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
Summary:
I recently discovered that block cache keys are slightly lower
quality than previously thought, because my stress testing tool failed
to simulate the effect of DB ID differences. This change updates the
tool and gives us data to guide future developments. (No changes to
production code here and now.)
Nevertheless, the following promise still holds
```
// In fact, if our SST files are all < 4TB (see
// BlockBasedTable::kMaxFileSizeStandardEncoding), then SST files generated
// in a single process are guaranteed to have unique cache keys, unless/until
// number session ids * max file number = 2**86 ...
```
because although different DB IDs could cause collision in file number
and offset data, that would have to be using the same DB session (lower)
to cause a block cache key collision, which is not possible in the same
process. (A session is associated with only one DB ID.)
This change fixes cache_bench -stress_cache_key to set and reset DB IDs in
a parameterized way to evaluate the effect. Previous results assumed to
be representative (using -sck_keep_bits=43):
```
15 collisions after 15 x 90 days, est 90 days between (1.03763e+20 corrected)
```
or expected collision on a single machine every 104 billion billion
days (see "corrected" value).
After accounting for DB IDs, test never really changing, intermediate, and very
frequently changing (using default -sck_db_count=100):
```
-sck_newdb_nreopen=1000000000:
15 collisions after 2 x 90 days, est 12 days between (1.38351e+19 corrected)
-sck_newdb_nreopen=10000:
17 collisions after 2 x 90 days, est 10.5882 days between (1.22074e+19 corrected)
-sck_newdb_nreopen=100:
19 collisions after 2 x 90 days, est 9.47368 days between (1.09224e+19 corrected)
```
or roughly 10x more often than previously thought (still extremely if
not impossibly rare), and better than random base cache keys
(with -sck_randomize), though < 10x better than random:
```
31 collisions after 1 x 90 days, est 2.90323 days between (3.34719e+18 corrected)
```
If we simply fixed this by ignoring DB ID for cache keys, we would
potentially have a shortage of entropy for some cases, such as small
file numbers and offsets (e.g. many short-lived processes each using
SstFileWriter to create a small file), because existing DB session IDs
only provide ~103 bits of entropy. We could upgrade the entropy in DB
session IDs to accommodate, but it's not known what all would be
affected by changing from 20 digit session IDs to something larger.
Instead, my plan is to
1) Move to block cache keys derived from SST unique IDs (so that we can
derive block cache keys from manifest data without reading file on
storage), and show no significant regression in expected collision
rate.
2) Generate better SST unique IDs in format_version=6 (https://github.com/facebook/rocksdb/issues/9058),
which should have ~100x lower expected/predicted collision rate based
on simulations with this stress test:
```
./cache_bench -stress_cache_key -sck_keep_bits=39 -sck_newdb_nreopen=100 -sck_footer_unique_id
...
15 collisions after 19 x 90 days, est 114 days between (2.10293e+21 corrected)
```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10388
Test Plan: no production changes
Reviewed By: jay-zhuang
Differential Revision: D37986714
Pulled By: pdillinger
fbshipit-source-id: e759b2469e3365cb01c6661a69e0ab849ef4c3df
Summary:
Sometimes we may not want to include extra computation in our cache_bench experiments. Here we add a flag to avoid any extra work. We also moved the timer start after the key generation.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10363
Test Plan: Run cache_bench with and without the new flag and check that the appropriate code is being executed.
Reviewed By: pdillinger
Differential Revision: D37870416
Pulled By: guidotag
fbshipit-source-id: f853207b6643b9328e774251c3f679b1fd78a11a
Summary:
ClockCache is still in experimental stage, and currently fails some pre-release fbcode tests. See https://www.internalfb.com/diff/D37772011. API calls to construct ClockCache are done via the function NewClockCache. For now, NewClockCache calls will return an LRUCache (with appropriate arguments), which is stable.
