|
|
|
// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
|
|
|
|
// This source code is licensed under both the GPLv2 (found in the
|
|
|
|
// COPYING file in the root directory) and Apache 2.0 License
|
|
|
|
// (found in the LICENSE.Apache file in the root directory).
|
|
|
|
|
|
|
|
#ifdef GFLAGS
|
|
|
|
#include <cinttypes>
|
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
3 years ago
|
|
|
#include <cstddef>
|
|
|
|
#include <cstdio>
|
|
|
|
#include <limits>
|
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
3 years ago
|
|
|
#include <memory>
|
|
|
|
#include <set>
|
|
|
|
#include <sstream>
|
|
|
|
|
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
3 years ago
|
|
|
#include "db/db_impl/db_impl.h"
|
|
|
|
#include "monitoring/histogram.h"
|
|
|
|
#include "port/port.h"
|
|
|
|
#include "rocksdb/cache.h"
|
|
|
|
#include "rocksdb/convenience.h"
|
|
|
|
#include "rocksdb/db.h"
|
|
|
|
#include "rocksdb/env.h"
|
|
|
|
#include "rocksdb/secondary_cache.h"
|
|
|
|
#include "rocksdb/system_clock.h"
|
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
3 years ago
|
|
|
#include "rocksdb/table_properties.h"
|
|
|
|
#include "table/block_based/block_based_table_reader.h"
|
|
|
|
#include "table/block_based/cachable_entry.h"
|
|
|
|
#include "util/coding.h"
|
|
|
|
#include "util/gflags_compat.h"
|
|
|
|
#include "util/hash.h"
|
|
|
|
#include "util/mutexlock.h"
|
|
|
|
#include "util/random.h"
|
|
|
|
#include "util/stop_watch.h"
|
|
|
|
#include "util/string_util.h"
|
|
|
|
|
|
|
|
using GFLAGS_NAMESPACE::ParseCommandLineFlags;
|
|
|
|
|
|
|
|
static constexpr uint32_t KiB = uint32_t{1} << 10;
|
|
|
|
static constexpr uint32_t MiB = KiB << 10;
|
|
|
|
static constexpr uint64_t GiB = MiB << 10;
|
|
|
|
|
|
|
|
DEFINE_uint32(threads, 16, "Number of concurrent threads to run.");
|
|
|
|
DEFINE_uint64(cache_size, 1 * GiB,
|
|
|
|
"Number of bytes to use as a cache of uncompressed data.");
|
|
|
|
DEFINE_uint32(num_shard_bits, 6, "shard_bits.");
|
|
|
|
|
|
|
|
DEFINE_double(resident_ratio, 0.25,
|
|
|
|
"Ratio of keys fitting in cache to keyspace.");
|
|
|
|
DEFINE_uint64(ops_per_thread, 2000000U, "Number of operations per thread.");
|
|
|
|
DEFINE_uint32(value_bytes, 8 * KiB, "Size of each value added.");
|
|
|
|
|
|
|
|
DEFINE_uint32(skew, 5, "Degree of skew in key selection");
|
|
|
|
DEFINE_bool(populate_cache, true, "Populate cache before operations");
|
|
|
|
|
|
|
|
DEFINE_uint32(lookup_insert_percent, 87,
|
|
|
|
"Ratio of lookup (+ insert on not found) to total workload "
|
|
|
|
"(expressed as a percentage)");
|
|
|
|
DEFINE_uint32(insert_percent, 2,
|
|
|
|
"Ratio of insert to total workload (expressed as a percentage)");
|
|
|
|
DEFINE_uint32(lookup_percent, 10,
