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Author SHA1 Message Date
anand76 cc069f25b3 Add some compressed and tiered secondary cache stats (#12150)
Summary:
Add statistics for more visibility.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/12150

Reviewed By: akankshamahajan15

Differential Revision: D52184633

Pulled By: anand1976

fbshipit-source-id: 9969e05d65223811cd12627102b020bb6d229352
2023-12-15 11:34:08 -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
anand76 269478ee46 Support compressed and local flash secondary cache stacking (#11812)
Summary:
This PR implements support for a three tier cache - primary block cache, compressed secondary cache, and a nvm (local flash) secondary cache. This allows more effective utilization of the nvm cache, and minimizes the number of reads from local flash by caching compressed blocks in the compressed secondary cache.

The basic design is as follows -
1. A new secondary cache implementation, ```TieredSecondaryCache```, is introduced. It keeps the compressed and nvm secondary caches and manages the movement of blocks between them and the primary block cache. To setup a three tier cache, we allocate a ```CacheWithSecondaryAdapter```, with a ```TieredSecondaryCache``` instance as the secondary cache.
2. The table reader passes both the uncompressed and compressed block to ```FullTypedCacheInterface::InsertFull```, allowing the block cache to optionally store the compressed block.
3. When there's a miss, the block object is constructed and inserted in the primary cache, and the compressed block is inserted into the nvm cache by calling ```InsertSaved```. This avoids the overhead of recompressing the block, as well as avoiding putting more memory pressure on the compressed secondary cache.
4. When there's a hit in the nvm cache, we attempt to insert the block in the compressed secondary cache and the primary cache, subject to the admission policy of those caches (i.e admit on second access). Blocks/items evicted from any tier are simply discarded.

We can easily implement additional admission policies if desired.

Todo (In a subsequent PR):
1. Add to db_bench and run benchmarks
2. Add to db_stress

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11812

Reviewed By: pdillinger

Differential Revision: D49461842

Pulled By: anand1976

fbshipit-source-id: b40ac1330ef7cd8c12efa0a3ca75128e602e3a0b
2023-09-21 20:30:53 -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 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 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 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 ccaa3225b0 Simplify tracking entries already in SecondaryCache (#11299)
Summary:
In preparation for factoring secondary cache support out of individual Cache implementations, we can get rid of the "in secondary cache" flag on entries through a workable hack: when an entry is promoted from secondary, it is inserted in primary using a helper that lacks secondary cache support, thus preventing re-insertion into secondary cache through existing logic.

This adds to the complexity of building CacheItemHelpers, because you always have to be able to get to an equivalent helper without secondary cache support, but that complexity is reasonably isolated within RocksDB typed_cache.h and test code.

gcc-7 seems to have problems with constexpr constructor referencing `this` so removed constexpr support on CacheItemHelper.

Also refactored some related test code to share common code / functionality.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11299

Test Plan: existing tests

Reviewed By: anand1976

Differential Revision: D44101453

Pulled By: pdillinger

fbshipit-source-id: 7a59d0a3938ee40159c90c3e65d7004f6a272345
2023-03-15 17:51:44 -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
Peter Dillinger 2a23bee963 Use CacheWrapper in more places (#11295)
Summary:
... to simplify code and make it less prone to needless updates on refactoring.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11295

Test Plan: existing tests (no functional changes intended)

Reviewed By: hx235

Differential Revision: D44040260

Pulled By: pdillinger

fbshipit-source-id: 1b6badb5c8ca673db0903bfaba3cfbc986f386be
2023-03-13 20:41:55 -07:00
anand76 cf09917c18 Add filter/index/data secondary cache hits stats (#11246)
Summary:
Add more stats for better visibility into the usefulness of the secondary cache.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11246

Test Plan: Add a new unit test

Reviewed By: akankshamahajan15

Differential Revision: D43521364

Pulled By: anand1976

fbshipit-source-id: a92f04884e738a9bf40ad4047acaaaea343838a7
2023-02-28 10:36:56 -08:00
sdong 4720ba4391 Remove RocksDB LITE (#11147)
Summary:
We haven't been actively mantaining RocksDB LITE recently and the size must have been gone up significantly. We are removing the support.