The idea that NewClockCache returns nullptr was also floated, but this would be interpreted as unsupported cache, and a default LRUCache would be constructed instead, potentially causing a performance regression that is harder to identify.
A new version of the NewClockCache function was created for our internal tests.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10351
Test Plan: ``make -j24 check`` and re-run the pre-release tests.
Reviewed By: pdillinger
Differential Revision: D37802685
Pulled By: guidotag
fbshipit-source-id: 0a8d10612ff21e576f7360cb13e20bc36e244972
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
Summary:
cache_bench wasn't generating 16B keys, which are necessary for FastLRUCache. Also:
- Added asserts in cache_bench, which is assuming that inserts never fail. When they fail (for example, if we used keys of the wrong size), memory allocated to the values will becomes leaked, and eventually the program crashes.
- Move kCacheKeySize to the right spot.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10234
Test Plan:
``make -j24 check``. Also, run cache_bench with FastLRUCache and check that memory usage doesn't blow up:
``./cache_bench -cache_type=fast_lru_cache -num_shard_bits=6 -skewed=true \
-lookup_insert_percent=100 -lookup_percent=0 -insert_percent=0 -erase_percent=0 \
-populate_cache=true -cache_size=1073741824 -ops_per_thread=10000000 \
-value_bytes=8192 -resident_ratio=1 -threads=16``
Reviewed By: pdillinger
Differential Revision: D37382949
Pulled By: guidotag
fbshipit-source-id: b697a942ebb215de5d341f98dc8566763436ba9b
Summary:
folly DistributedMutex is faster than standard mutexes though
imposes some static obligations on usage. See
https://github.com/facebook/folly/blob/main/folly/synchronization/DistributedMutex.h
for details. Here we use this alternative for our Cache implementations
(especially LRUCache) for better locking performance, when RocksDB is
compiled with folly.
Also added information about which distributed mutex implementation is
being used to cache_bench output and to DB LOG.
Intended follow-up:
* Use DMutex in more places, perhaps improving API to support non-scoped
locking
* Fix linking with fbcode compiler (needs ROCKSDB_NO_FBCODE=1 currently)
Credit: Thanks Siying for reminding me about this line of work that was previously
left unfinished.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10179
Test Plan:
for correctness, existing tests. CircleCI config updated.
Also Meta-internal buck build updated.
For performance, ran simultaneous before & after cache_bench. Out of three
comparison runs, the middle improvement to ops/sec was +21%:
Baseline: USE_CLANG=1 DEBUG_LEVEL=0 make -j24 cache_bench (fbcode
compiler)
```
Complete in 20.201 s; Rough parallel ops/sec = 1584062
Thread ops/sec = 107176
Operation latency (ns):
Count: 32000000 Average: 9257.9421 StdDev: 122412.04
Min: 134 Median: 3623.0493 Max: 56918500
Percentiles: P50: 3623.05 P75: 10288.02 P99: 30219.35 P99.9: 683522.04 P99.99: 7302791.63
```
New: (add USE_FOLLY=1)
```
Complete in 16.674 s; Rough parallel ops/sec = 1919135 (+21%)
Thread ops/sec = 135487
Operation latency (ns):
Count: 32000000 Average: 7304.9294 StdDev: 108530.28
Min: 132 Median: 3777.6012 Max: 91030902
Percentiles: P50: 3777.60 P75: 10169.89 P99: 24504.51 P99.9: 59721.59 P99.99: 1861151.83
```
Reviewed By: anand1976
Differential Revision: D37182983
Pulled By: pdillinger
fbshipit-source-id: a17eb05f25b832b6a2c1356f5c657e831a5af8d1
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
Summary:
cache_bench can now run with FastLRUCache.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/10095
Test Plan:
- Temporarily add an ``assert(false)`` in the execution path that sets up the FastLRUCache. Run ``make -j24 cache_bench``. Then test the appropriate code is used by running ``./cache_bench -cache_type=fast_lru_cache`` and checking that the assert is called. Repeat for LRUCache.
