 io_bytes/op: 1411.29 miss_ratio: 0.0179934 max_rss_mb: 1775.89
1597MB 32thread new_clock -> kops/s: 1182.59 io_bytes/op: 1440.77 miss_ratio: 0.0185449 max_rss_mb: 1636.45
1597MB 128thread base -> kops/s: 309.91 io_bytes/op: 1438.25 miss_ratio: 0.018399 max_rss_mb: 1689.98
1597MB 128thread folly -> kops/s: 267.605 io_bytes/op: 1394.16 miss_ratio: 0.0180286 max_rss_mb: 1631.91
1597MB 128thread gt_clock -> kops/s: 691.518 io_bytes/op: 9056.73 miss_ratio: 0.0186572 max_rss_mb: 1982.26
1597MB 128thread new_clock -> kops/s: 1406.12 io_bytes/op: 1440.82 miss_ratio: 0.0185463 max_rss_mb: 1685.63
610MB 1thread base -> kops/s: 45.511 io_bytes/op: 2279.61 miss_ratio: 0.0290528 max_rss_mb: 615.137
610MB 1thread folly -> kops/s: 43.386 io_bytes/op: 2217.29 miss_ratio: 0.0289282 max_rss_mb: 600.996
610MB 1thread gt_clock -> kops/s: 46.207 io_bytes/op: 2275.51 miss_ratio: 0.0290057 max_rss_mb: 637.934
610MB 1thread new_clock -> kops/s: 48.879 io_bytes/op: 2283.1 miss_ratio: 0.0291253 max_rss_mb: 613.5
610MB 32thread base -> kops/s: 306.59 io_bytes/op: 2250 miss_ratio: 0.0288721 max_rss_mb: 683.402
610MB 32thread folly -> kops/s: 269.176 io_bytes/op: 2187.86 miss_ratio: 0.0286938 max_rss_mb: 628.742
610MB 32thread gt_clock -> kops/s: 855.097 io_bytes/op: 2279.26 miss_ratio: 0.0288009 max_rss_mb: 733.062
610MB 32thread new_clock -> kops/s: 1121.47 io_bytes/op: 2244.29 miss_ratio: 0.0289046 max_rss_mb: 666.453
610MB 128thread base -> kops/s: 305.079 io_bytes/op: 2252.43 miss_ratio: 0.0288884 max_rss_mb: 723.457
610MB 128thread folly -> kops/s: 269.583 io_bytes/op: 2204.58 miss_ratio: 0.0287001 max_rss_mb: 676.426
610MB 128thread gt_clock -> kops/s: 53.298 io_bytes/op: 8128.98 miss_ratio: 0.0292452 max_rss_mb: 956.273
610MB 128thread new_clock -> kops/s: 1301.09 io_bytes/op: 2246.04 miss_ratio: 0.0289171 max_rss_mb: 788.812
The new version is still winning every time, sometimes dramatically so, and we can tell from the maximum resident memory numbers (which contain some noise, by the way) that the new cache is not cheating on memory usage. IMPORTANT: The previous generation experimental clock cache appears to hit a serious bottleneck in the higher thread count configurations, presumably due to some of its waiting functionality. (The same bottleneck is not seen with partitioned index+filters.)
Now we consider even smaller cache sizes, with higher miss ratios, eviction work, etc.