Most of changes were done through following comments:

unifdef -m -UROCKSDB_LITE `git grep -l ROCKSDB_LITE | egrep '[.](cc|h)'`

by Peter Dillinger. Others changes were manually applied to build scripts, CircleCI manifests, ROCKSDB_LITE is used in an expression and file db_stress_test_base.cc.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11147

Test Plan: See CI

Reviewed By: pdillinger

Differential Revision: D42796341

fbshipit-source-id: 4920e15fc2060c2cd2221330a6d0e5e65d4b7fe2
2023-01-27 13:14:19 -08:00
sdong 2800aa069a Remove compressed block cache (#11117)
Summary:
Compressed block cache is replaced by compressed secondary cache. Remove the feature.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11117

Test Plan: See CI passes

Reviewed By: pdillinger

Differential Revision: D42700164

fbshipit-source-id: 6cbb24e460da29311150865f60ecb98637f9f67d
2023-01-24 17:09:19 -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 e079d562af Add a SecondaryCache::InsertSaved() API, use in CacheDumper impl (#10945)
Summary:
Can simplify some ugly code in cache_dump_load_impl.cc by having an API in SecondaryCache that can directly consume persisted data.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10945

Test Plan: existing tests for CacheDumper, added basic unit test

Reviewed By: anand1976

Differential Revision: D41231497

Pulled By: pdillinger

fbshipit-source-id: b8ec993ef7d3e7efd68aae8602fd3f858da58068
2022-11-21 16:17:36 -08:00
Peter Dillinger 32520df1d9 Remove prototype FastLRUCache (#10954)
Summary:
This was just a stepping stone to what eventually became HyperClockCache, and is now just more code to maintain.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10954

Test Plan: tests updated

Reviewed By: akankshamahajan15

Differential Revision: D41310123

Pulled By: pdillinger

fbshipit-source-id: 618ee148a1a0a29ee756ba8fe28359617b7cd67c
2022-11-16 10:15:55 -08:00
Peter Dillinger f321e8fc98 Don't attempt to use SecondaryCache on block_cache_compressed (#10944)
Summary:
Compressed block cache depends on reading the block compression marker beyond the payload block size. Only the payload bytes were being saved and loaded from SecondaryCache -> boom!

This removes some unnecessary code attempting to combine these two competing features. Note that BlockContents was previously used for block-based filter in block cache, but that support has been removed.

Also marking block_cache_compressed as deprecated in this commit as we expect it to be replaced with SecondaryCache.

This problem was discovered during refactoring but didn't want to combine bug fix with that refactoring.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10944

Test Plan: test added that fails on base revision (at least with ASAN)

Reviewed By: akankshamahajan15

Differential Revision: D41205578

Pulled By: pdillinger

fbshipit-source-id: 1b29d36c7a6552355ac6511fcdc67038ef4af29f
2022-11-11 17:35:53 -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
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 e466173d5c Print stack traces on frozen tests in CI (#10828)
Summary:
Instead of existing calls to ps from gnu_parallel, call a new wrapper that does ps, looks for unit test like processes, and uses pstack or gdb to print thread stack traces. Also, using `ps -wwf` instead of `ps -wf` ensures output is not cut off.

For security, CircleCI runs with security restrictions on ptrace (/proc/sys/kernel/yama/ptrace_scope = 1), and this change adds a work-around to `InstallStackTraceHandler()` (only used by testing tools) to allow any process from the same user to debug it. (I've also touched >100 files to ensure all the unit tests call this function.)