|
|
|
|
"Ratio of lookup to total workload (expressed as a percentage)");
|
|
|
|
DEFINE_uint32(erase_percent, 1,
|
|
|
|
"Ratio of erase to total workload (expressed as a percentage)");
|
|
|
|
DEFINE_bool(gather_stats, false,
|
|
|
|
"Whether to periodically simulate gathering block cache stats, "
|
|
|
|
"using one more thread.");
|
|
|
|
DEFINE_uint32(
|
|
|
|
gather_stats_sleep_ms, 1000,
|
|
|
|
"How many milliseconds to sleep between each gathering of stats.");
|
|
|
|
|
|
|
|
DEFINE_uint32(gather_stats_entries_per_lock, 256,
|
|
|
|
"For Cache::ApplyToAllEntries");
|
|
|
|
DEFINE_bool(skewed, false, "If true, skew the key access distribution");
|
|
|
|
#ifndef ROCKSDB_LITE
|
|
|
|
DEFINE_string(secondary_cache_uri, "",
|
|
|
|
"Full URI for creating a custom secondary cache object");
|
|
|
|
static class std::shared_ptr<ROCKSDB_NAMESPACE::SecondaryCache> secondary_cache;
|
|
|
|
#endif // ROCKSDB_LITE
|
|
|
|
|
|
|
|
DEFINE_bool(use_clock_cache, false, "");
|
|
|
|
|
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
3 years ago
|
|
|
// ## BEGIN stress_cache_key sub-tool options ##
|
|
|
|
DEFINE_bool(stress_cache_key, false,
|
|
|
|
"If true, run cache key stress test instead");
|
|
|
|
DEFINE_uint32(sck_files_per_day, 2500000,
|
|
|
|
"(-stress_cache_key) Simulated files generated per day");
|
|
|
|
DEFINE_uint32(sck_duration, 90,
|
|
|
|
"(-stress_cache_key) Number of days to simulate in each run");
|
|
|
|
DEFINE_uint32(
|
|
|
|
sck_min_collision, 15,
|
|
|
|
"(-stress_cache_key) Keep running until this many collisions seen");
|
|
|
|
DEFINE_uint32(
|
|
|
|
sck_file_size_mb, 32,
|
|
|
|
"(-stress_cache_key) Simulated file size in MiB, for accounting purposes");
|
|
|
|
DEFINE_uint32(sck_reopen_nfiles, 100,
|
|
|
|
"(-stress_cache_key) Re-opens DB average every n files");
|
|
|
|
DEFINE_uint32(
|
|
|
|
sck_restarts_per_day, 24,
|
|
|
|
"(-stress_cache_key) Simulated process restarts per day (across DBs)");
|
|
|
|
DEFINE_uint32(sck_db_count, 100,
|
|
|
|
"(-stress_cache_key) Parallel DBs in operation");
|
|
|
|
DEFINE_uint32(sck_table_bits, 20,
|
|
|
|
"(-stress_cache_key) Log2 number of tracked files");
|
|
|
|
DEFINE_uint32(sck_keep_bits, 50,
|
|
|
|
"(-stress_cache_key) Number of cache key bits to keep");
|
|
|
|
DEFINE_bool(sck_randomize, false,
|
|
|
|
"(-stress_cache_key) Randomize (hash) cache key");
|
|
|
|
DEFINE_bool(sck_footer_unique_id, false,
|
|
|
|
"(-stress_cache_key) Simulate using proposed footer unique id");
|
|
|
|
// ## END stress_cache_key sub-tool options ##
|
|
|
|
|
|
|
|
namespace ROCKSDB_NAMESPACE {
|
|
|
|
|
|
|
|
class CacheBench;
|
|
|
|
namespace {
|
|
|
|
// State shared by all concurrent executions of the same benchmark.
