Commit graph

83 commits

Author SHA1 Message Date
Peter Dillinger 54cb9c77d9 Prefer static_cast in place of most reinterpret_cast (#12308)
Summary:
The following are risks associated with pointer-to-pointer reinterpret_cast:
* Can produce the "wrong result" (crash or memory corruption). IIRC, in theory this can happen for any up-cast or down-cast for a non-standard-layout type, though in practice would only happen for multiple inheritance cases (where the base class pointer might be "inside" the derived object). We don't use multiple inheritance a lot, but we do.
* Can mask useful compiler errors upon code change, including converting between unrelated pointer types that you are expecting to be related, and converting between pointer and scalar types unintentionally.

I can only think of some obscure cases where static_cast could be troublesome when it compiles as a replacement:
* Going through `void*` could plausibly cause unnecessary or broken pointer arithmetic. Suppose we have
`struct Derived: public Base1, public Base2`.  If we have `Derived*` -> `void*` -> `Base2*` -> `Derived*` through reinterpret casts, this could plausibly work (though technical UB) assuming the `Base2*` is not dereferenced. Changing to static cast could introduce breaking pointer arithmetic.
* Unnecessary (but safe) pointer arithmetic could arise in a case like `Derived*` -> `Base2*` -> `Derived*` where before the Base2 pointer might not have been dereferenced. This could potentially affect performance.

With some light scripting, I tried replacing pointer-to-pointer reinterpret_casts with static_cast and kept the cases that still compile. Most occurrences of reinterpret_cast have successfully been changed (except for java/ and third-party/). 294 changed, 257 remain.

A couple of related interventions included here:
* Previously Cache::Handle was not actually derived from in the implementations and just used as a `void*` stand-in with reinterpret_cast. Now there is a relationship to allow static_cast. In theory, this could introduce pointer arithmetic (as described above) but is unlikely without multiple inheritance AND non-empty Cache::Handle.
* Remove some unnecessary casts to void* as this is allowed to be implicit (for better or worse).

Most of the remaining reinterpret_casts are for converting to/from raw bytes of objects. We could consider better idioms for these patterns in follow-up work.

I wish there were a way to implement a template variant of static_cast that would only compile if no pointer arithmetic is generated, but best I can tell, this is not possible. AFAIK the best you could do is a dynamic check that the void* conversion after the static cast is unchanged.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12308

Test Plan: existing tests, CI

Reviewed By: ltamasi

Differential Revision: D53204947

Pulled By: pdillinger

fbshipit-source-id: 9de23e618263b0d5b9820f4e15966876888a16e2
2024-02-07 10:44:11 -08:00
Peter Dillinger 88bc91f3cc Cap eviction effort (CPU under stress) in HyperClockCache (#12141)
Summary:
HyperClockCache is intended to mitigate performance problems under stress conditions (as well as optimizing average-case parallel performance). In LRUCache, the biggest such problem is lock contention when one or a small number of cache entries becomes particularly hot. Regardless of cache sharding, accesses to any particular cache entry are linearized against a single mutex, which is held while each access updates the LRU list.  All HCC variants are fully lock/wait-free for accessing blocks already in the cache, which fully mitigates this contention problem.

However, HCC (and CLOCK in general) can exhibit extremely degraded performance under a different stress condition: when no (or almost no) entries in a cache shard are evictable (they are pinned). Unlike LRU which can find any evictable entries immediately (at the cost of more coordination / synchronization on each access), CLOCK has to search for evictable entries. Under the right conditions (almost exclusively MB-scale caches not GB-scale), the CPU cost of each cache miss could fall off a cliff and bog down the whole system.

To effectively mitigate this problem (IMHO), I'm introducing a new default behavior and tuning parameter for HCC, `eviction_effort_cap`. See the comments on the new config parameter in the public API.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12141

Test Plan:
unit test included

 ## Performance test

We can use cache_bench to validate no regression (CPU and memory) in normal operation, and to measure change in behavior when cache is almost entirely pinned. (TODO: I'm not sure why I had to get the pinned ratio parameter well over 1.0 to see truly bad performance, but the behavior is there.) Build with `make DEBUG_LEVEL=0 USE_CLANG=1 PORTABLE=0 cache_bench`. We also set MALLOC_CONF="narenas:1" for all these runs to essentially remove jemalloc variances from the results, so that the max RSS given by /usr/bin/time is essentially ideal (assuming the allocator minimizes fragmentation and other memory overheads well). Base command reproducing bad behavior:

```
./cache_bench -cache_type=auto_hyper_clock_cache -threads=12 -histograms=0 -pinned_ratio=1.7
```

```
Before, LRU (alternate baseline not exhibiting bad behavior):
Rough parallel ops/sec = 2290997
1088060 maxresident

Before, AutoHCC (bad behavior):
Rough parallel ops/sec = 141011 <- Yes, more than 10x slower
1083932 maxresident
```

Now let us sample a range of values in the solution space:

```
After, AutoHCC, eviction_effort_cap = 1:
Rough parallel ops/sec = 3212586
2402216 maxresident

After, AutoHCC, eviction_effort_cap = 10:
Rough parallel ops/sec = 2371639
1248884 maxresident

After, AutoHCC, eviction_effort_cap = 30:
Rough parallel ops/sec = 1981092
1131596 maxresident

After, AutoHCC, eviction_effort_cap = 100:
Rough parallel ops/sec = 1446188
1090976 maxresident

After, AutoHCC, eviction_effort_cap = 1000:
Rough parallel ops/sec = 549568
1084064 maxresident
```

I looks like `cap=30` is a sweet spot balancing acceptable CPU and memory overheads, so is chosen as the default.

```
Change to -pinned_ratio=0.85
Before, LRU:
Rough parallel ops/sec = 2108373
1078232 maxresident

Before, AutoHCC, averaged over ~20 runs:
Rough parallel ops/sec = 2164910
1077312 maxresident

After, AutoHCC, eviction_effort_cap = 30, averaged over ~20 runs:
Rough parallel ops/sec = 2145542
1077216 maxresident
```

The slight CPU improvement above is consistent with the cap, with no measurable memory overhead under moderate stress.

```
Change to -pinned_ratio=0.25 (low stress)
Before, AutoHCC, averaged over ~20 runs:
Rough parallel ops/sec = 2221149
1076540 maxresident

After, AutoHCC, eviction_effort_cap = 30, averaged over ~20 runs:
Rough parallel ops/sec = 2224521
1076664 maxresident
```

No measurable difference under normal circumstances.

Some tests repeated with FixedHCC, with similar results.

Reviewed By: anand1976

Differential Revision: D52174755

Pulled By: pdillinger

fbshipit-source-id: d278108031b1220c1fa4c89c5a9d34b7cf4ef1b8
2023-12-14 22:13:32 -08:00
Peter Dillinger c74531b1d2 Fix a nuisance compiler warning from clang (#12144)
Summary:
Example:

```
cache/clock_cache.cc:56:7: error: fallthrough annotation in unreachable code [-Werror,-Wimplicit-fallthrough]
      FALLTHROUGH_INTENDED;
      ^
./port/lang.h:10:30: note: expanded from macro 'FALLTHROUGH_INTENDED'
                             ^
```

In clang < 14, this is annoyingly generated from -Wimplicit-fallthrough, but was changed to -Wunreachable-code-fallthrough (implied by -Wunreachable-code) in clang 14. See https://reviews.llvm.org/D107933 for how this nuisance pattern generated false positives similar to ours in the Linux kernel.

Just to underscore the ridiculousness of this warning, here an error is reported on the annotation, not the call to do_something(), depending on the constexpr value (https://godbolt.org/z/EvxqdPTdr):

```
#include <atomic>
void do_something();
void test(int v) {
    switch (v) {
        case 1:
            if constexpr (std::atomic<long>::is_always_lock_free) {
                return;
            } else {
                do_something();
                [[fallthrough]];
            }
        case 2:
            return;
    }
}
```

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12144

Test Plan: Added the warning to our Makefile for USE_CLANG, which reproduced the warning-as-error as shown above, but is now fixed.

Reviewed By: jaykorean

Differential Revision: D52139615

Pulled By: pdillinger

fbshipit-source-id: ba967ae700c0916d1a478bc465cf917633e337d9
2023-12-13 15:58:46 -08:00
Peter Dillinger 65cde19f40 Safer wrapper for std::atomic, use in HCC (#12051)
Summary:
See new atomic.h file comments for motivation.

I have updated HyperClockCache to use the new atomic wrapper, fixing a few cases where an implicit conversion was accidentally used and therefore mixing std::memory_order_seq_cst where release/acquire ordering (or relaxed) was intended. There probably wasn't a real bug because I think all the cases happened to be in single-threaded contexts like constructors/destructors or statistical ops like `GetCapacity()` that don't need any particular ordering constraints.

Recommended follow-up:
* Replace other uses of std::atomic to help keep them safe from bugs.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12051

Test Plan:
Did some local correctness stress testing with cache_bench. Also triggered 15 runs of fbcode_blackbox_crash_test and saw no related failures (just 3 failures in ~CacheWithSecondaryAdapter(), already known)

No performance difference seen before & after running simultaneously:
```
(while ./cache_bench -cache_type=fixed_hyper_clock_cache -populate_cache=0 -cache_size=3000000000 -ops_per_thread=500000 -threads=12 -histograms=0 2>&1 | grep parallel; do :; done) | awk '{ s += $3; c++; print "Avg time: " (s/c);}'
```

... for both fixed_hcc and auto_hcc.

Reviewed By: jowlyzhang

Differential Revision: D51090518

Pulled By: pdillinger

fbshipit-source-id: eeb324facb3185584603f9ea0c4de6f32919a2d7
2023-11-08 13:28:43 -08:00
Peter Dillinger 9af25a392b Clean up AutoHyperClockTable::PurgeImpl (#12052)
Summary:
There was some unncessary logic (e.g. a dead assignment to home_shift) left over from earlier revision of the code.

Also, rename confusing ChainRewriteLock::new_head_ / GetNewHead() to saved_head_ / GetSavedHead().