233MB 1thread base -> kops/s: 10.557 io_bytes/op: 227040 miss_ratio: 0.0403105 max_rss_mb: 247.371
233MB 1thread folly -> kops/s: 15.348 io_bytes/op: 112007 miss_ratio: 0.0372238 max_rss_mb: 245.293
233MB 1thread gt_clock -> kops/s: 6.365 io_bytes/op: 244854 miss_ratio: 0.0413873 max_rss_mb: 259.844
233MB 1thread new_clock -> kops/s: 47.501 io_bytes/op: 2591.93 miss_ratio: 0.0330989 max_rss_mb: 242.461
233MB 32thread base -> kops/s: 96.498 io_bytes/op: 363379 miss_ratio: 0.0459966 max_rss_mb: 479.227
233MB 32thread folly -> kops/s: 109.95 io_bytes/op: 314799 miss_ratio: 0.0450032 max_rss_mb: 400.738
233MB 32thread gt_clock -> kops/s: 2.353 io_bytes/op: 385397 miss_ratio: 0.048445 max_rss_mb: 500.688
233MB 32thread new_clock -> kops/s: 1088.95 io_bytes/op: 2567.02 miss_ratio: 0.0330593 max_rss_mb: 303.402
233MB 128thread base -> kops/s: 84.302 io_bytes/op: 378020 miss_ratio: 0.0466558 max_rss_mb: 1051.84
233MB 128thread folly -> kops/s: 89.921 io_bytes/op: 338242 miss_ratio: 0.0460309 max_rss_mb: 812.785
233MB 128thread gt_clock -> kops/s: 2.588 io_bytes/op: 462833 miss_ratio: 0.0509158 max_rss_mb: 1109.94
233MB 128thread new_clock -> kops/s: 1299.26 io_bytes/op: 2565.94 miss_ratio: 0.0330531 max_rss_mb: 361.016
89MB 1thread base -> kops/s: 0.574 io_bytes/op: 5.35977e+06 miss_ratio: 0.274427 max_rss_mb: 91.3086
89MB 1thread folly -> kops/s: 0.578 io_bytes/op: 5.16549e+06 miss_ratio: 0.27276 max_rss_mb: 96.8984
89MB 1thread gt_clock -> kops/s: 0.512 io_bytes/op: 4.13111e+06 miss_ratio: 0.242817 max_rss_mb: 119.441
89MB 1thread new_clock -> kops/s: 48.172 io_bytes/op: 2709.76 miss_ratio: 0.0346162 max_rss_mb: 100.754
89MB 32thread base -> kops/s: 5.779 io_bytes/op: 6.14192e+06 miss_ratio: 0.320399 max_rss_mb: 311.812
89MB 32thread folly -> kops/s: 5.601 io_bytes/op: 5.83838e+06 miss_ratio: 0.313123 max_rss_mb: 252.418
89MB 32thread gt_clock -> kops/s: 0.77 io_bytes/op: 3.99236e+06 miss_ratio: 0.236296 max_rss_mb: 396.422
89MB 32thread new_clock -> kops/s: 1064.97 io_bytes/op: 2687.23 miss_ratio: 0.0346134 max_rss_mb: 155.293
89MB 128thread base -> kops/s: 4.959 io_bytes/op: 6.20297e+06 miss_ratio: 0.323945 max_rss_mb: 823.43
89MB 128thread folly -> kops/s: 4.962 io_bytes/op: 5.9601e+06 miss_ratio: 0.319857 max_rss_mb: 626.824
89MB 128thread gt_clock -> kops/s: 1.009 io_bytes/op: 4.1083e+06 miss_ratio: 0.242512 max_rss_mb: 1095.32
89MB 128thread new_clock -> kops/s: 1224.39 io_bytes/op: 2688.2 miss_ratio: 0.0346207 max_rss_mb: 218.223
^ Now something interesting has happened: the new clock cache has gained a dramatic lead in the single-threaded case, and this is because the cache is so small, and full filters are so big, that dividing the cache into 64 shards leads to significant (random) imbalances in cache shards and excessive churn in imbalanced shards. This new clock cache only uses two shards for this configuration, and that helps to ensure that entries are part of a sufficiently big pool that their eviction order resembles the single-shard order. (This effect is not seen with partitioned index+filters.)