|
|
|
|
class SharedState {
|
|
|
|
public:
|
|
|
|
explicit SharedState(CacheBench* cache_bench)
|
|
|
|
: cv_(&mu_),
|
|
|
|
num_initialized_(0),
|
|
|
|
start_(false),
|
|
|
|
num_done_(0),
|
|
|
|
cache_bench_(cache_bench) {}
|
|
|
|
|
|
|
|
~SharedState() {}
|
|
|
|
|
|
|
|
port::Mutex* GetMutex() { return &mu_; }
|
|
|
|
|
|
|
|
port::CondVar* GetCondVar() { return &cv_; }
|
|
|
|
|
|
|
|
CacheBench* GetCacheBench() const { return cache_bench_; }
|
|
|
|
|
|
|
|
void IncInitialized() { num_initialized_++; }
|
|
|
|
|
|
|
|
void IncDone() { num_done_++; }
|
|
|
|
|
|
|
|
bool AllInitialized() const { return num_initialized_ >= FLAGS_threads; }
|
|
|
|
|
|
|
|
bool AllDone() const { return num_done_ >= FLAGS_threads; }
|
|
|
|
|
|
|
|
void SetStart() { start_ = true; }
|
|
|
|
|
|
|
|
bool Started() const { return start_; }
|
|
|
|
|
|
|
|
private:
|
|
|
|
port::Mutex mu_;
|
|
|
|
port::CondVar cv_;
|
|
|
|
|
|
|
|
uint64_t num_initialized_;
|
|
|
|
bool start_;
|
|
|
|
uint64_t num_done_;
|
|
|
|
|
|
|
|
CacheBench* cache_bench_;
|
|
|
|
};
|
|
|
|
|
|
|
|
// Per-thread state for concurrent executions of the same benchmark.
|
|
|
|
struct ThreadState {
|
|
|
|
uint32_t tid;
|
|
|
|
Random64 rnd;
|
|
|
|
SharedState* shared;
|
|
|
|
HistogramImpl latency_ns_hist;
|
|
|
|
uint64_t duration_us = 0;
|
|
|
|
|
|
|
|
ThreadState(uint32_t index, SharedState* _shared)
|
|
|
|
: tid(index), rnd(1000 + index), shared(_shared) {}
|
|
|
|
};
|
|
|
|
|
|
|
|
struct KeyGen {
|
|
|
|
char key_data[27];
|
|
|
|
|
|
|
|
Slice GetRand(Random64& rnd, uint64_t max_key, int max_log) {
|
|
|
|
uint64_t key = 0;
|
|
|
|
if (!FLAGS_skewed) {
|
|
|
|
uint64_t raw = rnd.Next();
|
|
|
|
// Skew according to setting
|
|
|
|
for (uint32_t i = 0; i < FLAGS_skew; ++i) {
|
|
|
|
raw = std::min(raw, rnd.Next());
|
|
|
|
}
|
|
|
|
key = FastRange64(raw, max_key);
|
|
|
|
} else {
|
|
|
|
key = rnd.Skewed(max_log);
|
|
|
|
if (key > max_key) {
|
|
|
|
key -= max_key;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
// Variable size and alignment
|
|
|
|
size_t off = key % 8;
|
|
|
|
key_data[0] = char{42};
|
|
|
|
EncodeFixed64(key_data + 1, key);
|
|
|
|
key_data[9] = char{11};
|
|
|
|
EncodeFixed64(key_data + 10, key);
|
|
|
|
key_data[18] = char{4};
|
|
|
|
EncodeFixed64(key_data + 19, key);
|
|
|
|
return Slice(&key_data[off], sizeof(key_data) - off);
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
char* createValue(Random64& rnd) {
|
|
|
|
char* rv = new char[FLAGS_value_bytes];
|
|
|
|
// Fill with some filler data, and take some CPU time
|
|
|
|
for (uint32_t i = 0; i < FLAGS_value_bytes; i += 8) {
|
|
|
|
EncodeFixed64(rv + i, rnd.Next());
|
|
|
|
}
|
|
|
|
return rv;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Callbacks for secondary cache
|
|
|
|
size_t SizeFn(void* /*obj*/) { return FLAGS_value_bytes; }
|
|
|
|
|
|
|
|
Status SaveToFn(void* obj, size_t /*offset*/, size_t size, void* out) {
|
|
|
|
memcpy(out, obj, size);
|
|
|
|
return Status::OK();
|
|
|
|
}
|
|
|
|
|
|
|
|
// Different deleters to simulate using deleter to gather
|
|
|
|
// stats on the code origin and kind of cache entries.