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10828

Test Plan: local manual + temporary infinite loop in a unit test to observe in CircleCI

Reviewed By: hx235

Differential Revision: D40447634

Pulled By: pdillinger

fbshipit-source-id: 718a4c4a5b54fa0f9af2d01a446162b45e5e84e1
2022-10-18 00:35:35 -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
Bo Wang d490bfcdb6 Avoid recompressing cold block in CompressedSecondaryCache (#10527)
Summary:
**Summary:**
When a block is firstly `Lookup` from the secondary cache, we just insert a dummy block in the primary cache (charging the actual size of the block) and don’t erase the block from the secondary cache. A standalone handle is returned from `Lookup`. Only if the block is hit again, we erase it from the secondary cache and add it into the primary cache.

When a block is firstly evicted from the primary cache to the secondary cache, we just insert a dummy block (size 0) in the secondary cache. When the block is evicted again, it is treated as a hot block and is inserted into the secondary cache.

**Implementation Details**
Add a new state of LRUHandle: The handle is never inserted into the LRUCache (both hash table and LRU list) and it doesn't experience the above three states. The entry can be freed when refs becomes 0.  (refs >= 1 && in_cache == false && IS_STANDALONE == true)

The behaviors of  `LRUCacheShard::Lookup()` are updated if the secondary_cache is CompressedSecondaryCache:
1. If a handle is found in primary cache:
  1.1. If the handle's value is not nullptr, it is returned immediately.
  1.2. If the handle's value is nullptr, this means the handle is a dummy one. For a dummy handle, if it was retrieved from secondary cache, it may still exist in secondary cache.
    - 1.2.1. If no valid handle can be `Lookup` from secondary cache, return nullptr.
    - 1.2.2. If the handle from secondary cache is valid, erase it from the secondary cache and add it into the primary cache.
2. If a handle is not found in primary cache:
  2.1. If no valid handle can be `Lookup` from secondary cache, return nullptr.
  2.2.  If the handle from secondary cache is valid, insert a dummy block in the primary cache (charging the actual size of the block)  and return a standalone handle.

The behaviors of `LRUCacheShard::Promote()` are updated as follows:
1. If `e->sec_handle` has value, one of the following steps can happen:
  1.1. Insert a dummy handle and return a standalone handle to caller when `secondary_cache_` is `CompressedSecondaryCache` and e is a standalone handle.
  1.2. Insert the item into the primary cache and return the handle to caller.
  1.3. Exception handling.
3. If `e->sec_handle` has no value, mark the item as not in cache and charge the cache as its only metadata that'll shortly be released.

The behavior of  `CompressedSecondaryCache::Insert()` is updated:
1. If a block is evicted from the primary cache for the first time, a dummy item is inserted.
4. If a dummy item is found for a block, the block is inserted into the secondary cache.

The behavior of  `CompressedSecondaryCache:::Lookup()` is updated:
1. If a handle is not found or it is a dummy item, a nullptr is returned.
2. If `erase_handle` is true, the handle is erased.

The behaviors of  `LRUCacheShard::Release()` are adjusted for the standalone handles.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10527

Test Plan:
1. stress tests.
5. unit tests.
6. CPU profiling for db_bench.

Reviewed By: siying

Differential Revision: D38747613

Pulled By: gitbw95

fbshipit-source-id: 74a1eba7e1957c9affb2bd2ae3e0194584fa6eca
2022-09-07 19:00:27 -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
Peter Dillinger 86a1e3e0e7 Derive cache keys from SST unique IDs (#10394)
Summary:
... so that cache keys can be derived from DB manifest data
before reading the file from storage--so that every part of the file
can potentially go in a persistent cache.

See updated comments in cache_key.cc for technical details. Importantly,
the new cache key encoding uses some fancy but efficient math to pack
data into the cache key without depending on the sizes of the various
pieces. This simplifies some existing code creating cache keys, like
cache warming before the file size is known.

This should provide us an essentially permanent mapping between SST
unique IDs and base cache keys, with the ability to "upgrade" SST
unique IDs (and thus cache keys) with new SST format_versions.