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12052

Test Plan: existing tests

Reviewed By: jowlyzhang

Differential Revision: D51091499

Pulled By: pdillinger

fbshipit-source-id: 4b191b60a2b16085681e59d49c4d97e802869db8
2023-11-07 16:35:19 -08:00
Peter Dillinger 16ae3548a2 AutoHCC: Improve/fix allocation/detection of grow homes (#12047)
Summary:
This change simplifies some code and logic by introducing a new atomic field that tracks the next slot to grow into. It should offer slightly better performance during the growth phase (not measurable; see Test Plan below) and fix a suspected (but unconfirmed) bug like this:
* Thread 1 is in non-trivial SplitForGrow() with grow_home=n.
* Thread 2 reaches Grow() with grow_home=2n, and waits at the start of SplitForGrow() for the rewrite lock on n. By this point, the head at 2n is marked with the new shift amount but no chain is locked.
* Thread 3 reaches Grow() with grow_home=4n, and waits before SplitForGrow() for the rewrite lock on n. By this point, the head at 4n is marked with the new shift amount but no chain is locked.
* Thread 4 reaches Grow() with grow_home=8n and meets no resistance to proceeding through a SplitForGrow() on an empty chain, permanently missing out on any entries from chain n that should have ended up here.

This is fixed by not updating the shift amount at the grow_home head until we have checked the preconditions that Grow()s feeding into this one have completed.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12047

Test Plan:
Some manual cache_bench stress runs, and about 20 triggered runs of fbcode_blackbox_crash_test

No discernible performance difference on this benchmark, running before & after in parallel for a few minutes:
```
(while ./cache_bench -cache_type=auto_hyper_clock_cache -populate_cache=0 -cache_size=3000000000 -ops_per_thread=50000 -threads=12 -histograms=0 2>&1 | grep parallel; do :; done) | awk '{ s += $3; c++; print "Avg time: " (s/c);}'
```

Reviewed By: jowlyzhang

Differential Revision: D51017007

Pulled By: pdillinger

fbshipit-source-id: 5f6d6a6194fc966f94693f3205ed75c87cdad269
2023-11-07 10:40:39 -08:00
Peter Dillinger 92dc5f3e67 AutoHCC: fix a bug with "blind" Insert (#12046)
Summary:
I have finally tracked down and fixed a bug affecting AutoHCC that was causing CI crash test assertion failures in AutoHCC when using secondary cache, but I was only able to reproduce locally a couple of times, after very long runs/repetitions.

It turns out that the essential feature used by secondary cache to trigger the bug is Insert without keeping a handle, which is otherwise rarely used in RocksDB and not incorporated into cache_bench (also used for targeted correctness stress testing) until this change (new option `-blind_insert_percent`).

The problem was in copying some logic from FixedHCC that makes the entry "sharable" but unreferenced once populated, if no reference is to be saved. The problem in AutoHCC is that we can only add the entry to a chain after it is in the sharable state, and must be removed from the chain while in the "under (de)construction" state and before it is back in the "empty" state. Also, it is possible for Lookup to find entries that are not connected to any chain, by design for efficiency, and for Release to erase_if_last_ref. Therefore, we could have
* Thread 1 starts to Insert a cache entry without keeping ref, and pauses before adding to the chain.
* Thread 2 finds it with Lookup optimizations, and then does Release with `erase_if_last_ref=true` causing it to trigger erasure on the entry. It successfully locks the home chain for the entry and purges any entries pending erasure. It is OK that this entry is not found on the chain, as another thread is allowed to remove it from the chain before we are able to (but after is it marked for (de)construction). And after the purge of the chain, the entry is marked empty.
* Thread 1 resumes in adding the slot (presumed entry) to the home chain for what was being inserted, but that now violates invariants and sets up a race or double-chain-reference as another thread could insert a new entry in the slot and try to insert into a different chain.

This is easily fixed by holding on to a reference until inserted onto the chain.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12046

Test Plan:
As I don't have a reliable local reproducer, I triggered 20 runs of internal CI on fbcode_blackbox_crash_test that were previously failing in AutoHCC with about 1/3 probability, and they all passed.

Also re-enabling AutoHCC in the crash test with this change. (Revert https://github.com/facebook/rocksdb/issues/12000)

Reviewed By: jowlyzhang

Differential Revision: D51016979

Pulled By: pdillinger

fbshipit-source-id: 3840fb829d65b97c779d8aed62a4a4a433aeff2b
2023-11-06 16:06:01 -08:00
Peter Dillinger ef0c3f08fa Fix rare destructor bug in AutoHCC (#11988)
Summary:
and some other small enhancements/fixes:
* The main bug fixed is that in some rare cases, the "published" table size might be smaller than the actual table size. This is a transient state that can happen with concurrent growth that is normally fixed after enough insertions, but if the cache is destroyed soon enough after growth, it could fail to fully destroy some entries and cause assertion failures. We can fix this by detecting the true table size in the destructor.
* Change the "too many iterations" debug threshold from 512 to 768. We might have hit at least one false positive failure. (Failed despite legitimate operation.)
* Added some stronger assertions in some places to aid in debugging.
* Use COERCE_CONTEXT_SWITCH to make behavior of Grow less predictable in terms of thread interleaving. (Might add in more places.) This was useful in reproducing the destructor bug.
* Fix some comments with typos or that were based on earlier revisions of the code.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11988

Test Plan:
Variants of this bug-finding command:
```
USE_CLANG=1 COMPILE_WITH_ASAN=1 COMPILE_WITH_UBSAN=1 COERCE_CONTEXT_SWITCH=1 DEBUG_LEVEL=2 make -j32 cache_bench && while ROCKSDB_DEBUG=1 ./cache_bench -cache_type=auto_hyper_clock_cache -histograms=0 -cache_size=80000000 -threads=32 -populate_cache=0 -ops_per_thread=1000 -num_shard_bits=0; do :; done
```

Reviewed By: jowlyzhang

Differential Revision: D50470318

Pulled By: pdillinger

fbshipit-source-id: d407a8bb0b6d2ddc598a954c319a1640136f12f2
2023-10-19 14:51:22 -07:00
Peter Dillinger dc576af0fd AutoHCC - fix a rare loop condition in Lookup (#11948)
Summary:
Saw this in stress test:
```
db_stress: cache/clock_cache.cc:3152:[...] Assertion `i < 0x2000' failed.
```

The problem is related to Lookups on a chain currently involved in a Grow operation. To avoid Lookup waiting on Grow, Lookup is able to walk a chain whose first part is already migrated and tail is not yet migrated, so is mixed with entries with a different destination home (according to `home_shift`) than what we're looking for. This is fine until we save one of these entries as a safe point in the chain to backtrack to (`read_ref_on_chain`) in case of concurrent modification and end up backtracking to it. In that case, we can get stuck on the wrong destination chain and keep trying to backtrack to an entry that is supposed to be on the correct chain but is not (anymore).

For some reason I haven't quite worked out, I believe it's usually able to recover after some 1000+ looop iterations, so reproducibility depends on the threshold at which we consider a Lookup loop to be too many iterations for a plausibly valid Lookup.

Detecting and working around this case is relatively simple. We can (and must) keep going on the chain but ensure we don't save it as a safe entry to backtrack to.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11948

Test Plan:
The problem could be reproduced in a few minutes with this (debug build):
```
$ while ./cache_bench -cache_type=auto_hyper_clock_cache -histograms=0 -cache_size=80000000 -threads=32 -populate_cache=0 -ops_per_thread=10000 -degenerate_hash_bits=6 -num_shard_bits=0; do :; done
```

At least with a lower threshold on suspiciously high number of iterations. I've lowered the thresholds quite a bit and no longer able to reproduce a failure.

Reviewed By: jowlyzhang

Differential Revision: D50236574

Pulled By: pdillinger

fbshipit-source-id: 2cb54a4e02bb51d5933eea41fcd489ab9d34aa96
2023-10-13 09:52:33 -07:00
Peter Dillinger 77a1d6eafb Fix assertion failure in AutoHCC (#11877)
Summary:
Example crash seen in crash test:

```
db_stress: cache/clock_cache.cc:237: bool rocksdb::clock_cache::{anonymous}::BeginSlotInsert(const rocksdb::clock_cache::ClockHandleBasicData&, rocksdb::clock_cache::ClockHandle&, uint64_t, bool*): Assertion `*already_matches == false' failed.
```

I was intentionally ignoring `already_matches` without resetting it to false for the next call.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11877

Test Plan:
Reproducer no longer reproduces:

```
while ./cache_bench -cache_type=auto_hyper_clock_cache -threads=32 -populate_cache=0 -histograms=0 -report_problems -insert_percent=87 -lookup_insert_percent=2 -skew=10 -ops_per_thread=100 -cache_size=1000000; do echo hi; done
```

Reviewed By: cbi42

Differential Revision: D49562065

Pulled By: pdillinger

fbshipit-source-id: 941062e6eac7a4b56157925b1cf2a0b15ff9cc9d
2023-09-22 16:42:52 -07:00
Peter Dillinger f6cb763409 Fix major performance bug in AutoHCC growth phase (#11871)
Summary:
## The Problem
Mark Callaghan found a performance bug in yet-unreleased AutoHCC (which should have been found in my own testing). The observed behavior is very slow insertion performance as the table is growing into a very large structure. The root cause is the precarious combination of linear hashing (indexing into the table while allowing growth) and linear probing (for finding an empty slot to insert into). Naively combined, this is a disaster because in linear hashing, part of the table is twice as dense as first probing location as the rest. Thus, even a modest load factor like 0.6 could cause the dense part of the table to degrade to linear search. The code had a correction for this imbalance, which works in steady-state operation, but failed to account for the concentrating effect of table growth. Specifically, newly-added slots were underpopulated which allowed old slots to become over-populated and degrade to linear search, even in single-threaded operation. Here's an example:

```
./cache_bench -cache_type=auto_hyper_clock_cache -threads=1 -populate_cache=0 -value_bytes=500 -cache_size=3000000000 -histograms=0 -report_problems -ops_per_thread=20000000 -resident_ratio=0.6
```
AutoHCC: Complete in 774.213 s; Rough parallel ops/sec = 25832
FixedHCC: Complete in 19.630 s; Rough parallel ops/sec = 1018840
LRUCache: Complete in 25.842 s; Rough parallel ops/sec = 773947

## The Fix
One small change is apparently sufficient to fix the problem, but I wanted to re-optimize the whole "finding a good empty slot" algorithm to improve safety margins for good performance and to improve typical case performance.

The small change is to track the newly-added slot from Grow in Insert, when applicable, and use that slot for insertion if (a) the home slot is already occupied, and (b) the newly-added slot is empty. This appears to sufficiently load new slots while avoiding over-population of either old or new slots. See `likely_empty_slot`.