|
|
|
|
void deleter1(const Slice& /*key*/, void* value) {
|
|
|
|
delete[] static_cast<char*>(value);
|
|
|
|
}
|
|
|
|
void deleter2(const Slice& /*key*/, void* value) {
|
|
|
|
delete[] static_cast<char*>(value);
|
|
|
|
}
|
|
|
|
void deleter3(const Slice& /*key*/, void* value) {
|
|
|
|
delete[] static_cast<char*>(value);
|
|
|
|
}
|
|
|
|
|
|
|
|
Cache::CacheItemHelper helper1(SizeFn, SaveToFn, deleter1);
|
|
|
|
Cache::CacheItemHelper helper2(SizeFn, SaveToFn, deleter2);
|
|
|
|
Cache::CacheItemHelper helper3(SizeFn, SaveToFn, deleter3);
|
|
|
|
} // namespace
|
|
|
|
|
|
|
|
class CacheBench {
|
|
|
|
static constexpr uint64_t kHundredthUint64 =
|
|
|
|
std::numeric_limits<uint64_t>::max() / 100U;
|
|
|
|
|
|
|
|
public:
|
|
|
|
CacheBench()
|
|
|
|
: max_key_(static_cast<uint64_t>(FLAGS_cache_size / FLAGS_resident_ratio /
|
|
|
|
FLAGS_value_bytes)),
|
|
|
|
lookup_insert_threshold_(kHundredthUint64 *
|
|
|
|
FLAGS_lookup_insert_percent),
|
|
|
|
insert_threshold_(lookup_insert_threshold_ +
|
|
|
|
kHundredthUint64 * FLAGS_insert_percent),
|
|
|
|
lookup_threshold_(insert_threshold_ +
|
|
|
|
kHundredthUint64 * FLAGS_lookup_percent),
|
|
|
|
erase_threshold_(lookup_threshold_ +
|
|
|
|
kHundredthUint64 * FLAGS_erase_percent),
|
|
|
|
skewed_(FLAGS_skewed) {
|
|
|
|
if (erase_threshold_ != 100U * kHundredthUint64) {
|
|
|
|
fprintf(stderr, "Percentages must add to 100.\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
|
|
|
|
max_log_ = 0;
|
|
|
|
if (skewed_) {
|
|
|
|
uint64_t max_key = max_key_;
|
|
|
|
while (max_key >>= 1) max_log_++;
|
|
|
|
if (max_key > (static_cast<uint64_t>(1) << max_log_)) max_log_++;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (FLAGS_use_clock_cache) {
|
|
|
|
cache_ = NewClockCache(FLAGS_cache_size, FLAGS_num_shard_bits);
|
|
|
|
if (!cache_) {
|
|
|
|
fprintf(stderr, "Clock cache not supported.\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
} else {
|
|
|
|
LRUCacheOptions opts(FLAGS_cache_size, FLAGS_num_shard_bits, false, 0.5);
|
|
|
|
#ifndef ROCKSDB_LITE
|
|
|
|
if (!FLAGS_secondary_cache_uri.empty()) {
|
|
|
|
Status s = SecondaryCache::CreateFromString(
|
|
|
|
ConfigOptions(), FLAGS_secondary_cache_uri, &secondary_cache);
|
|
|
|
if (secondary_cache == nullptr) {
|
|
|
|
fprintf(
|
|
|
|
stderr,
|
|
|
|
"No secondary cache registered matching string: %s status=%s\n",
|
|
|
|
FLAGS_secondary_cache_uri.c_str(), s.ToString().c_str());
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
opts.secondary_cache = secondary_cache;
|
|
|
|
}
|
|
|
|
#endif // ROCKSDB_LITE
|
|
|
|
|
|
|
|
cache_ = NewLRUCache(opts);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
~CacheBench() {}
|
|
|
|
|
|
|
|
void PopulateCache() {
|
|
|
|
Random64 rnd(1);
|
|
|
|
KeyGen keygen;
|
|
|
|
for (uint64_t i = 0; i < 2 * FLAGS_cache_size; i += FLAGS_value_bytes) {
|
|
|
|
cache_->Insert(keygen.GetRand(rnd, max_key_, max_log_), createValue(rnd),
|
|
|
|
&helper1, FLAGS_value_bytes);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
bool Run() {
|
|
|
|