These cache keys are of similar, perhaps indistinguishable quality to
the previous generation. Before this change (see "corrected" days
between collision):

```
./cache_bench -stress_cache_key -sck_keep_bits=43
18 collisions after 2 x 90 days, est 10 days between (1.15292e+19 corrected)
```

After this change (keep 43 bits, up through 50, to validate "trajectory"
is ok on "corrected" days between collision):
```
19 collisions after 3 x 90 days, est 14.2105 days between (1.63836e+19 corrected)
16 collisions after 5 x 90 days, est 28.125 days between (1.6213e+19 corrected)
15 collisions after 7 x 90 days, est 42 days between (1.21057e+19 corrected)
15 collisions after 17 x 90 days, est 102 days between (1.46997e+19 corrected)
15 collisions after 49 x 90 days, est 294 days between (2.11849e+19 corrected)
15 collisions after 62 x 90 days, est 372 days between (1.34027e+19 corrected)
15 collisions after 53 x 90 days, est 318 days between (5.72858e+18 corrected)
15 collisions after 309 x 90 days, est 1854 days between (1.66994e+19 corrected)
```

However, the change does modify (probably weaken) the "guaranteed unique" promise from this

> SST files generated in a single process are guaranteed to have unique cache keys, unless/until number session ids * max file number = 2**86

to this (see https://github.com/facebook/rocksdb/issues/10388)

> With the DB id limitation, we only have nice guaranteed unique cache keys for files generated in a single process until biggest session_id_counter and offset_in_file reach combined 64 bits

I don't think this is a practical concern, though.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10394

Test Plan: unit tests updated, see simulation results above

Reviewed By: jay-zhuang

Differential Revision: D38667529

Pulled By: pdillinger

fbshipit-source-id: 49af3fe7f47e5b61162809a78b76c769fd519fba
2022-08-12 13:49:49 -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 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
Gang Liao 0b6bc101ba Charge blob cache usage against the global memory limit (#10321)
Summary:
To help service owners to manage their memory budget effectively, we have been working towards counting all major memory users inside RocksDB towards a single global memory limit (see e.g. https://github.com/facebook/rocksdb/wiki/Write-Buffer-Manager#cost-memory-used-in-memtable-to-block-cache). The global limit is specified by the capacity of the block-based table's block cache, and is technically implemented by inserting dummy entries ("reservations") into the block cache. The goal of this task is to support charging the memory usage of the new blob cache against this global memory limit when the backing cache of the blob cache and the block cache are different.

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

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10321

Reviewed By: ltamasi

Differential Revision: D37913590

Pulled By: gangliao

fbshipit-source-id: eaacf23907f82dc7d18964a3f24d7039a2937a72
2022-07-18 23:26:57 -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
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
Guido Tagliavini Ponce 57a0e2f304 Clock cache (#10273)
Summary:
This is the initial step in the development of a lock-free clock cache. This PR includes the base hash table design (which we mostly ported over from FastLRUCache) and the clock eviction algorithm. Importantly, it's still _not_ lock-free---all operations use a shard lock. Besides the locking, there are other features left as future work:
- Remove keys from the handles. Instead, use 128-bit bijective hashes of them for handle comparisons, probing (we need two 32-bit hashes of the key for double hashing) and sharding (we need one 6-bit hash).
- Remove the clock_usage_ field, which is updated on every lookup. Even if it were atomically updated, it could cause memory invalidations across cores.
- Middle insertions into the clock list.
- A test that exercises the clock eviction policy.
- Update the Java API of ClockCache and Java calls to C++.

Along the way, we improved the code and comments quality of FastLRUCache. These changes are relatively minor.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10273

Test Plan: ``make -j24 check``

Reviewed By: pdillinger

Differential Revision: D37522461

Pulled By: guidotag

fbshipit-source-id: 3d70b737dbb70dcf662f00cef8c609750f083943
2022-06-29 21:50:39 -07:00
Guido Tagliavini Ponce c6055cba30 Calculate table size of FastLRUCache more accurately (#10235)
Summary:
Calculate the required size of the hash table in FastLRUCache more accurately.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10235

Test Plan: ``make -j24 check``

Reviewed By: gitbw95

Differential Revision: D37460546

Pulled By: guidotag

fbshipit-source-id: 7945128d6f002832f8ed922ef0151919f4350854
2022-06-27 21:04:59 -07:00
Guido Tagliavini Ponce f105e1a501 Make the per-shard hash table fixed-size. (#10154)
Summary:
We make the size of the per-shard hash table fixed. The base level of the hash table is now preallocated with the required capacity. The user must provide an estimate of the size of the values.