However I've also made the logic much more resilient to parts of the table becoming over-populated. I tested a variant that used double hashing instead of linear probing and found that hurt steady-state average-case performance, presumably due to loss of locality in the chains. And even conventional double hashing might not be ideally robust against density skew in the table (still present because of home location bias), because double hashing might choose a small increment that could take a long time to iterate to the under-populated part of the table.

The compromise that seems to bring the best of each approach is this: do linear probing (+1 at a time) within a small bound (chosen bound of 4 based on performance testing) and then fall back on a double-hashing variant if no slot has been found. The double-hashing variant uses a probing increment that is always close to the golden ratio, relative to the table size, so that any under-populated regions of the table can be found relatively quickly, without introducing any additional skew. And the increment is varied slightly to avoid clustering effects that could happen with a fixed increment (regardless of how big it is).

And that leaves us with one remaining problem: the double hashing increment might not be relatively prime to the table size, so the probing sequence might be a cycle that does not cover the full set of slots. To solve this we can use a technique I developed many years ago (probably also developed by others) that simply adds one (in modular arithmetic) whenever we finish a (potentially incomplete) cycle. This is a simple and reasonably efficient way to iterate over all the slots without repetition, regardless of whether the increment is not relatively prime to the table size, or even zero.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11871

Test Plan:
existing correctness tests, especially ClockCacheTest.ClockTableFull

Intended follow-up: make ClockTableFull test more complete for AutoHCC

## Performance
Ignoring old AutoHCC performance, as we established above it could be terrible. FixedHCC and LRUCache are unaffected by this change. All tests below include this change.

### Getting up to size, single thread
(same cache_bench command as above, all three run at same time)

AutoHCC: Complete in 26.724 s; Rough parallel ops/sec = 748400
FixedHCC: Complete in 19.987 s; Rough parallel ops/sec = 1000631
LRUCache: Complete in 28.291 s; Rough parallel ops/sec = 706939

Single-threaded faster than LRUCache (often / sometimes) is good. FixedHCC has an obvious advantage because it starts at full size.

### Multiple threads, steady state, high hit rate ~95%
Using `-threads=10 -populate_cache=1 -ops_per_thread=10000000` and still `-resident_ratio=0.6`

AutoHCC: Complete in 48.778 s; Rough parallel ops/sec = 2050119
FixedHCC: Complete in 46.569 s; Rough parallel ops/sec = 2147329
LRUCache: Complete in 50.537 s; Rough parallel ops/sec = 1978735

### Multiple threads, steady state, low hit rate ~50%
Change to `-resident_ratio=0.2`

AutoHCC: Complete in 49.264 s; Rough parallel ops/sec = 2029884
FixedHCC: Complete in 49.750 s; Rough parallel ops/sec = 2010041
LRUCache: Complete in 53.002 s; Rough parallel ops/sec = 1886713

Don't expect AutoHCC to be consistently faster than FixedHCC, but they are at least similar in these benchmarks.

Reviewed By: jowlyzhang

Differential Revision: D49548534

Pulled By: pdillinger

fbshipit-source-id: 263e4f4d71d0e9a7d91db3795b48fad75408822b
2023-09-22 13:47:31 -07:00
Peter Dillinger e67ee46642 Suppress TSAN reports on AutoHyperClockTable::Lookup (#11806)
Summary:
This function uses racing reads for heuristic performance improvement. My change in https://github.com/facebook/rocksdb/issues/11792 only worked for clang, not gcc, and gcc does not accurately handle TSAN suppressions. I would have to mark much more code as suppressed than I want to.

So I've taken a different approach: TSAN build does not use the racing reads but substitutes random results, as an extra test that a "correct" value is not needed for correct overall behavior.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11806

Test Plan: manual TSAN builds & tests with cache_bench

Reviewed By: ajkr

Differential Revision: D49100115

Pulled By: pdillinger

fbshipit-source-id: d6d0dfb796d710b953212dd3fc171b6e88fadea1
2023-09-08 10:50:47 -07:00
Peter Dillinger d01b1215bd Fix TSAN reports on AutoHCC (#11792)
Summary:
Forgot to run TSAN test on latest revision of https://github.com/facebook/rocksdb/issues/11738

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11792

Test Plan: Use cache_bench to reproduce TSAN errors and observe fix

Reviewed By: ajkr

Differential Revision: D48953196

Pulled By: pdillinger

fbshipit-source-id: 9e358b4768d8ddde86f84b451863263f661d7b80
2023-09-04 10:59:16 -07:00
Peter Dillinger fe3405e80f Automatic table sizing for HyperClockCache (AutoHCC) (#11738)
Summary:
This change add an experimental next-generation HyperClockCache (HCC) with automatic sizing of the underlying hash table. Both the existing version (stable) and the new version (experimental for now) of HCC are available depending on whether an estimated average entry charge is provided in HyperClockCacheOptions.

Internally, we call the two implementations AutoHyperClockCache (new) and FixedHyperClockCache (existing). The performance characteristics and much of the underlying logic are similar enough that AutoHCC is likely to make FixedHCC obsolete, and so it's best considered an evolution of the same technology or solution rather than an alternative. More specifically, both implementations share essentially the same logic for managing the state of individual entries in the cache, including metadata for reference counting and counting clocks for eviction. This metadata, which I like to call the "low-level HCC protocol," includes a read-write lock on entries, but relaxed consistency requirements on the cache (e.g. allowing rare duplication) means high-level cache operations never wait for these low-level per-entry locks. FixedHCC is fully wait-free.

AutoHCC is different in how entries are indexed into an efficient hash table. AutoHCC is "essentially wait-free" as there is no pattern of typical high-level operations on a large cache that can lead to one thread waiting on another to complete some work, though it can happen in some unusual/unlucky cases, or atypical uses such as erasing specific cache keys. Table growth and entry reclamation is more complex in AutoHCC compared to FixedHCC, so uses some localized locking to manage that. AutoHCC uses linear hashing to grow the table as needed, with low latency and to a precise size. AutoHCC depends on anonymous mmap support from the OS (currently verified working on Linux, MacOS, and Windows) to allow the array underlying a hash table to grow in place without wasting resident memory on space reserved but unused. AutoHCC uses a form of chaining while FixedHCC uses open addressing and double hashing.

More specifics:
* In developing this PR, a rare availability bug (minor) was noticed in the existing HCC implementation of Release()+erase_if_last_ref, which is now inherited into AutoHCC. Fixing this without a performance regression will not be simple, so is left for follow-up work.
* Some existing unit tests required adjustment of operational parameters or conditions to work with the new behaviors of AutoHCC. A number of bugs were found and fixed in the validation process, including getting unit tests in good working order.
* Added an option to cache_bench, `-degenerate_hash_bits` for correctness stress testing described below. For this, the tool uses the reverse-engineered hash function for HCC to generate keys in which the specified number of hash bits, in critical positions, have a fixed value. Essentially each degenerate hash bit will half the number of chain heads utilized and double the average chain length.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11738

Test Plan:
unit tests updated, and already added to db crash test. Also

## Correctness
The code includes generous assertions to check for unexpected states, especially at destruction time, so should be able to detect critical concurrency bugs. Less serious "availability bugs" in which cache data is hidden or cleanly lost are more difficult to detect, but also less scary for data correctness (as long as performance is good and the design is sound).

In average operation, the structure is extremely low stress and low contention (see next section) so stressing the corner case logic requires artificially stressing the operating conditions. First, we keep the structure small to increase the number of threads hitting the same chain or entry, and just one cache shard. Second, we artificially degrade the hashing so that chains are much longer than typical, using the new `-degenerate_hash_bits` option to cache_bench. Third, we re-create the structure from scratch frequently in order to exercise the Grow logic repeatedly and to get the benefit of the consistency checks in the structure's destructor in debug builds. For cache_bench this also means disabling the single-threaded "populate cache" step (normally used for steady state performance testing). And of course use many more threads than cores to have many preemptions.

An effective test for working out bugs was this (using debug build of course):
```
while ./cache_bench -cache_type=auto_hyper_clock_cache -histograms=0 -cache_size=8000000 -threads=100 -populate_cache=0 -ops_per_thread=10000 -degenerate_hash_bits=6 -num_shard_bits=0; do :; done
```

Or even smaller cases. This setup has around 27 utilized chains, with around 35 entries each, and yield-waits more than 1 million times per second (very high contention; see next section). I have let this run for hours searching for any lingering issues.

I've also run cache_bench under ASAN, UBSAN, and TSAN.

## Essentially wait free
There is a counter for number of yield() calls when one thread is waiting on another. When we pre-populate the structure in a single thread,
```
./cache_bench -cache_type=auto_hyper_clock_cache -histograms=0 -populate_cache=1 -ops_per_thread=200000 2>&1 | grep Yield
```
We see something on the order of 1 yield call per second across 16 threads, even when we load the system other other jobs (parallel compilation). With -populate_cache=0, there are more yield opportunities with parallel table growth. On an otherwise unloaded system, we still see very small (single digit) yield counts, with a chance of getting into the thousands, and getting into 10s of thousands per second during table growth phase if the system is loaded with other jobs. However, I am not worried about this if performance is still good (see next section).

## Overall performance
Although cache_bench initially suggested performance very close to FixedHCC, there was a very noticeable performance hit under a db_bench setup like used in validating https://github.com/facebook/rocksdb/issues/10626. Much of the difference has been reduced by optimizing Lookup with a "naive" pass that will almost always find entries quickly, and only falling back to the careful Lookup algorithm when not found in the first pass.

Setups (chosen to be sensitive to block cache performance), and compiled with USE_CLANG=1 JEMALLOC=1 PORTABLE=0 DEBUG_LEVEL=0:
```
TEST_TMPDIR=/dev/shm base/db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16
```

### No regression on FixedHCC
Running before & after builds at the same time on a 48 core machine.
```
TEST_TMPDIR=/dev/shm /usr/bin/time ./db_bench -benchmarks=readrandom[-X10],block_cache_entry_stats,cache_report_problems -readonly -num=30000000 -bloom_bits=16 -cache_index_and_filter_blocks=1 -cache_size=610000000 -duration 20 -threads=24 -cache_type=fixed_hyper_clock_cache -seed=1234
```

Before:
readrandom [AVG    10 runs] : 847234 (± 8150) ops/sec;   59.2 (± 0.6) MB/sec
703MB max RSS

After:
readrandom [AVG    10 runs] : 851021 (± 7929) ops/sec;   59.5 (± 0.6) MB/sec
706MB max RSS

Probably no material difference.