const auto clock = SystemClock::Default().get();
|
|
|
|
|
|
|
|
PrintEnv();
|
|
|
|
SharedState shared(this);
|
|
|
|
std::vector<std::unique_ptr<ThreadState> > threads(FLAGS_threads);
|
|
|
|
for (uint32_t i = 0; i < FLAGS_threads; i++) {
|
|
|
|
threads[i].reset(new ThreadState(i, &shared));
|
|
|
|
std::thread(ThreadBody, threads[i].get()).detach();
|
|
|
|
}
|
|
|
|
|
|
|
|
HistogramImpl stats_hist;
|
|
|
|
std::string stats_report;
|
|
|
|
std::thread stats_thread(StatsBody, &shared, &stats_hist, &stats_report);
|
|
|
|
|
|
|
|
uint64_t start_time;
|
|
|
|
{
|
|
|
|
MutexLock l(shared.GetMutex());
|
|
|
|
while (!shared.AllInitialized()) {
|
|
|
|
shared.GetCondVar()->Wait();
|
|
|
|
}
|
|
|
|
// Record start time
|
|
|
|
start_time = clock->NowMicros();
|
|
|
|
|
|
|
|
// Start all threads
|
|
|
|
shared.SetStart();
|
|
|
|
shared.GetCondVar()->SignalAll();
|
|
|
|
|
|
|
|
// Wait threads to complete
|
|
|
|
while (!shared.AllDone()) {
|
|
|
|
shared.GetCondVar()->Wait();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Stats gathering is considered background work. This time measurement
|
|
|
|
// is for foreground work, and not really ideal for that. See below.
|
|
|
|
uint64_t end_time = clock->NowMicros();
|
|
|
|
stats_thread.join();
|
|
|
|
|
|
|
|
// Wall clock time - includes idle time if threads
|
|
|
|
// finish at different times (not ideal).
|
|
|
|
double elapsed_secs = static_cast<double>(end_time - start_time) * 1e-6;
|
|
|
|
uint32_t ops_per_sec = static_cast<uint32_t>(
|
|
|
|
1.0 * FLAGS_threads * FLAGS_ops_per_thread / elapsed_secs);
|
|
|
|
printf("Complete in %.3f s; Rough parallel ops/sec = %u\n", elapsed_secs,
|
|
|
|
ops_per_sec);
|
|
|
|
|
|
|
|
// Total time in each thread (more accurate throughput measure)
|
|
|
|
elapsed_secs = 0;
|
|
|
|
for (uint32_t i = 0; i < FLAGS_threads; i++) {
|
|
|
|
elapsed_secs += threads[i]->duration_us * 1e-6;
|
|
|
|
}
|
|
|
|
ops_per_sec = static_cast<uint32_t>(1.0 * FLAGS_threads *
|
|
|
|
FLAGS_ops_per_thread / elapsed_secs);
|
|
|
|
printf("Thread ops/sec = %u\n", ops_per_sec);
|
|
|
|
|
|
|
|
printf("\nOperation latency (ns):\n");
|
|
|
|
HistogramImpl combined;
|
|
|
|
for (uint32_t i = 0; i < FLAGS_threads; i++) {
|
|
|
|
combined.Merge(threads[i]->latency_ns_hist);
|
|
|
|
}
|
|
|
|
printf("%s", combined.ToString().c_str());
|
|
|
|
|
|
|
|
if (FLAGS_gather_stats) {
|
|
|
|
printf("\nGather stats latency (us):\n");
|
|
|
|
printf("%s", stats_hist.ToString().c_str());
|
|
|
|
}
|
|
|
|
|
|
|
|
printf("\n%s", stats_report.c_str());
|
|
|
|
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
private:
|
|
|
|
std::shared_ptr<Cache> cache_;
|
|
|
|
const uint64_t max_key_;
|
|
|
|
// Cumulative thresholds in the space of a random uint64_t
|
|
|
|
const uint64_t lookup_insert_threshold_;
|
|
|
|
const uint64_t insert_threshold_;
|
|
|
|
const uint64_t lookup_threshold_;
|
|
|
|
const uint64_t erase_threshold_;
|
|
|
|
const bool skewed_;
|
|
|
|
int max_log_;
|
|
|
|
|
|
|
|
// A benchmark version of gathering stats on an active block cache by