- Verify that FastLRUCache (currently a clone of LRUCache) has similar latency distribution than LRUCache, by comparing the outputs of ``./cache_bench -cache_type=fast_lru_cache`` and ``./cache_bench -cache_type=lru_cache``.
Reviewed By: pdillinger
Differential Revision: D36875834
Pulled By: guidotag
fbshipit-source-id: eb2ad0bb32c2717a258a6ac66ed736e06f826cd8
Summary:
Follow-up to https://github.com/facebook/rocksdb/issues/9126
Added new unit tests to validate some of the claims of guaranteed uniqueness
within certain large bounds.
Also cleaned up the cache_bench -stress-cache-key tool with better comments
and description.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9329
Test Plan: no changes to production code
Reviewed By: mrambacher
Differential Revision: D33269328
Pulled By: pdillinger
fbshipit-source-id: 3a2b684a6b2b15f79dc872e563e3d16563be26de
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
Summary:
This PR adds a ```-secondary_cache_uri``` option to the cache_bench and db_bench tools to allow the user to specify a custom secondary cache URI. The object registry is used to create an instance of the ```SecondaryCache``` object of the type specified in the URI.
The main cache_bench code is packaged into a separate library, similar to db_bench.
An example invocation of db_bench with a secondary cache URI -
```db_bench --env_uri=ws://ws.flash_sandbox.vll1_2/ -db=anand/nvm_cache_2 -use_existing_db=true -benchmarks=readrandom -num=30000000 -key_size=32 -value_size=256 -use_direct_reads=true -cache_size=67108864 -cache_index_and_filter_blocks=true -secondary_cache_uri='cachelibwrapper://filename=/home/anand76/nvm_cache/cache_file;size=2147483648;regionSize=16777216;admPolicy=random;admProbability=1.0;volatileSize=8388608;bktPower=20;lockPower=12' -partition_index_and_filters=true -duration=1800```
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8312
Reviewed By: zhichao-cao
Differential Revision: D28544325
Pulled By: anand1976
fbshipit-source-id: 8f209b9af900c459dc42daa7a610d5f00176eeed
Summary:
Adds a new Cache::ApplyToAllEntries API that we expect to use
(in follow-up PRs) for efficiently gathering block cache statistics.
Notable features vs. old ApplyToAllCacheEntries:
* Includes key and deleter (in addition to value and charge). We could
have passed in a Handle but then more virtual function calls would be
needed to get the "fields" of each entry. We expect to use the 'deleter'
to identify the origin of entries, perhaps even more.
* Heavily tuned to minimize latency impact on operating cache. It
does this by iterating over small sections of each cache shard while
cycling through the shards.
* Supports tuning roughly how many entries to operate on for each
lock acquire and release, to control the impact on the latency of other
operations without excessive lock acquire & release. The right balance
can depend on the cost of the callback. Good default seems to be
around 256.
* There should be no need to disable thread safety. (I would expect
uncontended locks to be sufficiently fast.)
I have enhanced cache_bench to validate this approach:
* Reports a histogram of ns per operation, so we can look at the
ditribution of times, not just throughput (average).
* Can add a thread for simulated "gather stats" which calls
ApplyToAllEntries at a specified interval. We also generate a histogram
of time to run ApplyToAllEntries.
To make the iteration over some entries of each shard work as cleanly as
possible, even with resize between next set of entries, I have
re-arranged which hash bits are used for sharding and which for indexing
within a shard.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/8225
Test Plan:
A couple of unit tests are added, but primary validation is manual, as
the primary risk is to performance.
The primary validation is using cache_bench to ensure that neither
the minor hashing changes nor the simulated stats gathering
significantly impact QPS or latency distribution. Note that adding op
latency histogram seriously impacts the benchmark QPS, so for a
fair baseline, we need the cache_bench changes (except remove simulated
stat gathering to make it compile). In short, we don't see any
reproducible difference in ops/sec or op latency unless we are gathering
stats nearly continuously. Test uses 10GB block cache with
8KB values to be somewhat realistic in the number of items to iterate
over.