### Single-threaded performance
Using `[-X2]` and `-threads=1` and `-duration=30`, running all three at the same time:

lru_cache: 55100 ops/sec, then 55862 ops/sec  (627MB max RSS)
fixed_hyper_clock_cache: 60496 ops/sec, then 61231 ops/sec (626MB max RSS)
auto_hyper_clock_cache: 47560 ops/sec, then 56081 ops/sec (626MB max RSS)

So AutoHCC has more ramp-up cost in the first pass as the cache grows to the appropriate size. (In single-threaded operation, the parallelizability and per-op low latency of table growth is overall slower.) However, once up to size, its performance is comparable to LRUCache. FixedHCC's lean operations still win overall when a good estimate is available.

If we look at HCC table stats, we can see that this configuration is not favorable to AutoHCC (and I have verified that other memory sizes do not yield substantially different results, until shards are under-sized for the full filters):

FixedHCC:
Slot occupancy stats: Overall 47% (124991/262144), Min/Max/Window = 28%/64%/500, MaxRun{Pos/Neg} = 17/22

AutoHCC:
Slot occupancy stats: Overall 59% (125781/209682), Min/Max/Window = 43%/82%/500, MaxRun{Pos/Neg} = 76/16
Head occupancy stats: Overall 43% (92259/209682), Min/Max/Window = 24%/74%/500, MaxRun{Pos/Neg} = 19/26
Entries at home count: 53350

FixedHCC configuration is relatively good for speed, and not ideal for space utilization. As is typical, AutoHCC has tighter control on metadata usage (209682 x 64 bytes rather than 262144 x 64 bytes), and the higher load factor is slightly worse for speed. LRUCache also has more metadata usage, at 199680 x 96 bytes of tracked metadata (plus roughly another 10% of that untracked in the head pointers), and that metadata is subject to fragmentation.

### Parallel performance, high hit rate
Now using `[-X10]` and `-threads=10`, all three at the same time

lru_cache: [AVG    10 runs] : 263629 (± 1425) ops/sec;   18.4 (± 0.1) MB/sec
655MB max RSS, 97.1% cache hit rate
fixed_hyper_clock_cache: [AVG    10 runs] : 479590 (± 8114) ops/sec;   33.5 (± 0.6) MB/sec
651MB max RSS, 97.1% cache hit rate
auto_hyper_clock_cache: [AVG    10 runs] : 418687 (± 5915) ops/sec;   29.3 (± 0.4) MB/sec
657MB max RSS, 97.1% cache hit rate

Even with just 10-way parallelism for each cache (though 30+/48 cores busy overall), LRUCache is already showing performance degradation, while AutoHCC is in the neighborhood of FixedHCC. And that brings us to the question of how AutoHCC holds up under extreme parallelism, so now independent runs with `-threads=100` (overloading 48 cores).

lru_cache: 438613 ops/sec, 827MB max RSS
fixed_hyper_clock_cache: 1651310 ops/sec, 812MB max RSS
auto_hyper_clock_cache: 1505875 ops/sec, 821MB max RSS (Yield count: 1089 over 30s)

Clearly, AutoHCC holds up extremely well under extreme parallelism, even closing some of the modest performance gap with  FixedHCC.

### Parallel performance, low hit rate
To get down to roughly 50% cache hit rate, we use `-cache_index_and_filter_blocks=0 -cache_size=1650000000` with `-threads=10`. Here the extra cost of running counting clock eviction, especially on the chains of AutoHCC, are evident, especially with the lower contention of cache_index_and_filter_blocks=0:

lru_cache: 725231 ops/sec, 1770MB max RSS, 51.3% hit rate
fixed_hyper_clock_cache: 638620 ops/sec, 1765MB max RSS, 50.2% hit rate
auto_hyper_clock_cache: 541018 ops/sec, 1777MB max RSS, 50.8% hit rate

Reviewed By: jowlyzhang

Differential Revision: D48784755

Pulled By: pdillinger

fbshipit-source-id: e79813dc087474ac427637dd282a14fa3011a6e4
2023-09-01 15:44:38 -07:00
anand76 a1743e85be Implement a allow cache hits admission policy for the compressed secondary cache (#11713)
Summary:
This PR implements a new admission policy for the compressed secondary cache, which includes the functionality of the existing policy, and also admits items evicted from the primary block cache with the hit bit set. Effectively, the new policy works as follows -
1. When an item is demoted from the primary cache without a hit, a placeholder is inserted in the compressed cache. A second demotion will insert the full entry.
2. When an item is promoted from the compressed cache to the primary cache for the first time, a placeholder is inserted in the primary. The second promotion inserts the full entry, while erasing it form the compressed cache.
3. If an item is demoted from the primary cache with the hit bit set, it is immediately inserted in the compressed secondary cache.
The ```TieredVolatileCacheOptions``` has been updated with a new option, ```adm_policy```, which allows the policy to be selected.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11713

Reviewed By: pdillinger

Differential Revision: D48444512

Pulled By: anand1976

fbshipit-source-id: b4cbf8c169a88097dff08e36e8bc4b3088de1492
2023-08-18 11:19:48 -07:00
Peter Dillinger ef6f025563 Placeholder for AutoHyperClockCache, more (#11692)
Summary:
* The plan is for AutoHyperClockCache to be selected when HyperClockCacheOptions::estimated_entry_charge == 0, and in that case to use a new configuration option min_avg_entry_charge for determining an extreme case maximum size for the hash table. For the placeholder, a hack is in place in HyperClockCacheOptions::MakeSharedCache() to make the unit tests happy despite the new options not really making sense with the current implementation.
* Mostly updating and refactoring tests to test both the current HCC (internal name FixedHyperClockCache) and a placeholder for the new version (internal name AutoHyperClockCache).
* Simplify some existing tests not to depend directly on cache type.
* Type-parameterize the shard-level unit tests, which unfortunately requires more syntax like `this->` in places for disambiguation.
* Added means of choosing auto_hyper_clock_cache to cache_bench, db_bench, and db_stress, including add to crash test.
* Add another templated class BaseHyperClockCache to reduce future copy-paste
* Added ReportProblems support to cache_bench
* Added a DEBUG-level diagnostic to ReportProblems for the variance in load factor throughout the table, which will become more of a concern with linear hashing to be used in the Auto implementation. Example with current Fixed HCC:
```
2023/08/10-13:41:41.602450 6ac36 [DEBUG] [che/clock_cache.cc:1507] Slot occupancy stats: Overall 49% (129008/262144), Min/Max/Window = 39%/60%/500, MaxRun{Pos/Neg} = 18/17
```

In other words, with overall occupancy of 49%, the lowest across any 500 contiguous cells is 39% and highest 60%. Longest run of occupied is 18 and longest run of unoccupied is 17. This seems consistent with random samples from a uniform distribution.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11692

Test Plan: Shouldn't be any meaningful changes yet to production code or to what is tested, but there is temporary redundancy in testing until the new implementation is plugged in.

Reviewed By: jowlyzhang

Differential Revision: D48247413

Pulled By: pdillinger

fbshipit-source-id: 11541f996d97af403c2e43c92fb67ff22dd0b5da
2023-08-11 16:27:38 -07:00
Peter Dillinger 99daea3481 Prepare tests for new HCC naming (#11676)
Summary:
I'm anticipating using the public name HyperClockCache for both the current version with a fixed-size table and the upcoming version with an automatically growing table. However, for simplicity of testing them as substantially distinct implementations, I want to give them distinct internal names, like FixedHyperClockCache and AutoHyperClockCache.

This change anticipates that by renaming to FixedHyperClockCache and assuming for now that all the unit tests run on HCC will run and behave similarly for the automatic HCC. Obviously updates will need to be made, but I'm trying to avoid uninteresting find & replace updates in what will be a large and engineering-heavy PR for AutoHCC

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11676

Test Plan: no behavior change intended, except logging will now use the name FixedHyperClockCache

Reviewed By: ajkr

Differential Revision: D48103165

Pulled By: pdillinger

fbshipit-source-id: a33f1901488fea102164c2318e2f2b156aaba736
2023-08-07 18:17:12 -07:00
Peter Dillinger cdb11f5ce6 More minor HCC refactoring + typed mmap (#11670)
Summary:
More code leading up to dynamic HCC.
* Small enhancements to cache_bench
* Extra assertion in Unref
* Improve a CAS loop in ChargeUsageMaybeEvictStrict
* Put load factor constants in appropriate class
* Move `standalone` field to HyperClockTable::HandleImpl because it can be encoded differently in the upcoming dynamic HCC.
* Add a typed version of MemMapping to simplify some future code.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11670

Test Plan: existing tests, unit test added for TypedMemMapping

Reviewed By: jowlyzhang

Differential Revision: D48056464

Pulled By: pdillinger

fbshipit-source-id: 186b7d3105c5d6d2eb6a592369bc10a97ee14a15
2023-08-07 12:20:23 -07:00
Peter Dillinger c41122b1a0 Even more HyperClockCache refactoring (#11630)
Summary:
... ahead of dynamic variant.

* Introduce an Unref function for a common pattern. Cases that were previously using std::memory_order_acq_rel we doing so because we were saving the pre-updated value in case it might be used. Now we are explicitly throwing away the pre-updated value so do not need the acquire semantic, just release.
* Introduce a reusable EvictionData struct and TrackAndReleaseEvictedEntry() function.
* Based on a linter suggesting, use const Func& parameter type instead of Func for templated callable parameters.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11630

Test Plan: existing tests, and performance test with release build of cache_bench. Getting 1-2% difference between before & after from run to run, but inconsistent about which one is faster.

Reviewed By: jowlyzhang

Differential Revision: D47657334

Pulled By: pdillinger

fbshipit-source-id: 5cf2377c0d47a39143b04be6735f98c550e8bdc3
2023-07-24 09:36:09 -07:00
Peter Dillinger 846db9d7b1 Refactor ClockCache ApplyToEntries (#11609)
Summary:
... ahead of planned dynamic HCC variant. This changes
simplifies some logic while still enabling future code sharing between
implementation variants.

Detail: For complicated reasons, using a std::function parameter to
`ConstApplyToEntriesRange` with a lambda argument does not play
nice with templated HandleImpl. An explicit conversion to std::function
would be needed for it to compile. Templating the function type is the
easy work-around.