|
|
|
|
// iterating over it. The primary purpose is to measure the impact of
|
|
|
|
// gathering stats with ApplyToAllEntries on throughput- and
|
|
|
|
// latency-sensitive Cache users. Performance of stats gathering is
|
|
|
|
// also reported. The last set of gathered stats is also reported, for
|
|
|
|
// manual sanity checking for logical errors or other unexpected
|
|
|
|
// behavior of cache_bench or the underlying Cache.
|
|
|
|
static void StatsBody(SharedState* shared, HistogramImpl* stats_hist,
|
|
|
|
std::string* stats_report) {
|
|
|
|
if (!FLAGS_gather_stats) {
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
const auto clock = SystemClock::Default().get();
|
|
|
|
uint64_t total_key_size = 0;
|
|
|
|
uint64_t total_charge = 0;
|
|
|
|
uint64_t total_entry_count = 0;
|
|
|
|
std::set<Cache::DeleterFn> deleters;
|
|
|
|
StopWatchNano timer(clock);
|
|
|
|
|
|
|
|
for (;;) {
|
|
|
|
uint64_t time;
|
|
|
|
time = clock->NowMicros();
|
|
|
|
uint64_t deadline = time + uint64_t{FLAGS_gather_stats_sleep_ms} * 1000;
|
|
|
|
|
|
|
|
{
|
|
|
|
MutexLock l(shared->GetMutex());
|
|
|
|
for (;;) {
|
|
|
|
if (shared->AllDone()) {
|
|
|
|
std::ostringstream ostr;
|
|
|
|
ostr << "Most recent cache entry stats:\n"
|
|
|
|
<< "Number of entries: " << total_entry_count << "\n"
|
|
|
|
<< "Total charge: " << BytesToHumanString(total_charge) << "\n"
|
|
|
|
<< "Average key size: "
|
|
|
|
<< (1.0 * total_key_size / total_entry_count) << "\n"
|
|
|
|
<< "Average charge: "
|
|
|
|
<< BytesToHumanString(static_cast<uint64_t>(
|
|
|
|
1.0 * total_charge / total_entry_count))
|
|
|
|
<< "\n"
|
|
|
|
<< "Unique deleters: " << deleters.size() << "\n";
|
|
|
|
*stats_report = ostr.str();
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
if (clock->NowMicros() >= deadline) {
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
uint64_t diff = deadline - std::min(clock->NowMicros(), deadline);
|
|
|
|
shared->GetCondVar()->TimedWait(diff + 1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Now gather stats, outside of mutex
|
|
|
|
total_key_size = 0;
|
|
|
|
total_charge = 0;
|
|
|
|
total_entry_count = 0;
|
|
|
|
deleters.clear();
|
|
|
|
auto fn = [&](const Slice& key, void* /*value*/, size_t charge,
|
|
|
|
Cache::DeleterFn deleter) {
|
|
|
|
total_key_size += key.size();
|
|
|
|
total_charge += charge;
|
|
|
|
++total_entry_count;
|
|
|
|
// Something slightly more expensive as in (future) stats by category
|
|
|
|
deleters.insert(deleter);
|
|
|
|
};
|
|
|
|
timer.Start();
|
|
|
|
Cache::ApplyToAllEntriesOptions opts;
|
|
|
|
opts.average_entries_per_lock = FLAGS_gather_stats_entries_per_lock;
|
|
|
|
shared->GetCacheBench()->cache_->ApplyToAllEntries(fn, opts);
|
|
|
|
stats_hist->Add(timer.ElapsedNanos() / 1000);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
static void ThreadBody(ThreadState* thread) {
|
|
|
|
SharedState* shared = thread->shared;
|
|
|
|
|
|
|
|
{
|
|
|
|
MutexLock l(shared->GetMutex());
|
|
|
|
shared->IncInitialized();
|
|
|
|