Even smaller cache size:
34MB 1thread base -> kops/s: 0.198 io_bytes/op: 1.65342e+07 miss_ratio: 0.939466 max_rss_mb: 48.6914
34MB 1thread folly -> kops/s: 0.201 io_bytes/op: 1.63416e+07 miss_ratio: 0.939081 max_rss_mb: 45.3281
34MB 1thread gt_clock -> kops/s: 0.448 io_bytes/op: 4.43957e+06 miss_ratio: 0.266749 max_rss_mb: 100.523
34MB 1thread new_clock -> kops/s: 1.055 io_bytes/op: 1.85439e+06 miss_ratio: 0.107512 max_rss_mb: 75.3125
34MB 32thread base -> kops/s: 3.346 io_bytes/op: 1.64852e+07 miss_ratio: 0.93596 max_rss_mb: 180.48
34MB 32thread folly -> kops/s: 3.431 io_bytes/op: 1.62857e+07 miss_ratio: 0.935693 max_rss_mb: 137.531
34MB 32thread gt_clock -> kops/s: 1.47 io_bytes/op: 4.89704e+06 miss_ratio: 0.295081 max_rss_mb: 392.465
34MB 32thread new_clock -> kops/s: 8.19 io_bytes/op: 3.70456e+06 miss_ratio: 0.20826 max_rss_mb: 519.793
34MB 128thread base -> kops/s: 2.293 io_bytes/op: 1.64351e+07 miss_ratio: 0.931866 max_rss_mb: 449.484
34MB 128thread folly -> kops/s: 2.34 io_bytes/op: 1.6219e+07 miss_ratio: 0.932023 max_rss_mb: 396.457
34MB 128thread gt_clock -> kops/s: 1.798 io_bytes/op: 5.4241e+06 miss_ratio: 0.324881 max_rss_mb: 1104.41
34MB 128thread new_clock -> kops/s: 10.519 io_bytes/op: 2.39354e+06 miss_ratio: 0.136147 max_rss_mb: 1050.52
As the miss ratio gets higher (say, above 10%), the CPU time spent in eviction starts to erode the advantage of using fewer shards (13% miss rate much lower than 94%). LRU's O(1) eviction time can eventually pay off when there's enough block cache churn:
13MB 1thread base -> kops/s: 0.195 io_bytes/op: 1.65732e+07 miss_ratio: 0.946604 max_rss_mb: 45.6328
13MB 1thread folly -> kops/s: 0.197 io_bytes/op: 1.63793e+07 miss_ratio: 0.94661 max_rss_mb: 33.8633
13MB 1thread gt_clock -> kops/s: 0.519 io_bytes/op: 4.43316e+06 miss_ratio: 0.269379 max_rss_mb: 100.684
13MB 1thread new_clock -> kops/s: 0.176 io_bytes/op: 1.54148e+07 miss_ratio: 0.91545 max_rss_mb: 66.2383
13MB 32thread base -> kops/s: 3.266 io_bytes/op: 1.65544e+07 miss_ratio: 0.943386 max_rss_mb: 132.492
13MB 32thread folly -> kops/s: 3.396 io_bytes/op: 1.63142e+07 miss_ratio: 0.943243 max_rss_mb: 101.863
13MB 32thread gt_clock -> kops/s: 2.758 io_bytes/op: 5.13714e+06 miss_ratio: 0.310652 max_rss_mb: 396.121
13MB 32thread new_clock -> kops/s: 3.11 io_bytes/op: 1.23419e+07 miss_ratio: 0.708425 max_rss_mb: 321.758
13MB 128thread base -> kops/s: 2.31 io_bytes/op: 1.64823e+07 miss_ratio: 0.939543 max_rss_mb: 425.539
13MB 128thread folly -> kops/s: 2.339 io_bytes/op: 1.6242e+07 miss_ratio: 0.939966 max_rss_mb: 346.098
13MB 128thread gt_clock -> kops/s: 3.223 io_bytes/op: 5.76928e+06 miss_ratio: 0.345899 max_rss_mb: 1087.77
13MB 128thread new_clock -> kops/s: 2.984 io_bytes/op: 1.05341e+07 miss_ratio: 0.606198 max_rss_mb: 898.27
gt_clock is clearly blowing way past its memory budget for lower miss rates and best throughput. new_clock also seems to be exceeding budgets, and this warrants more investigation but is not the use case we are targeting with the new cache. With partitioned index+filter, the miss ratio is much better, and although still high enough that the eviction CPU time is definitely offsetting mutex contention:
13MB 1thread base -> kops/s: 16.326 io_bytes/op: 23743.9 miss_ratio: 0.205362 max_rss_mb: 65.2852
13MB 1thread folly -> kops/s: 15.574 io_bytes/op: 19415 miss_ratio: 0.184157 max_rss_mb: 56.3516
13MB 1thread gt_clock -> kops/s: 14.459 io_bytes/op: 22873 miss_ratio: 0.198355 max_rss_mb: 63.9688
13MB 1thread new_clock -> kops/s: 16.34 io_bytes/op: 24386.5 miss_ratio: 0.210512 max_rss_mb: 61.707
13MB 128thread base -> kops/s: 289.786 io_bytes/op: 23710.9 miss_ratio: 0.205056 max_rss_mb: 103.57
13MB 128thread folly -> kops/s: 185.282 io_bytes/op: 19433.1 miss_ratio: 0.184275 max_rss_mb: 116.219
13MB 128thread gt_clock -> kops/s: 354.451 io_bytes/op: 23150.6 miss_ratio: 0.200495 max_rss_mb: 102.871
13MB 128thread new_clock -> kops/s: 295.359 io_bytes/op: 24626.4 miss_ratio: 0.212452 max_rss_mb: 121.109