Also made some functions from https://github.com/facebook/rocksdb/issues/11572 private as recommended

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11609

Test Plan: existing tests

Reviewed By: jowlyzhang

Differential Revision: D47407415

Pulled By: pdillinger

fbshipit-source-id: 0f65954db16335999b78fb7d2563ec627624cef0
2023-07-18 12:09:27 -07:00
Peter Dillinger b1b6f87fbe Some small improvements to HyperClockCache (#11601)
Summary:
Stacked on https://github.com/facebook/rocksdb/issues/11572
* Minimize use of std::function and lambdas to minimize chances of
compiler heap-allocating closures (unnecessary stress on allocator). It
appears that converting FindSlot to a template enables inlining the
lambda parameters, avoiding heap allocations.
* Clean up some logic with FindSlot (FIXMEs from https://github.com/facebook/rocksdb/issues/11572)
* Fix handling of rare case of probing all slots, with new unit test.
(Previously Insert would not roll back displacements in that case, which
would kill performance if it were to happen.)
* Add an -early_exit option to cache_bench for gathering memory stats
before deallocation.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11601

Test Plan:
unit test added for probing all slots

## Seeing heap allocations
Run `MALLOC_CONF="stats_print:true" ./cache_bench -cache_type=hyper_clock_cache`
before https://github.com/facebook/rocksdb/issues/11572 vs. after this change. Before, we see this in the
interesting bin statistics:

```
size  nrequests
----  ---------
  32     578460
  64      24340
8192     578460
```
And after:
```
size  nrequests
----  ---------
  32  (insignificant)
  64      24370
8192     579130
```

## Performance test
Build with `make USE_CLANG=1 PORTABLE=0 DEBUG_LEVEL=0 -j32 cache_bench`

Run `./cache_bench -cache_type=hyper_clock_cache -ops_per_thread=5000000`
in before and after configurations, simultaneously:

```
Before: Complete in 33.244 s; Rough parallel ops/sec = 2406442
After:  Complete in 32.773 s; Rough parallel ops/sec = 2441019
```

Reviewed By: jowlyzhang

Differential Revision: D47375092

Pulled By: pdillinger

fbshipit-source-id: 46f0f57257ddb374290a0a38c651764ea60ba410
2023-07-14 16:19:22 -07:00
Peter Dillinger c3c84b3397 Refactor (Hyper)ClockCache code for upcoming changes (#11572)
Summary:
Separate out some functionality that will be common to both static and dynamic HCC into BaseClockTable. Table::InsertState and GrowIfNeeded will be used by the dynamic HCC so don't make much sense right now.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11572

Test Plan:
existing tests. No functional changes intended.

Performance test in subsequent PR https://github.com/facebook/rocksdb/issues/11601

Reviewed By: jowlyzhang

Differential Revision: D47110496

Pulled By: pdillinger

fbshipit-source-id: 379bd433322a42ea28c0043b41ec24956d21e7aa
2023-07-12 14:05:34 -07:00
Peter Dillinger 206fdea3d9 Change internal headers with duplicate names (#11408)
Summary:
In IDE navigation I find it annoying that there are two statistics.h files (etc.) and often land on the wrong one. Here I migrate several headers to use the blah.h <- blah_impl.h <- blah.cc idiom. Although clang-format wants "blah.h" to be the top include for "blah.cc", I think overall this is an improvement.

No public API changes.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11408

Test Plan: existing tests

Reviewed By: ltamasi

Differential Revision: D45456696

Pulled By: pdillinger

fbshipit-source-id: 809d931253f3272c908cf5facf7e1d32fc507373
2023-05-17 11:27:09 -07:00
Peter Dillinger f4a02f2c52 Add hash_seed to Caches (#11391)
Summary:
See motivation and description in new ShardedCacheOptions::hash_seed option.

Updated db_bench so that its seed param is used for the cache hash seed.
Made its code more safe to ensure seed is set before use.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11391

Test Plan:
unit tests added / updated

**Performance** - no discernible difference seen running cache_bench repeatedly before & after. With lru_cache and hyper_clock_cache.

Reviewed By: hx235

Differential Revision: D45557797

Pulled By: pdillinger

fbshipit-source-id: 40bf4da6d66f9d41a8a0eb8e5cf4246a4aa07934
2023-05-09 22:24:26 -07:00
Peter Dillinger 41a7fbf758 Avoid long parameter lists configuring Caches (#11386)
Summary:
For better clarity, encouraging more options explicitly specified using fields rather than positionally via constructor parameter lists. Simplifies code maintenance as new fields are added. Deprecate some cases of the confusing pattern of NewWhatever() functions returning shared_ptr.

Net reduction of about 70 source code lines (including comments).

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11386

Test Plan: existing tests

Reviewed By: ajkr

Differential Revision: D45059075

Pulled By: pdillinger

fbshipit-source-id: d53fa09b268024f9c55254bb973b6c69feebf41a
2023-05-01 14:52:01 -07:00
Peter Dillinger 204fcff751 HyperClockCache support for SecondaryCache, with refactoring (#11301)
Summary:
Internally refactors SecondaryCache integration out of LRUCache specifically and into a wrapper/adapter class that works with various Cache implementations. Notably, this relies on separating the notion of async lookup handles from other cache handles, so that HyperClockCache doesn't have to deal with the problem of allocating handles from the hash table for lookups that might fail anyway, and might be on the same key without support for coalescing. (LRUCache's hash table can incorporate previously allocated handles thanks to its pointer indirection.) Specifically, I'm worried about the case in which hundreds of threads try to access the same block and probing in the hash table degrades to linear search on the pile of entries with the same key.

This change is a big step in the direction of supporting stacked SecondaryCaches, but there are obstacles to completing that. Especially, there is no SecondaryCache hook for evictions to pass from one to the next. It has been proposed that evictions be transmitted simply as the persisted data (as in SaveToCallback), but given the current structure provided by the CacheItemHelpers, that would require an extra copy of the block data, because there's intentionally no way to ask for a contiguous Slice of the data (to allow for flexibility in storage). `AsyncLookupHandle` and the re-worked `WaitAll()` should be essentially prepared for stacked SecondaryCaches, but several "TODO with stacked secondaries" issues remain in various places.

It could be argued that the stacking instead be done as a SecondaryCache adapter that wraps two (or more) SecondaryCaches, but at least with the current API that would require an extra heap allocation on SecondaryCache Lookup for a wrapper SecondaryCacheResultHandle that can transfer a Lookup between secondaries. We could also consider trying to unify the Cache and SecondaryCache APIs, though that might be difficult if `AsyncLookupHandle` is kept a fixed struct.

## cache.h (public API)
Moves `secondary_cache` option from LRUCacheOptions to ShardedCacheOptions so that it is applicable to HyperClockCache.

## advanced_cache.h (advanced public API)
* Add `Cache::CreateStandalone()` so that the SecondaryCache support wrapper can use it.
* Add `SetEvictionCallback()` / `eviction_callback_` so that the SecondaryCache support wrapper can use it. Only a single callback is supported for efficiency. If there is ever a need for more than one, hopefully that can be handled with a broadcast callback wrapper.

These are essentially the two "extra" pieces of `Cache` for pulling out specific SecondaryCache support from the `Cache` implementation. I think it's a good trade-off as these are reasonable, limited, and reusable "cut points" into the `Cache` implementations.

* Remove async capability from standard `Lookup()` (getting rid of awkward restrictions on pending Handles) and add `AsyncLookupHandle` and `StartAsyncLookup()`. As noted in the comments, the full struct of `AsyncLookupHandle` is exposed so that it can be stack allocated, for efficiency, though more data is being copied around than before, which could impact performance. (Lookup info -> AsyncLookupHandle -> Handle vs. Lookup info -> Handle)

I could foresee a future in which a Cache internally saves a pointer to the AsyncLookupHandle, which means it's dangerous to allow it to be copyable or even movable. It also means it's not compatible with std::vector (which I don't like requiring as an API parameter anyway), so `WaitAll()` expects any contiguous array of AsyncLookupHandles. I believe this is best for common case efficiency, while behaving well in other cases also. For example, `WaitAll()` has no effect on default-constructed AsyncLookupHandles, which look like a completed cache miss.

## cacheable_entry.h
A couple of functions are obsolete because Cache::Handle can no longer be pending.

## cache.cc
Provides default implementations for new or revamped Cache functions, especially appropriate for non-blocking caches.

## secondary_cache_adapter.{h,cc}
The full details of the Cache wrapper adding SecondaryCache support. Essentially replicates the SecondaryCache handling that was in LRUCache, but obviously refactored. There is a bit of logic duplication, where Lookup() is essentially a manually optimized version of StartAsyncLookup() and Wait(), but it's roughly a dozen lines of code.

## sharded_cache.h, typed_cache.h, charged_cache.{h,cc}, sim_cache.cc
Simply updated for Cache API changes.

## lru_cache.{h,cc}
Carefully remove SecondaryCache logic, implement `CreateStandalone` and eviction handler functionality.

## clock_cache.{h,cc}
Expose existing `CreateStandalone` functionality, add eviction handler functionality. Light refactoring.

## block_based_table_reader*
Mostly re-worked the only usage of async Lookup, which is in BlockBasedTable::MultiGet. Used arrays in place of autovector in some places for efficiency. Simplified some logic by not trying to process some cache results before they're all ready.

Created new function `BlockBasedTable::GetCachePriority()` to reduce some pre-existing code duplication (and avoid making it worse).

Fixed at least one small bug from the prior confusing mixture of async and sync Lookups. In MaybeReadBlockAndLoadToCache(), called by RetrieveBlock(), called by MultiGet() with wait=false, is_cache_hit for the block_cache_tracer entry would not be set to true if the handle was pending after Lookup and before Wait.

## Intended follow-up work
* Figure out if there are any missing stats or block_cache_tracer work in refactored BlockBasedTable::MultiGet
* Stacked secondary caches (see above discussion)
* See if we can make up for the small MultiGet performance regression.
* Study more performance with SecondaryCache
* Items evicted from over-full LRUCache in Release were not being demoted to SecondaryCache, and still aren't to minimize unit test churn. Ideally they would be demoted, but it's an exceptional case so not a big deal.
* Use CreateStandalone for cache reservations (save unnecessary hash table operations). Not a big deal, but worthy cleanup.
* Somehow I got the contract for SecondaryCache::Insert wrong in #10945. (Doesn't take ownership!) That API comment needs to be fixed, but didn't want to mingle that in here.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11301

Test Plan:
## Unit tests
Generally updated to include HCC in SecondaryCache tests, though HyperClockCache has some different, less strict behaviors that leads to some tests not really being set up to work with it. Some of the tests remain disabled with it, but I think we have good coverage without them.