if (shared->AllInitialized()) {
|
|
|
|
shared->GetCondVar()->SignalAll();
|
|
|
|
}
|
|
|
|
while (!shared->Started()) {
|
|
|
|
shared->GetCondVar()->Wait();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
thread->shared->GetCacheBench()->OperateCache(thread);
|
|
|
|
|
|
|
|
{
|
|
|
|
MutexLock l(shared->GetMutex());
|
|
|
|
shared->IncDone();
|
|
|
|
if (shared->AllDone()) {
|
|
|
|
shared->GetCondVar()->SignalAll();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void OperateCache(ThreadState* thread) {
|
|
|
|
// To use looked-up values
|
|
|
|
uint64_t result = 0;
|
|
|
|
// To hold handles for a non-trivial amount of time
|
|
|
|
Cache::Handle* handle = nullptr;
|
|
|
|
KeyGen gen;
|
|
|
|
const auto clock = SystemClock::Default().get();
|
|
|
|
uint64_t start_time = clock->NowMicros();
|
|
|
|
StopWatchNano timer(clock);
|
|
|
|
|
|
|
|
for (uint64_t i = 0; i < FLAGS_ops_per_thread; i++) {
|
|
|
|
timer.Start();
|
|
|
|
Slice key = gen.GetRand(thread->rnd, max_key_, max_log_);
|
|
|
|
uint64_t random_op = thread->rnd.Next();
|
|
|
|
Cache::CreateCallback create_cb =
|
|
|
|
[](void* buf, size_t size, void** out_obj, size_t* charge) -> Status {
|
|
|
|
*out_obj = reinterpret_cast<void*>(new char[size]);
|
|
|
|
memcpy(*out_obj, buf, size);
|
|
|
|
*charge = size;
|
|
|
|
return Status::OK();
|
|
|
|
};
|
|
|
|
|
|
|
|
if (random_op < lookup_insert_threshold_) {
|
|
|
|
if (handle) {
|
|
|
|
cache_->Release(handle);
|
|
|
|
handle = nullptr;
|
|
|
|
}
|
|
|
|
// do lookup
|
|
|
|
handle = cache_->Lookup(key, &helper2, create_cb, Cache::Priority::LOW,
|
|
|
|
true);
|
|
|
|
if (handle) {
|
|
|
|
// do something with the data
|
|
|
|
result += NPHash64(static_cast<char*>(cache_->Value(handle)),
|
|
|
|
FLAGS_value_bytes);
|
|
|
|
} else {
|
|
|
|
// do insert
|
|
|
|
cache_->Insert(key, createValue(thread->rnd), &helper2,
|
|
|
|
FLAGS_value_bytes, &handle);
|
|
|
|
}
|
|
|
|
} else if (random_op < insert_threshold_) {
|
|
|
|
if (handle) {
|
|
|
|
cache_->Release(handle);
|
|
|
|
handle = nullptr;
|
|
|
|
}
|
|
|
|
// do insert
|
|
|
|
cache_->Insert(key, createValue(thread->rnd), &helper3,
|
|
|
|
FLAGS_value_bytes, &handle);
|
|
|
|
} else if (random_op < lookup_threshold_) {
|
|
|
|
if (handle) {
|
|
|
|
cache_->Release(handle);
|
|
|
|
handle = nullptr;
|
|
|
|
}
|
|
|
|
// do lookup
|
|
|
|
handle = cache_->Lookup(key, &helper2, create_cb, Cache::Priority::LOW,
|
|
|
|
true);
|
|
|
|
if (handle) {
|
|
|
|
// do something with the data
|
|
|
|
result += NPHash64(static_cast<char*>(cache_->Value(handle)),
|
|
|
|
FLAGS_value_bytes);
|
|
|
|
}
|
|
|
|
} else if (random_op < erase_threshold_) {
|
|
|
|
// do erase
|
|
|
|
cache_->Erase(key);
|
|
|
|
} else {
|
|
|
|
// Should be extremely unlikely (noop)
|
|
|
|
assert(random_op >= kHundredthUint64 * 100U);
|
|
|
|
}
|
|
|
|
thread->latency_ns_hist.Add(timer.ElapsedNanos());
|
|
|
|
}
|
|
|
|
if (handle) {
|
|
|
|
cache_->Release(handle);
|
|
|
|
handle = nullptr;
|
|
|
|
}
|
|
|
|
// Ensure computations on `result` are not optimized away.