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10626
Test Plan: updated unit tests, stress/crash test runs including with TSAN, ASAN, UBSAN
Reviewed By: anand1976
Differential Revision: D39368406
Pulled By: pdillinger
fbshipit-source-id: 5afc44da4c656f8f751b44552bbf27bd3ca6fef9
2 years ago
|
|
|
size_t LRUCacheShard::GetOccupancyCount() const {
|
|
|
|
DMutexLock l(mutex_);
|
|
|
|
return table_.GetOccupancy();
|
|
|
|
}
|
|
|
|
|
|
|
|
size_t LRUCacheShard::GetTableAddressCount() const {
|
|
|
|
DMutexLock l(mutex_);
|
|
|
|
return table_.GetTableSize();
|
|
|
|
}
|
|
|
|
|
|
|
|
LRUCache::LRUCache(size_t capacity, size_t estimated_value_size,
|
|
|
|
int num_shard_bits, bool strict_capacity_limit,
|
|
|
|
CacheMetadataChargePolicy metadata_charge_policy)
|
|
|
|
: ShardedCache(capacity, num_shard_bits, strict_capacity_limit,
|
|
|
|
nullptr /*allocator*/) {
|
|
|
|
assert(estimated_value_size > 0 ||
|
|
|
|
metadata_charge_policy != kDontChargeCacheMetadata);
|
|
|
|
size_t per_shard = GetPerShardCapacity();
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InitShards([=](LRUCacheShard* cs) {
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new (cs) LRUCacheShard(per_shard, estimated_value_size,
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strict_capacity_limit, metadata_charge_policy);
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});
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}
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void* LRUCache::Value(Handle* handle) {
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return reinterpret_cast<const LRUHandle*>(handle)->value;
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}
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size_t LRUCache::GetCharge(Handle* handle) const {
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return reinterpret_cast<const LRUHandle*>(handle)->GetCharge(
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GetShard(0).metadata_charge_policy_);
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}
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Cache::DeleterFn LRUCache::GetDeleter(Handle* handle) const {
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auto h = reinterpret_cast<const LRUHandle*>(handle);
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return h->deleter;
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}
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} // namespace fast_lru_cache
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std::shared_ptr<Cache> NewFastLRUCache(
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size_t capacity, size_t estimated_value_size, int num_shard_bits,
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bool strict_capacity_limit,
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CacheMetadataChargePolicy metadata_charge_policy) {
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if (num_shard_bits >= 20) {
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return nullptr; // The cache cannot be sharded into too many fine pieces.
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}
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if (num_shard_bits < 0) {
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num_shard_bits = GetDefaultCacheShardBits(capacity);
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}
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return std::make_shared<fast_lru_cache::LRUCache>(
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capacity, estimated_value_size, num_shard_bits, strict_capacity_limit,
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metadata_charge_policy);
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}
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} // namespace ROCKSDB_NAMESPACE
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