## Crash/stress test
Updated to use the new combination.

## Performance
First, let's check for regression on caches without secondary cache configured. Adding support for the eviction callback is likely to have a tiny effect, but it shouldn't be worrisome. LRUCache could benefit slightly from less logic around SecondaryCache handling. We can test with cache_bench default settings, built with DEBUG_LEVEL=0 and PORTABLE=0.

```
(while :; do base/cache_bench --cache_type=hyper_clock_cache | grep Rough; done) | awk '{ sum += $9; count++; print $0; print "Average: " int(sum / count) }'
```

**Before** this and #11299 (which could also have a small effect), running for about an hour, before & after running concurrently for each cache type:
HyperClockCache: 3168662 (average parallel ops/sec)
LRUCache: 2940127

**After** this and #11299, running for about an hour:
HyperClockCache: 3164862 (average parallel ops/sec) (0.12% slower)
LRUCache: 2940928 (0.03% faster)

This is an acceptable difference IMHO.

Next, let's consider essentially the worst case of new CPU overhead affecting overall performance. MultiGet uses the async lookup interface regardless of whether SecondaryCache or folly are used. We can configure a benchmark where all block cache queries are for data blocks, and all are hits.

Create DB and test (before and after tests running simultaneously):
```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=fillrandom -num=30000000 -disable_wal=1 -bloom_bits=16
TEST_TMPDIR=/dev/shm base/db_bench -benchmarks=multireadrandom[-X30] -readonly -multiread_batched -batch_size=32 -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16
```

**Before**:
multireadrandom [AVG    30 runs] : 3444202 (± 57049) ops/sec;  240.9 (± 4.0) MB/sec
multireadrandom [MEDIAN 30 runs] : 3514443 ops/sec;  245.8 MB/sec
**After**:
multireadrandom [AVG    30 runs] : 3291022 (± 58851) ops/sec;  230.2 (± 4.1) MB/sec
multireadrandom [MEDIAN 30 runs] : 3366179 ops/sec;  235.4 MB/sec

So that's roughly a 3% regression, on kind of a *worst case* test of MultiGet CPU. Similar story with HyperClockCache:

**Before**:
multireadrandom [AVG    30 runs] : 3933777 (± 41840) ops/sec;  275.1 (± 2.9) MB/sec
multireadrandom [MEDIAN 30 runs] : 3970667 ops/sec;  277.7 MB/sec
**After**:
multireadrandom [AVG    30 runs] : 3755338 (± 30391) ops/sec;  262.6 (± 2.1) MB/sec
multireadrandom [MEDIAN 30 runs] : 3785696 ops/sec;  264.8 MB/sec

Roughly a 4-5% regression. Not ideal, but not the whole story, fortunately.

Let's also look at Get() in db_bench:

```
TEST_TMPDIR=/dev/shm ./db_bench -benchmarks=readrandom[-X30] -readonly -num=30000000 -bloom_bits=16 -cache_size=6789000000 -duration 20 -threads=16
```

**Before**:
readrandom [AVG    30 runs] : 2198685 (± 13412) ops/sec;  153.8 (± 0.9) MB/sec
readrandom [MEDIAN 30 runs] : 2209498 ops/sec;  154.5 MB/sec
**After**:
readrandom [AVG    30 runs] : 2292814 (± 43508) ops/sec;  160.3 (± 3.0) MB/sec
readrandom [MEDIAN 30 runs] : 2365181 ops/sec;  165.4 MB/sec

That's showing roughly a 4% improvement, perhaps because of the secondary cache code that is no longer part of LRUCache. But weirdly, HyperClockCache is also showing 2-3% improvement:

**Before**:
readrandom [AVG    30 runs] : 2272333 (± 9992) ops/sec;  158.9 (± 0.7) MB/sec
readrandom [MEDIAN 30 runs] : 2273239 ops/sec;  159.0 MB/sec
**After**:
readrandom [AVG    30 runs] : 2332407 (± 11252) ops/sec;  163.1 (± 0.8) MB/sec
readrandom [MEDIAN 30 runs] : 2335329 ops/sec;  163.3 MB/sec

Reviewed By: ltamasi

Differential Revision: D44177044

Pulled By: pdillinger

fbshipit-source-id: e808e48ff3fe2f792a79841ba617be98e48689f5
2023-03-17 20:23:49 -07:00
Peter Dillinger 601efe3cf2 Misc cleanup of block cache code (#11291)
Summary:
... ahead of a larger change.
* Rename confusingly named `is_in_sec_cache` to `kept_in_sec_cache`
* Unify naming of "standalone" block cache entries (was "detached" in clock_cache)
* Remove some unused definitions in clock_cache.h (leftover from a previous revision)

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11291

Test Plan: usual tests and CI, no behavior changes

Reviewed By: anand1976

Differential Revision: D43984642

Pulled By: pdillinger

fbshipit-source-id: b8bf0c5b90a932a88bcbdb413b2f256834aedf97
2023-03-15 12:08:17 -07:00
Wentian Guo 42d6652ba2 remove dependency on options.h for port_posix.h andport_win.h (#11214)
Summary:
The files in `port/`, such as `port_posix.h`, are layering over the system libraries, so shouldn't include the DB-specific files like `options.h`. This PR remove this dependency.

# How
The reason that `port_posix.h` (or `port_win.h`) include `options.h` is to use `CpuPriority`, as there is a method `SetCpuPriority()` in `port_posix.h` that uses `CpuPriority.`
- I think `SetCpuPriority()` make sense to exist in `port_posix.h` as it provides has platform-dependent implementation
- `CpuPriority` enum is defined in `env.h`, but used in `rocksdb/include` and `port/`.

Hence, let us define `CpuPriority` enum in a common file, say `port_defs.h`, such that both directories `rocksdb/include` and `port/` can include.

When we remove this dependency, some other files have compile errors because they can't find definitions, so add header files to resolve

# Test
make all check -j

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11214

Reviewed By: pdillinger

Differential Revision: D43196910

Pulled By: guowentian

fbshipit-source-id: 70deccb72844cfb08fcc994f76c6ef6df5d55ab9
2023-02-13 02:21:38 -08:00
Peter Dillinger 9f7801c5f1 Major Cache refactoring, CPU efficiency improvement (#10975)
Summary:
This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache).

The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below.

* static_cast lines of code +29 -35 (net removed 6)
* reinterpret_cast lines of code +6 -32 (net removed 26)

## cache.h and secondary_cache.h
* Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications:
  * Simpler for implementations to deal with just one Insert and one Lookup.
  * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters
  * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428.
  * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks).
  * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below).
  * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc.
* Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation.
* Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.)
* Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.)
* Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774)
* Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object.
* Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change.

## typed_cache.h
Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae).

The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used.
* PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value.
* BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter.
* FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue.
* For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`.

These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.)

Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it.

## block_cache.h
This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table.

## block_based_table_reader.cc
Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation.

The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions.

## block_based_table_builder.cc, cache_dump_load_impl.cc
Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.)

## Everything else
Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975

Test Plan:
tests updated

Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache):

34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844
34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594
34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297
34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523
34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602
34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293
34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926
34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488
233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984
233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922
233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559
233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93
233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418
233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273
233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691
233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82
1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55
1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02
1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45
1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24
1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92
1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78
1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36
1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83

Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn.

Reviewed By: anand1976

Differential Revision: D42417818

Pulled By: pdillinger

fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432
2023-01-11 14:20:40 -08:00
Peter Dillinger 3182beeffc Observe and warn about misconfigured HyperClockCache (#10965)
Summary:
Background. One of the core risks of chosing HyperClockCache is ending up with degraded performance if estimated_entry_charge is very significantly wrong. Too low leads to under-utilized hash table, which wastes a bit of (tracked) memory and likely increases access times due to larger working set size (more TLB misses). Too high leads to fully populated hash table (at some limit with reasonable lookup performance) and not being able to cache as many objects as the memory limit would allow. In either case, performance degradation is graceful/continuous but can be quite significant. For example, cutting block size in half without updating estimated_entry_charge could lead to a large portion of configured block cache memory (up to roughly 1/3) going unused.

Fix. This change adds a mechanism through which the DB periodically probes the block cache(s) for "problems" to report, and adds diagnostics to the HyperClockCache for bad estimated_entry_charge. The periodic probing is currently done with DumpStats / stats_dump_period_sec, and diagnostics reported to info_log (normally LOG file).

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10965

Test Plan:
unit test included. Doesn't cover all the implemented subtleties of reporting, but ensures basics of when to report or not.

Also manual testing with db_bench. Create db with
```
./db_bench --benchmarks=fillrandom,flush --num=3000000 --disable_wal=1
```
Use and check LOG file for HyperClockCache for various block sizes (used as estimated_entry_charge)
```
./db_bench --use_existing_db --benchmarks=readrandom --num=3000000 --duration=20 --stats_dump_period_sec=8 --cache_type=hyper_clock_cache -block_size=XXXX
```
Seeing warnings / errors or not as expected.

Reviewed By: anand1976

Differential Revision: D41406932

Pulled By: pdillinger

fbshipit-source-id: 4ca56162b73017e4b9cec2cad74466f49c27a0a7
2022-11-21 12:08:21 -08:00
Peter Dillinger cc8c8f6958 Refactor (Hyper)ClockCache code (#10887)
Summary:
For clean-up and in preparation for some other anticipated changes, including
* A new dynamically-scaling variant of HyperClockCache
* SecondaryCache support for HyperClockCache

This change does some refactoring for current and future code sharing and reusability. (Including follow-up on https://github.com/facebook/rocksdb/issues/10843)

## clock_cache.h
* TBD whether new variant will be a HyperClockCache or use some other name, so namespace is just clock_cache for the family of structures.
* A number of helper functions introduced and used.
* Pre-emptively split ClockHandle (shared among lock-free clock cache variants) and HandleImpl (specific to a kind of Table), and introduce template to plug new Table implementation into ClockCacheShard.