Baseline typical output:
```
Complete in 92.017 s; Rough parallel ops/sec = 869401
Thread ops/sec = 54662
Operation latency (ns):
Count: 80000000 Average: 11223.9494 StdDev: 29.61
Min: 0 Median: 7759.3973 Max: 9620500
Percentiles: P50: 7759.40 P75: 14190.73 P99: 46922.75 P99.9: 77509.84 P99.99: 217030.58
------------------------------------------------------
[ 0, 1 ] 68 0.000% 0.000%
( 2900, 4400 ] 89 0.000% 0.000%
( 4400, 6600 ] 33630240 42.038% 42.038% ########
( 6600, 9900 ] 18129842 22.662% 64.700% #####
( 9900, 14000 ] 7877533 9.847% 74.547% ##
( 14000, 22000 ] 15193238 18.992% 93.539% ####
( 22000, 33000 ] 3037061 3.796% 97.335% #
( 33000, 50000 ] 1626316 2.033% 99.368%
( 50000, 75000 ] 421532 0.527% 99.895%
( 75000, 110000 ] 56910 0.071% 99.966%
( 110000, 170000 ] 16134 0.020% 99.986%
( 170000, 250000 ] 5166 0.006% 99.993%
( 250000, 380000 ] 3017 0.004% 99.996%
( 380000, 570000 ] 1337 0.002% 99.998%
( 570000, 860000 ] 805 0.001% 99.999%
( 860000, 1200000 ] 319 0.000% 100.000%
( 1200000, 1900000 ] 231 0.000% 100.000%
( 1900000, 2900000 ] 100 0.000% 100.000%
( 2900000, 4300000 ] 39 0.000% 100.000%
( 4300000, 6500000 ] 16 0.000% 100.000%
( 6500000, 9800000 ] 7 0.000% 100.000%
```
New, gather_stats=false. Median thread ops/sec of 5 runs:
```
Complete in 92.030 s; Rough parallel ops/sec = 869285
Thread ops/sec = 54458
Operation latency (ns):
Count: 80000000 Average: 11298.1027 StdDev: 42.18
Min: 0 Median: 7722.0822 Max: 6398720
Percentiles: P50: 7722.08 P75: 14294.68 P99: 47522.95 P99.9: 85292.16 P99.99: 228077.78
------------------------------------------------------
[ 0, 1 ] 109 0.000% 0.000%
( 2900, 4400 ] 793 0.001% 0.001%
( 4400, 6600 ] 34054563 42.568% 42.569% #########
( 6600, 9900 ] 17482646 21.853% 64.423% ####
( 9900, 14000 ] 7908180 9.885% 74.308% ##
( 14000, 22000 ] 15032072 18.790% 93.098% ####
( 22000, 33000 ] 3237834 4.047% 97.145% #
( 33000, 50000 ] 1736882 2.171% 99.316%
( 50000, 75000 ] 446851 0.559% 99.875%
( 75000, 110000 ] 68251 0.085% 99.960%
( 110000, 170000 ] 18592 0.023% 99.983%
( 170000, 250000 ] 7200 0.009% 99.992%
( 250000, 380000 ] 3334 0.004% 99.997%
( 380000, 570000 ] 1393 0.002% 99.998%
( 570000, 860000 ] 700 0.001% 99.999%
( 860000, 1200000 ] 293 0.000% 100.000%
( 1200000, 1900000 ] 196 0.000% 100.000%
( 1900000, 2900000 ] 69 0.000% 100.000%
( 2900000, 4300000 ] 32 0.000% 100.000%
( 4300000, 6500000 ] 10 0.000% 100.000%
```
New, gather_stats=true, 1 second delay between scans. Scans take about
1 second here so it's spending about 50% time scanning. Still the effect on
ops/sec and latency seems to be in the noise. Median thread ops/sec of 5 runs:
```
Complete in 91.890 s; Rough parallel ops/sec = 870608
Thread ops/sec = 54551
Operation latency (ns):