Notice that even though the base level becomes fixed, the chains are still dynamic. Overall, the shard capacity mechanisms haven't changed, so we don't need to test this.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10154

Test Plan: `make -j24 check`

Reviewed By: pdillinger

Differential Revision: D37124451

Pulled By: guidotag

fbshipit-source-id: cba6ac76052fe0ec60b8ff4211b3de7650e80d0c
2022-06-13 20:29:00 -07:00
Guido Tagliavini Ponce 415200d792 Assume fixed size key (#10137)
Summary:
FastLRUCache now only supports 16B keys. The tests have changed to reflect this.

Because the unit tests were designed for caches that accept any string as keys, some tests are no longer compatible with FastLRUCache. We have disabled those for runs with FastLRUCache. (We could potentially change all tests to use 16B keys, but we don't because the cache public API does not require this.)

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10137

Test Plan: make -j24 check

Reviewed By: gitbw95

Differential Revision: D37083934

Pulled By: guidotag

fbshipit-source-id: be1719cf5f8364a9a32bc4555bce1a0de3833b0d
2022-06-10 19:12:18 -07:00
gitbw95 f241d082b6 Prevent double caching in the compressed secondary cache (#9747)
Summary:
###  **Summary:**
When both LRU Cache and CompressedSecondaryCache are configured together, there possibly are some data blocks double cached.

**Changes include:**
1. Update IS_PROMOTED to IS_IN_SECONDARY_CACHE to prevent confusions.
2. This PR updates SecondaryCacheResultHandle and use IsErasedFromSecondaryCache to determine whether the handle is erased in the secondary cache. Then, the caller can determine whether to SetIsInSecondaryCache().
3. Rename LRUSecondaryCache to CompressedSecondaryCache.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/9747

Test Plan:
**Test Scripts:**
1. Populate a DB. The on disk footprint is 482 MB. The data is set to be 50% compressible, so the total decompressed size is expected to be 964 MB.
./db_bench --benchmarks=fillrandom --num=10000000 -db=/db_bench_1

2. overwrite it to a stable state:
./db_bench --benchmarks=overwrite,stats --num=10000000 -use_existing_db -duration=10 --benchmark_write_rate_limit=2000000 -db=/db_bench_1

4. Run read tests with diffeernt cache setting:

T1:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=520000000  --statistics -db=/db_bench_1

T2:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=320000000 -compressed_secondary_cache_size=400000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1

T3:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=520000000 -compressed_secondary_cache_size=400000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1

T4:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=20000000 -compressed_secondary_cache_size=500000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1

**Before this PR**
| Cache Size | Compressed Secondary Cache Size | Cache Hit Rate |
|------------|-------------------------------------|----------------|
|520 MB | 0 MB | 85.5% |
|320 MB | 400 MB | 96.2% |
|520 MB | 400 MB | 98.3% |
|20 MB | 500 MB | 98.8% |

**Before this PR**
| Cache Size | Compressed Secondary Cache Size | Cache Hit Rate |
|------------|-------------------------------------|----------------|
|520 MB | 0 MB | 85.5% |
|320 MB | 400 MB | 99.9% |
|520 MB | 400 MB | 99.9% |
|20 MB | 500 MB | 99.2% |

Reviewed By: anand1976

Differential Revision: D35117499

Pulled By: gitbw95

fbshipit-source-id: ea2657749fc13efebe91a8a1b56bc61d6a224a12
2022-04-11 13:28:33 -07:00
Andrew Kryczka 54fb2a8975 Change type of cache buffer passed to Cache::CreateCallback() to const void* (#9595)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/9595