## clock_cache.cc
* Mostly using helper functions. Some things like `Rollback()` and `FreeDataMarkEmpty()` were not combined because `Rollback()` is Table-specific while `FreeDataMarkEmpty()` can be used with different table implementations.
* Performance testing indicated that despite more opportunities for parallelism, making a local copy of handle data for processing after marking an entry empty was slower than doing that processing before marking the entry empty (but after marking it "under construction"), thus avoiding a few words of copying data. At least for now, this answers the "TODO? Delay freeing?" questions (no).

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10887

Test Plan:
fixed a unit testing gap; other minor test updates for refactoring

No functionality change

## Performance
Same setup as https://github.com/facebook/rocksdb/issues/10801:

Before: `readrandom [AVG 81 runs] : 627992 (± 5124) ops/sec`
After: `readrandom [AVG 81 runs] : 637512 (± 4866) ops/sec`

I've been getting some inconsistent results on restarts like the system is not being fair to the two processes, so I'm not sure there's such a real difference.

Reviewed By: anand1976

Differential Revision: D40959240

Pulled By: pdillinger

fbshipit-source-id: 0a8f3646b3bdb5bc7aaad60b26790b0779189949
2022-11-02 22:41:39 -07:00
Denis Hananein 9f3475eccf Fix compilation errors, clang++-15 (#10907)
Summary:
I've tried to compile the main branch, but there are two minor things which are make CE.
I'm not sure about the second one (`num_empty_non_l0_level`), probably there is should be additional assert.

```
-c ../cache/clock_cache.cc
[build] ../cache/clock_cache.cc:855:15: error: variable 'i' set but not used [-Werror,-Wunused-but-set-variable]
[build]   for (size_t i = 0; &array_[current] != h; i++) {
[build]               ^
```

```
[build] ../db/version_set.cc:3665:7: error: variable 'num_empty_non_l0_level' set but not used [-Werror,-Wunused-but-set-variable]
[build]   int num_empty_non_l0_level = 0;
[build]       ^
[build] 1 error generated.
```

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10907

Reviewed By: jay-zhuang

Differential Revision: D40866667

Pulled By: ajkr

fbshipit-source-id: 963b7bd56859d0b3b2779cd36fad229425cb7b17
2022-10-31 18:24:44 -07:00
Peter Dillinger b6e33dbc0e Fix HyperClockCache Rollback bug in #10801 (#10843)
Summary:
In https://github.com/facebook/rocksdb/issues/10801 in ClockHandleTable::Evict, we saved a reference to the hash value (`const UniqueId64x2& hashed_key`) instead of saving the hash value itself before marking the handle as empty and thus free for use by other threads. This could lead to Rollback seeing the wrong hash value for updating the `displacements` after an entry is removed.

The fix is (like other places) to copy the hash value before it's released. (We could Rollback while we own the entry, but that creates more dependences between atomic updates, because in that case, based on the code, the Rollback writes would have to happen before or after the entry is released by marking empty. By doing the relaxed Rollback after marking empty, there's more opportunity for re-ordering / ILP.)

Intended follow-up: refactoring for better code sharing in clock_cache.cc

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10843

Test Plan: watch for clean crash test, TSAN

Reviewed By: siying

Differential Revision: D40579680

Pulled By: pdillinger

fbshipit-source-id: 258e43b3b80bc980a161d5c675ccc6708ecb8025
2022-10-21 12:09:03 -07:00
Peter Dillinger 7555243bcf Refactor ShardedCache for more sharing, static polymorphism (#10801)
Summary:
The motivations for this change include
* Free up space in ClockHandle so that we can add data for secondary cache handling while still keeping within single cache line (64 byte) size.
  * This change frees up space by eliminating the need for the `hash` field by making the fixed-size key itself a hash, using a 128-bit bijective (lossless) hash.
* Generally more customizability of ShardedCache (such as hashing) without worrying about virtual call overheads
  * ShardedCache now uses static polymorphism (template) instead of dynamic polymorphism (virtual overrides) for the CacheShard. No obvious performance benefit is seen from the change (as mostly expected; most calls to virtual functions in CacheShard could already be optimized to static calls), but offers more flexibility without incurring the runtime cost of adhering to a common interface (without type parameters or static callbacks).
  * You'll also notice less `reinterpret_cast`ing and other boilerplate in the Cache implementations, as this can go in ShardedCache.

More detail:
* Don't have LRUCacheShard maintain `std::shared_ptr<SecondaryCache>` copies (extra refcount) when LRUCache can be in charge of keeping a `shared_ptr`.
* Renamed `capacity_mutex_` to `config_mutex_` to better represent the scope of what it guards.
* Some preparation for 64-bit hash and indexing in LRUCache, but didn't include the full change because of slight performance regression.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10801

Test Plan:
Unit test updates were non-trivial because of major changes to the ClockCacheShard interface in handling of key vs. hash.