Count: 80000000 Average: 11311.2629 StdDev: 45.28
Min: 0 Median: 7686.5458 Max: 10018340
Percentiles: P50: 7686.55 P75: 14481.95 P99: 47232.60 P99.9: 79230.18 P99.99: 232998.86
------------------------------------------------------
[ 0, 1 ] 71 0.000% 0.000%
( 2900, 4400 ] 291 0.000% 0.000%
( 4400, 6600 ] 34492060 43.115% 43.116% #########
( 6600, 9900 ] 16727328 20.909% 64.025% ####
( 9900, 14000 ] 7845828 9.807% 73.832% ##
( 14000, 22000 ] 15510654 19.388% 93.220% ####
( 22000, 33000 ] 3216533 4.021% 97.241% #
( 33000, 50000 ] 1680859 2.101% 99.342%
( 50000, 75000 ] 439059 0.549% 99.891%
( 75000, 110000 ] 60540 0.076% 99.967%
( 110000, 170000 ] 14649 0.018% 99.985%
( 170000, 250000 ] 5242 0.007% 99.991%
( 250000, 380000 ] 3260 0.004% 99.995%
( 380000, 570000 ] 1599 0.002% 99.997%
( 570000, 860000 ] 1043 0.001% 99.999%
( 860000, 1200000 ] 471 0.001% 99.999%
( 1200000, 1900000 ] 275 0.000% 100.000%
( 1900000, 2900000 ] 143 0.000% 100.000%
( 2900000, 4300000 ] 60 0.000% 100.000%
( 4300000, 6500000 ] 27 0.000% 100.000%
( 6500000, 9800000 ] 7 0.000% 100.000%
( 9800000, 14000000 ] 1 0.000% 100.000%
Gather stats latency (us):
Count: 46 Average: 980387.5870 StdDev: 60911.18
Min: 879155 Median: 1033777.7778 Max: 1261431
Percentiles: P50: 1033777.78 P75: 1120666.67 P99: 1261431.00 P99.9: 1261431.00 P99.99: 1261431.00
------------------------------------------------------
( 860000, 1200000 ] 45 97.826% 97.826% ####################
( 1200000, 1900000 ] 1 2.174% 100.000%
Most recent cache entry stats:
Number of entries: 1295133
Total charge: 9.88 GB
Average key size: 23.4982
Average charge: 8.00 KB
Unique deleters: 3
```
Reviewed By: mrambacher
Differential Revision: D28295742
Pulled By: pdillinger
fbshipit-source-id: bbc4a552f91ba0fe10e5cc025c42cef5a81f2b95
Summary:
Introduces and uses a SystemClock class to RocksDB. This class contains the time-related functions of an Env and these functions can be redirected from the Env to the SystemClock.
Many of the places that used an Env (Timer, PerfStepTimer, RepeatableThread, RateLimiter, WriteController) for time-related functions have been changed to use SystemClock instead. There are likely more places that can be changed, but this is a start to show what can/should be done. Over time it would be nice to migrate most (if not all) of the uses of the time functions from the Env to the SystemClock.
There are several Env classes that implement these functions. Most of these have not been converted yet to SystemClock implementations; that will come in a subsequent PR. It would be good to unify many of the Mock Timer implementations, so that they behave similarly and be tested similarly (some override Sleep, some use a MockSleep, etc).