Reviewed By: riversand963

Differential Revision: D34329906

Pulled By: ajkr

fbshipit-source-id: 508601856fa9bee4d40f4a68d14d333ef2143d40
2022-02-17 21:09:56 -08:00
Peter Dillinger fd3e0f43b3 Require C++17 (#9481)
Summary:
Drop support for some old compilers by requiring C++17 standard
(or higher). See https://github.com/facebook/rocksdb/issues/9388

First modification based on this is to remove some conditional compilation in slice.h (also
better for ODR)

Also in this PR:
* Fix some Makefile formatting that seems to affect ASSERT_STATUS_CHECKED config in
some cases
* Add c_test to NON_PARALLEL_TEST in Makefile
* Fix a clang-analyze reported "potential leak" in lru_cache_test
* Better "compatibility" definition of DEFINE_uint32 for old versions of gflags
* Fix a linking problem with shared libraries in Makefile (`./random_test: error while loading shared libraries: librocksdb.so.6.29: cannot open shared object file: No such file or directory`)
* Always set ROCKSDB_SUPPORT_THREAD_LOCAL and use thread_local (from C++11)
  * TODO in later PR: clean up that obsolete flag
* Fix a cosmetic typo in c.h (https://github.com/facebook/rocksdb/issues/9488)

Pull Request resolved: https://github.com/facebook/rocksdb/pull/9481

Test Plan:
CircleCI config substantially updated.

* Upgrade to latest Ubuntu images for each release
* Generally prefer Ubuntu 20, but keep a couple Ubuntu 16 builds with oldest supported
compilers, to ensure compatibility
* Remove .circleci/cat_ignore_eagain except for Ubuntu 16 builds, because this is to work
around a kernel bug that should not affect anything but Ubuntu 16.
* Remove designated gcc-9 build, because the default linux build now uses GCC 9 from
Ubuntu 20.
* Add some `apt-key add` to fix some apt "couldn't be verified" errors
* Generally drop SKIP_LINK=1; work-around no longer needed
* Generally `add-apt-repository` before `apt-get update` as manual testing indicated the
reverse might not work.

Travis:
* Use gcc-7 by default (remove specific gcc-7 and gcc-4.8 builds)
* TODO in later PR: fix s390x "Assembler messages: Error: invalid switch -march=z14" failure

AppVeyor:
* Completely dropped because we are dropping VS2015 support and CircleCI covers
VS >= 2017

Also local testing with old gflags (out of necessity when using ROCKSDB_NO_FBCODE=1).

Reviewed By: mrambacher

Differential Revision: D33946377

Pulled By: pdillinger

fbshipit-source-id: ae077c823905b45370a26c0103ada119459da6c1
2022-02-04 17:13:10 -08:00
Peter Dillinger 0050a73a4f New stable, fixed-length cache keys (#9126)
Summary:
This change standardizes on a new 16-byte cache key format for
block cache (incl compressed and secondary) and persistent cache (but
not table cache and row cache).

The goal is a really fast cache key with practically ideal stability and
uniqueness properties without external dependencies (e.g. from FileSystem).
A fixed key size of 16 bytes should enable future optimizations to the
concurrent hash table for block cache, which is a heavy CPU user /
bottleneck, but there appears to be measurable performance improvement
even with no changes to LRUCache.

This change replaces a lot of disjointed and ugly code handling cache
keys with calls to a simple, clean new internal API (cache_key.h).
(Preserving the old cache key logic under an option would be very ugly
and likely negate the performance gain of the new approach. Complete
replacement carries some inherent risk, but I think that's acceptable
with sufficient analysis and testing.)

The scheme for encoding new cache keys is complicated but explained
in cache_key.cc.

Also: EndianSwapValue is moved to math.h to be next to other bit
operations. (Explains some new include "math.h".) ReverseBits operation
added and unit tests added to hash_test for both.

Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause)

Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126

Test Plan:
### Basic correctness
Several tests needed updates to work with the new functionality, mostly
because we are no longer relying on filesystem for stable cache keys
so table builders & readers need more context info to agree on cache
keys. This functionality is so core, a huge number of existing tests
exercise the cache key functionality.

### Performance
Create db with
`TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters`
And test performance with
`TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4`
using DEBUG_LEVEL=0 and simultaneous before & after runs.
Before ops/sec, avg over 100 runs: 121924
After ops/sec, avg over 100 runs: 125385 (+2.8%)

### Collision probability
I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity
over many months, by making some pessimistic simplifying assumptions:
* Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys)
* All of every file is cached for its entire lifetime

We use a simple table with skewed address assignment and replacement on address collision
to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output
with `./cache_bench -stress_cache_key -sck_keep_bits=40`:

```
Total cache or DBs size: 32TiB  Writing 925.926 MiB/s or 76.2939TiB/day
Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached)
```

These come from default settings of 2.5M files per day of 32 MB each, and
`-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of
the 128-bit cache key.  With file size of 2\*\*25 contiguous keys (pessimistic), our simulation
is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality.

More default assumptions, relatively pessimistic:
* 100 DBs in same process (doesn't matter much)
* Re-open DB in same process (new session ID related to old session ID) on average
every 100 files generated
* Restart process (all new session IDs unrelated to old) 24 times per day

After enough data, we get a result at the end:

```
(keep 40 bits)  17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected)
```

If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data:

```
(keep 41 bits)  16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected)
(keep 42 bits)  19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected)
```

The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases:

```
197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected)
```

I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data.

Reviewed By: zhichao-cao

Differential Revision: D33171746

Pulled By: pdillinger

fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f
2021-12-16 17:15:13 -08:00
Zhichao Cao 6d93b87588 Add lowest_used_cache_tier to ImmutableDBOptions to enable or disable Secondary Cache (#9050)
Summary:
Currently, if Secondary Cache is provided to the lru cache, it is used by default. We add CacheTier to advanced_options.h to describe the cache tier we used. Add a `lowest_used_cache_tier` option to `DBOptions` (immutable) and pass it to BlockBasedTableReader to decide if secondary cache will be used or not. By default it is `CacheTier::kNonVolatileTier`, which means, we always use both block cache (kVolatileTier) and secondary cache (kNonVolatileTier). By set it to `CacheTier::kVolatileTier`, the DB will not use the secondary cache.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/9050

Test Plan: added new tests

Reviewed By: anand1976

Differential Revision: D31744769

Pulled By: zhichao-cao

fbshipit-source-id: a0575ebd23e1c6dfcfc2b4c8578764e73b15bce6
2021-10-19 15:54:23 -07:00
Zhichao Cao 699f45049d Introduce a mechanism to dump out blocks from block cache and re-insert to secondary cache (#8912)
Summary:
Background: Cache warming up will cause potential read performance degradation due to reading blocks from storage to the block cache. Since in production, the workload and access pattern to a certain DB is stable, it is a potential solution to dump out the blocks belonging to a certain DB to persist storage (e.g., to a file) and bulk-load the blocks to Secondary cache before the DB is relaunched. For example, when migrating a DB form host A to host B, it will take a short period of time, the access pattern to blocks in the block cache will not change much. It is efficient to dump out the blocks of certain DB, migrate to the destination host and insert them to the Secondary cache before we relaunch the DB.

Design: we introduce the interface of CacheDumpWriter and CacheDumpRead for user to store the blocks dumped out from block cache. RocksDB will encode all the information and send the string to the writer. User can implement their own writer it they want. CacheDumper and CacheLoad are introduced to save the blocks and load the blocks respectively.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/8912

Test Plan: add new tests to lru_cache_test and pass make check.