Performance:
Create 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[-X1000] -readonly -num=30000000 -bloom_bits=16 -cache_index_and_filter_blocks=1 -cache_size=610000000 -duration 20 -threads=16
```

Before: `readrandom [AVG 150 runs] : 321147 (± 253) ops/sec`
After: `readrandom [AVG 150 runs] : 321530 (± 326) ops/sec`

So possibly ~0.1% improvement.

And with `-cache_type=hyper_clock_cache`:
Before: `readrandom [AVG 30 runs] : 614126 (± 7978) ops/sec`
After: `readrandom [AVG 30 runs] : 645349 (± 8087) ops/sec`

So roughly 5% improvement!

Reviewed By: anand1976

Differential Revision: D40252236

Pulled By: pdillinger

fbshipit-source-id: ff8fc70ef569585edc95bcbaaa0386f61355ae5b
2022-10-18 22:06:57 -07:00
Peter Dillinger b205c6d029 Fix bug in HyperClockCache ApplyToEntries; cleanup (#10768)
Summary:
We have seen some rare crash test failures in HyperClockCache, and the source could certainly be a bug fixed in this change, in ClockHandleTable::ConstApplyToEntriesRange. It wasn't properly accounting for the fact that incrementing the acquire counter could be ineffective, due to parallel updates. (When incrementing the acquire counter is ineffective, it is incorrect to then decrement it.)

This change includes some other minor clean-up in HyperClockCache, and adds stats_dump_period_sec with a much lower period to the crash test. This should be the primary caller of ApplyToEntries, in collecting cache entry stats.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10768

Test Plan: haven't been able to reproduce the failure, but should be in a better state (bug fix and improved crash test)

Reviewed By: anand1976

Differential Revision: D40034747

Pulled By: anand1976

fbshipit-source-id: a06fcefe146e17ee35001984445cedcf3b63eb68
2022-10-06 14:54:21 -07:00
Peter Dillinger 0f91c72adc Call experimental new clock cache HyperClockCache (#10684)
Summary:
This change establishes a distinctive name for the experimental new lock-free clock cache (originally developed by guidotag and revamped in PR https://github.com/facebook/rocksdb/issues/10626). A few reasons:
* We want to make it clear that this is a fundamentally different implementation vs. the old clock cache, to avoid people saying "I already tried clock cache."
* We want to highlight the key feature: it's fast (especially under parallel load)
* Because it requires an estimated charge per entry, it is not drop-in API compatible with old clock cache. This estimate might always be required for highest performance, and giving it a distinct name should reduce confusion about the distinct API requirements.
* We might develop a variant requiring the same estimate parameter but with LRU eviction. In that case, using the name HyperLRUCache should make things more clear. (FastLRUCache is just a prototype that might soon be removed.)

Some API detail:
* To reduce copy-pasting parameter lists, etc. as in LRUCache construction, I have a `MakeSharedCache()` function on `HyperClockCacheOptions` instead of `NewHyperClockCache()`.
* Changes -cache_type=clock_cache to -cache_type=hyper_clock_cache for applicable tools. I think this is more consistent / sustainable for reasons already stated.

For performance tests see https://github.com/facebook/rocksdb/pull/10626

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10684

Test Plan: no interesting functional changes; tests updated

Reviewed By: anand1976

Differential Revision: D39547800

Pulled By: pdillinger

fbshipit-source-id: 5c0fe1b5cf3cb680ab369b928c8569682b9795bf
2022-09-16 12:47:29 -07:00
Peter Dillinger 5724348689 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
2022-09-16 00:24:11 -07:00
Gang Liao 275cd80cdb Add a blob-specific cache priority (#10461)
Summary:
RocksDB's `Cache` abstraction currently supports two priority levels for items: high (used for frequently accessed/highly valuable SST metablocks like index/filter blocks) and low (used for SST data blocks). Blobs are typically lower-value targets for caching than data blocks, since 1) with BlobDB, data blocks containing blob references conceptually form an index structure which has to be consulted before we can read the blob value, and 2) cached blobs represent only a single key-value, while cached data blocks generally contain multiple KVs. Since we would like to make it possible to use the same backing cache for the block cache and the blob cache, it would make sense to add a new, lower-than-low cache priority level (bottom level) for blobs so data blocks are prioritized over them.

This task is a part of https://github.com/facebook/rocksdb/issues/10156

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10461

Reviewed By: siying

Differential Revision: D38672823

Pulled By: ltamasi

fbshipit-source-id: 90cf7362036563d79891f47be2cc24b827482743
2022-08-12 17:59:06 -07:00
Guido Tagliavini Ponce a0798f6f92 Enable ClockCache in DB block cache test (#10482)
Summary:
A test in db_block_cache_test.cc was skipping ClockCache due to the 16-byte key length requirement. We fixed this. Along the way, we fixed a bug in ApplyToSomeEntries, which assumed the function being applied could modify handle metadata, and thus took an exclusive reference. This is incompatible with calls that need to inspect every element (including externally referenced ones) to gather stats.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10482

Test Plan: ``make -j24 check``

Reviewed By: anand1976

Differential Revision: D38553073

Pulled By: guidotag

fbshipit-source-id: 0ed63fed4d3b89e5056b35b7091fce579f5647ae
2022-08-10 13:57:52 -07:00
Peter Dillinger 65036e4217 Revert "Add a blob-specific cache priority (#10309)" (#10434)
Summary:
This reverts commit 8d178090be
because of a clear performance regression seen in internal dashboard
https://fburl.com/unidash/tpz75iee

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10434

Reviewed By: ltamasi

Differential Revision: D38256373

Pulled By: pdillinger

fbshipit-source-id: 134aa00f50dd7b1bbe037c227884a351342ec44b
2022-07-29 07:18:15 -07:00
Gang Liao 8d178090be Add a blob-specific cache priority (#10309)
Summary:
RocksDB's `Cache` abstraction currently supports two priority levels for items: high (used for frequently accessed/highly valuable SST metablocks like index/filter blocks) and low (used for SST data blocks). Blobs are typically lower-value targets for caching than data blocks, since 1) with BlobDB, data blocks containing blob references conceptually form an index structure which has to be consulted before we can read the blob value, and 2) cached blobs represent only a single key-value, while cached data blocks generally contain multiple KVs. Since we would like to make it possible to use the same backing cache for the block cache and the blob cache, it would make sense to add a new, lower-than-low cache priority level (bottom level) for blobs so data blocks are prioritized over them.

This task is a part of https://github.com/facebook/rocksdb/issues/10156

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10309

Reviewed By: ltamasi

Differential Revision: D38211655

Pulled By: gangliao

fbshipit-source-id: 65ef33337db4d85277cc6f9782d67c421ad71dd5
2022-07-27 19:09:24 -07:00
Guido Tagliavini Ponce d976f68977 Fix assertion failure and memory leak in ClockCache. (#10430)
Summary:
This fixes two issues:
- [T127355728](https://www.internalfb.com/intern/tasks/?t=127355728): In the stress tests, when the ClockCache is operating close to full capacity and a burst of inserts are concurrently executed, every slot in the hash table may become occupied. This contradicts an assertion in the code, which is no longer valid in the lock-free setting. We are removing that assertion and handling the case of an insertion into a full table.
- [T127427659](https://www.internalfb.com/intern/tasks/?t=127427659): There was a memory leak when an insertion is performed over capacity, but no handle is provided. In that case, a handle was dynamically allocated, but the pointer wasn't stored anywhere.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10430

Test Plan:
- ``make -j24 check``
- ``make -j24 USE_CLANG=1 COMPILE_WITH_ASAN=1 COMPILE_WITH_UBSAN=1 CRASH_TEST_EXT_ARGS="--duration=960 --cache_type=clock_cache" blackbox_crash_test_with_atomic_flush``
- ``make -j24 USE_CLANG=1 COMPILE_WITH_TSAN=1 CRASH_TEST_EXT_ARGS="--duration=960 --cache_type=clock_cache" blackbox_crash_test_with_atomic_flush``

Reviewed By: pdillinger

Differential Revision: D38226114

Pulled By: guidotag

fbshipit-source-id: 18f6ab7e6214e11e9721d5ff289db1bf795d0008
2022-07-27 18:55:55 -07:00
Guido Tagliavini Ponce 9d7de6517c Towards a production-quality ClockCache (#10418)
Summary:
In this PR we bring ClockCache closer to production quality. We implement the following changes:
1. Fixed a few bugs in ClockCache.
2. ClockCache now fully supports ``strict_capacity_limit == false``: When an insertion over capacity is commanded, we allocate a handle separately from the hash table.
3. ClockCache now runs on almost every test in cache_test. The only exceptions are a test where either the LRU policy is required, and a test that dynamically increases the table capacity.
4. ClockCache now supports dynamically decreasing capacity via SetCapacity. (This is easy: we shrink the capacity upper bound and run the clock algorithm.)
5. Old FastLRUCache tests in lru_cache_test.cc are now also used on ClockCache.

As a byproduct of 1. and 2. we are able to turn on ClockCache in the stress tests.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10418

Test Plan:
- ``make -j24 USE_CLANG=1 COMPILE_WITH_ASAN=1 COMPILE_WITH_UBSAN=1 check``
- ``make -j24 USE_CLANG=1 COMPILE_WITH_TSAN=1 check``
- ``make -j24 USE_CLANG=1 COMPILE_WITH_ASAN=1 COMPILE_WITH_UBSAN=1 CRASH_TEST_EXT_ARGS="--duration=960 --cache_type=clock_cache" blackbox_crash_test_with_atomic_flush``
- ``make -j24 USE_CLANG=1 COMPILE_WITH_TSAN=1 CRASH_TEST_EXT_ARGS="--duration=960 --cache_type=clock_cache" blackbox_crash_test_with_atomic_flush``

Reviewed By: pdillinger

Differential Revision: D38170673

Pulled By: guidotag

fbshipit-source-id: 508987b9dc9d9d68f1a03eefac769820b680340a
2022-07-26 17:42:03 -07:00
Guido Tagliavini Ponce 6a160e1fec Lock-free ClockCache (#10390)
Summary:
ClockCache completely free of locks. As part of this PR we have also pushed clock algorithm functionality out of ClockCacheShard into ClockHandleTable, so that ClockCacheShard acts more as an interface and less as an actual data structure.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10390

Test Plan:
- ``make -j24 check``
- ``make -j24 CRASH_TEST_EXT_ARGS="--duration=960 --cache_type=clock_cache --cache_size=1073741824 --block_size=16384" blackbox_crash_test_with_atomic_flush``

Reviewed By: pdillinger

Differential Revision: D38106945

Pulled By: guidotag

fbshipit-source-id: 6cbf6bd2397dc9f582809ccff5118a8a33ea6cb1
2022-07-25 10:02:19 -07:00
Guido Tagliavini Ponce efdb428edc Lock-free Lookup and Release in ClockCache (#10347)
Summary:
This is a prototype of a partially lock-free version of ClockCache. Roughly speaking, reads are lock-free and writes are lock-based:
- Lookup is lock-free.
- Release is lock-free, unless (i) no references to the element are left and (ii) it was marked for deletion or ``erase_if_last_ref`` is set.
- Insert and Erase still use a per-shard lock.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10347

Test Plan:
- ``make -j24 check``
- ``make -j24 CRASH_TEST_EXT_ARGS="--duration=960 --cache_type=clock_cache --cache_size=1073741824 --block_size=16384" blackbox_crash_test_with_atomic_flush``

Reviewed By: pdillinger

Differential Revision: D37898776

Pulled By: guidotag

fbshipit-source-id: 6418fd980f786d69b871bf2fe959398e44cd3d80
2022-07-15 22:36:58 -07:00
Guido Tagliavini Ponce 7e1b417824 Revert NewClockCache signature (#10358)
Summary:
This complements https://github.com/facebook/rocksdb/issues/10351. This PR reverts NewClockCache's signature to an older version, expected by the users of the old (buggy) ClockCache.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10358

Test Plan: ``make -j24 check`` and re-run the pre-release tests.

Reviewed By: siying

Differential Revision: D37832601

Pulled By: guidotag

fbshipit-source-id: 32a91d3da4119be187935003b7b897272ceb1950
2022-07-13 17:43:39 -07:00
Guido Tagliavini Ponce 9645e66fc9 Temporarily return a LRUCache from NewClockCache (#10351)
Summary:
ClockCache is still in experimental stage, and currently fails some pre-release fbcode tests. See https://www.internalfb.com/diff/D37772011. API calls to construct ClockCache are done via the function NewClockCache. For now, NewClockCache calls will return an LRUCache (with appropriate arguments), which is stable.

The idea that NewClockCache returns nullptr was also floated, but this would be interpreted as unsupported cache, and a default LRUCache would be constructed instead, potentially causing a performance regression that is harder to identify.

A new version of the NewClockCache function was created for our internal tests.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10351

Test Plan: ``make -j24 check`` and re-run the pre-release tests.

Reviewed By: pdillinger

Differential Revision: D37802685

Pulled By: guidotag

fbshipit-source-id: 0a8d10612ff21e576f7360cb13e20bc36e244972
2022-07-13 08:45:44 -07:00
Guido Tagliavini Ponce c277aeb42c Midpoint insertions in ClockCache (#10305)
Summary:
When an element is first inserted into the ClockCache, it is now assigned either medium or high clock priority, depending on whether its cache priority is low or high, respectively. This is a variant of LRUCache's midpoint insertions. The main difference is that LRUCache can specify the allocated capacity for high-priority elements via the ``high_pri_pool_ratio`` parameter. Contrarily, in ClockCache, low- and high-priority elements compete for all cache slots, and one group can take over the other (of course, it takes more low-priority insertions to push out high-priority elements). However, just as LRUCache, ClockCache provides the following guarantee: a high-priority element will not be evicted before a low-priority element that was inserted earlier in time.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10305

Test Plan: ``make -j24 check``

Reviewed By: pdillinger

Differential Revision: D37607787

Pulled By: guidotag

fbshipit-source-id: 24d9f2523d2f4e6415e7f0029cc061fa275c2040
2022-07-06 18:28:35 -07:00
Peter Dillinger e6c5e0ab9a Have Cache use Status::MemoryLimit (#10262)
Summary:
I noticed it would clean up some things to have Cache::Insert()
return our MemoryLimit Status instead of Incomplete for the case in
which the capacity limit is reached. I suspect this fixes some existing but
unknown bugs where this Incomplete could be confused with other uses
of Incomplete, especially no_io cases. This is the most suspicious case I
noticed, but was not able to reproduce a bug, in part because the existing
code is not covered by unit tests (FIXME added): 57adbf0e91/table/get_context.cc (L397)

I audited all the existing uses of IsIncomplete and updated those that
seemed relevant.

HISTORY updated with a clear warning to users of strict_capacity_limit=true
to update uses of `IsIncomplete()`

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10262

Test Plan: updated unit tests

Reviewed By: hx235

Differential Revision: D37473155

Pulled By: pdillinger

fbshipit-source-id: 4bd9d9353ccddfe286b03ebd0652df8ce20f99cb
2022-07-06 14:41:46 -07:00
Guido Tagliavini Ponce 54f678cd86 Fix CalcHashBits (#10295)
Summary:
We fix two bugs in CalcHashBits. The first one is an off-by-one error: the desired number of table slots is the real number ``capacity / (kLoadFactor * handle_charge)``, which should not be rounded down. The second one is that we should disallow inputs that set the element charge to 0, namely ``estimated_value_size == 0 && metadata_charge_policy == kDontChargeCacheMetadata``.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10295

Test Plan: CalcHashBits is tested by CalcHashBitsTest (in lru_cache_test.cc). The test now iterates over many more inputs; it covers, in particular, the rounding error edge case. Overall, the test is now more robust. Run ``make -j24 check``.

Reviewed By: pdillinger

Differential Revision: D37573797

Pulled By: guidotag

fbshipit-source-id: ea4f4439f7196ab1c1afb88f566fe92850537262
2022-07-01 20:51:20 -07:00