Additionally, this change will allow new methods to be introduced to the SystemClock (like https://github.com/facebook/rocksdb/issues/7101 WaitFor) in a consistent manner across a smaller number of classes.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7858
Reviewed By: pdillinger
Differential Revision: D26006406
Pulled By: mrambacher
fbshipit-source-id: ed10a8abbdab7ff2e23d69d85bd25b3e7e899e90
Summary:
A generic algorithm in progress depends on a templatized
version of fastrange, so this change generalizes it and renames
it to fit our style guidelines, FastRange32, FastRange64, and now
FastRangeGeneric.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/7436
Test Plan: added a few more test cases
Reviewed By: jay-zhuang
Differential Revision: D23958153
Pulled By: pdillinger
fbshipit-source-id: 8c3b76101653417804997e5f076623a25586f3e8
Summary:
I suspect LRUCache could use some optimization, and to support
such an effort, a good benchmarking tool is needed. The existing
cache_bench was heavily skewed toward insertion and lookup misses, and
did not saturate memory with other work. This change should improve
those things to better resemble a real workload.
(All below using clang compiler, for some consistency, but not
necessarily same version and settings.)
The real workload is from production MySQL on RocksDB, filtering stacks
containing "LRU", "ShardedCache" or "CacheShard."
Lookup inclusive: 66%
Insert inclusive: 17%
Release inclusive: 15%
An alternate simulated workload is MySQL running a LinkBench read test:
Lookup inclusive: 54%
Insert inclusive: 24%
Release inclusive: 21%
cache_bench default settings, prior to this change:
Lookup inclusive: 35.8%
Insert inclusive: 63.6%
Release inclusive: 0%
cache_bench after this change (intended as somewhat "tighter" workload
than average production, more like LinkBench):
Lookup inclusive: 52%
Insert inclusive: 20%
Release inclusive: 26%
And top exclusive stacks (portion of stack samples as filtered above):
Production MySQL:
LRUHandleTable::FindPointer: 25.3%
rocksdb::operator==: 15.1% <-- Slice ==
LRUCacheShard::LRU_Remove: 13.8%
ShardedCache::Lookup: 8.9%
__pthread_mutex_lock: 7.1%
LRUCacheShard::LRU_Insert: 6.3%
MurmurHash64A: 4.8% <-- Since upgraded to XXH3p
...
Old cache_bench:
LRUHandleTable::FindPointer: 23.6%
__pthread_mutex_lock: 15.0%
__pthread_mutex_unlock_usercnt: 11.7%
__lll_lock_wait: 8.6%
__lll_unlock_wake: 6.8%
LRUCacheShard::LRU_Insert: 6.0%
ShardedCache::Lookup: 4.4%
LRUCacheShard::LRU_Remove: 2.8%
...
rocksdb::operator==: 0.2% <-- Slice ==
...
New cache_bench:
LRUHandleTable::FindPointer: 22.8%
__pthread_mutex_unlock_usercnt: 14.3%
rocksdb::operator==: 10.5% <-- Slice ==
LRUCacheShard::LRU_Insert: 9.0%
__pthread_mutex_lock: 5.9%
LRUCacheShard::LRU_Remove: 5.0%
...
ShardedCache::Lookup: 2.9%
...
So there's a bit more lock contention in the benchmark than in
production, but otherwise looks similar enough to me. At least it's a
big improvement over the existing code.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6629
Test Plan: No production code changes, ran cache_bench with ASAN
Reviewed By: ltamasi
Differential Revision: D20824318
Pulled By: pdillinger
fbshipit-source-id: 6f8dc5891ead0f87edbed3a615ecd5289d9abe12
Summary:
As the first step of reintroducing eviction statistics for the block
cache, the patch switches from using simple function pointers as deleters
to function objects implementing an interface. This will enable using
deleters that have state, like a smart pointer to the statistics object
that is to be updated when an entry is removed from the cache. For now,
the patch adds a deleter template class `SimpleDeleter`, which simply
casts the `value` pointer to its original type and calls `delete` or
`delete[]` on it as appropriate. Note: to prevent object lifecycle
issues, deleters must outlive the cache entries referring to them;
`SimpleDeleter` ensures this by using the ("leaky") Meyers singleton
pattern.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6545
Test Plan: `make asan_check`
Reviewed By: siying
Differential Revision: D20475823
Pulled By: ltamasi
fbshipit-source-id: fe354c33dd96d9bafc094605462352305449a22a
Summary:
When dynamically linking two binaries together, different builds of RocksDB from two sources might cause errors. To provide a tool for user to solve the problem, the RocksDB namespace is changed to a flag which can be overridden in build time.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6433
Test Plan: Build release, all and jtest. Try to build with ROCKSDB_NAMESPACE with another flag.