Reviewed By: pdillinger

Differential Revision: D31452871

Pulled By: zhichao-cao

fbshipit-source-id: 11ab4f5d03e383f476947116361d54188d36ec48
2021-10-07 11:42:31 -07:00
anand76 f35042ca40 Add a PerfContext counter for secondary cache hits (#8685)
Summary:
Add a PerfContext counter.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/8685

Reviewed By: zhichao-cao

Differential Revision: D30453957

Pulled By: anand1976

fbshipit-source-id: 42888a3ced240e1c44446d52d3b04adfb01f5665
2021-08-20 15:17:30 -07:00
anand76 add68bd28a Add a stat to count secondary cache hits (#8666)
Summary:
Add a stat for secondary cache hits. The ```Cache::Lookup``` API had an unused ```stats``` parameter. This PR uses that to pass the pointer to a ```Statistics``` object that ```LRUCache``` uses to record the stat.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/8666

Test Plan: Update a unit test in lru_cache_test

Reviewed By: zhichao-cao

Differential Revision: D30353816

Pulled By: anand1976

fbshipit-source-id: 2046f78b460428877a26ffdd2bb914ae47dfbe77
2021-08-16 21:01:14 -07:00
Drewryz 3b27725245 Fix a minor issue with initializing the test path (#8555)
Summary:
The PerThreadDBPath has already specified a slash. It does not need to be specified when initializing the test path.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/8555

Reviewed By: ajkr

Differential Revision: D29758399

Pulled By: jay-zhuang

fbshipit-source-id: 6d2b878523e3e8580536e2829cb25489844d9011
2021-07-23 08:38:45 -07:00
mrambacher 570248aeff Make SecondaryCache Customizable (#8480)
Summary: Pull Request resolved: https://github.com/facebook/rocksdb/pull/8480

Reviewed By: zhichao-cao

Differential Revision: D29528740

Pulled By: mrambacher

fbshipit-source-id: fd0f70d15f66611c8498257a9973f7e98ca13839
2021-07-06 09:18:08 -07:00
anand76 8ea0a2c1bd Parallelize secondary cache lookup in MultiGet (#8405)
Summary:
Implement the ```WaitAll()``` interface in ```LRUCache``` to allow callers to issue multiple lookups in parallel and wait for all of them to complete. Modify ```MultiGet``` to use this to parallelize the secondary cache lookups in order to reduce the overall latency. A call to ```cache->Lookup()``` returns a handle that has an incomplete value (nullptr), and the caller can call ```cache->IsReady()``` to check whether the lookup is complete, and pass a vector of handles to ```WaitAll``` to wait for completion. If any of the lookups fail, ```MultiGet``` will read the block from the SST file.

Another change in this PR is to rename ```SecondaryCacheHandle``` to ```SecondaryCacheResultHandle``` as it more accurately describes the return result of the secondary cache lookup, which is more like a future.

Tests:
1. Add unit tests in lru_cache_test
2. Benchmark results with no secondary cache configured
Master -
```
readrandom   :      41.175 micros/op 388562 ops/sec;  106.7 MB/s (7277999 of 7277999 found)
readrandom   :      41.217 micros/op 388160 ops/sec;  106.6 MB/s (7274999 of 7274999 found)
multireadrandom :      10.309 micros/op 1552082 ops/sec; (28908992 of 28908992 found)
multireadrandom :      10.321 micros/op 1550218 ops/sec; (29081984 of 29081984 found)
```

This PR -
```
readrandom   :      41.158 micros/op 388723 ops/sec;  106.8 MB/s (7290999 of 7290999 found)
readrandom   :      41.185 micros/op 388463 ops/sec;  106.7 MB/s (7287999 of 7287999 found)
multireadrandom :      10.277 micros/op 1556801 ops/sec; (29346944 of 29346944 found)
multireadrandom :      10.253 micros/op 1560539 ops/sec; (29274944 of 29274944 found)
```

Pull Request resolved: https://github.com/facebook/rocksdb/pull/8405

Reviewed By: zhichao-cao

Differential Revision: D29190509

Pulled By: anand1976

fbshipit-source-id: 6f8eff6246712af8a297cfe22ea0d1c3b2a01bb0
2021-06-18 09:35:59 -07:00