Differential Revision: D19977691
fbshipit-source-id: aa7f2d0972e1c31d75339ac48478f34f6cfcfb3e
Summary:
Further apply formatter to more recent commits.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5830
Test Plan: Run all existing tests.
Differential Revision: D17488031
fbshipit-source-id: 137458fd94d56dd271b8b40c522b03036943a2ab
Summary:
When using `PRIu64` type of printf specifier, current code base does the following:
```
#ifndef __STDC_FORMAT_MACROS
#define __STDC_FORMAT_MACROS
#endif
#include <inttypes.h>
```
However, this can be simplified to
```
#include <cinttypes>
```
as long as flag `-std=c++11` is used.
This should solve issues like https://github.com/facebook/rocksdb/issues/5159
Pull Request resolved: https://github.com/facebook/rocksdb/pull/5402
Differential Revision: D15701195
Pulled By: miasantreble
fbshipit-source-id: 6dac0a05f52aadb55e9728038599d3d2e4b59d03
Summary:
This PR comments out the rest of the unused arguments which allow us to turn on the -Wunused-parameter flag. This is the second part of a codemod relating to https://github.com/facebook/rocksdb/pull/3557.
Closes https://github.com/facebook/rocksdb/pull/3662
Differential Revision: D7426121
Pulled By: Dayvedde
fbshipit-source-id: 223994923b42bd4953eb016a0129e47560f7e352
Summary:
I started adding gflags support for cmake on linux and got frustrated that I'd need to duplicate the build_detect_platform logic, which determines namespace based on attempting compilation. We can do it differently -- use the GFLAGS_NAMESPACE macro if available, and if not, that indicates it's an old gflags version without configurable namespace so we can simply hardcode "google".
Closes https://github.com/facebook/rocksdb/pull/3212
Differential Revision: D6456973
Pulled By: ajkr
fbshipit-source-id: 3e6d5bde3ca00d4496a120a7caf4687399f5d656
Summary:
Move some files under util/ to new directories env/, monitoring/ options/ and cache/
Closes https://github.com/facebook/rocksdb/pull/2090
Differential Revision: D4833681
Pulled By: siying
fbshipit-source-id: 2fd8bef
Summary:
Clock-based cache implemenetation aim to have better concurreny than
default LRU cache. See inline comments for implementation details.
Test Plan:
Update cache_test to run on both LRUCache and ClockCache. Adding some
new tests to catch some of the bugs that I fixed while implementing the
cache.
Reviewers: kradhakrishnan, sdong
Reviewed By: sdong
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D61647
Summary:
Cache to have an option to fail Cache::Insert() when full. Update call sites to check status and handle error.
I totally have no idea what's correct behavior of all the call sites when they encounter error. Please let me know if you see something wrong or more unit test is needed.
Test Plan: make check -j32, see tests pass.
Reviewers: anthony, yhchiang, andrewkr, IslamAbdelRahman, kradhakrishnan, sdong
Reviewed By: sdong
Subscribers: andrewkr, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D54705
Summary: Previously I made `make check` work with -Wshadow, but there are some tools that are not compiled using `make check`.
Test Plan: make all
Reviewers: yhchiang, rven, ljin, sdong
Reviewed By: ljin, sdong
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D28497
Peter Dillinger