|
|
|
|
if (result == 1) {
|
|
|
|
printf("You are extremely unlucky(2). Try again.\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
thread->duration_us = clock->NowMicros() - start_time;
|
|
|
|
}
|
|
|
|
|
|
|
|
void PrintEnv() const {
|
|
|
|
printf("RocksDB version : %d.%d\n", kMajorVersion, kMinorVersion);
|
|
|
|
printf("Number of threads : %u\n", FLAGS_threads);
|
|
|
|
printf("Ops per thread : %" PRIu64 "\n", FLAGS_ops_per_thread);
|
|
|
|
printf("Cache size : %s\n",
|
|
|
|
BytesToHumanString(FLAGS_cache_size).c_str());
|
|
|
|
printf("Num shard bits : %u\n", FLAGS_num_shard_bits);
|
|
|
|
printf("Max key : %" PRIu64 "\n", max_key_);
|
|
|
|
printf("Resident ratio : %g\n", FLAGS_resident_ratio);
|
|
|
|
printf("Skew degree : %u\n", FLAGS_skew);
|
|
|
|
printf("Populate cache : %d\n", int{FLAGS_populate_cache});
|
|
|
|
printf("Lookup+Insert pct : %u%%\n", FLAGS_lookup_insert_percent);
|
|
|
|
printf("Insert percentage : %u%%\n", FLAGS_insert_percent);
|
|
|
|
printf("Lookup percentage : %u%%\n", FLAGS_lookup_percent);
|
|
|
|
printf("Erase percentage : %u%%\n", FLAGS_erase_percent);
|
|
|
|
std::ostringstream stats;
|
|
|
|
if (FLAGS_gather_stats) {
|
|
|
|
stats << "enabled (" << FLAGS_gather_stats_sleep_ms << "ms, "
|
|
|
|
<< FLAGS_gather_stats_entries_per_lock << "/lock)";
|
|
|
|
} else {
|
|
|
|
stats << "disabled";
|
|
|
|
}
|
|
|
|
printf("Gather stats : %s\n", stats.str().c_str());
|
|
|
|
printf("----------------------------\n");
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
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
3 years ago
|
|
|
// TODO: better description (see PR #9126 for some info)
|
|
|
|
class StressCacheKey {
|
|
|
|
public:
|
|
|
|
void Run() {
|
|
|
|
if (FLAGS_sck_footer_unique_id) {
|
|
|
|
FLAGS_sck_db_count = 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
uint64_t mb_per_day =
|
|
|
|
uint64_t{FLAGS_sck_files_per_day} * FLAGS_sck_file_size_mb;
|
|
|
|
printf("Total cache or DBs size: %gTiB Writing %g MiB/s or %gTiB/day\n",
|
|
|
|
FLAGS_sck_file_size_mb / 1024.0 / 1024.0 *
|
|
|
|
std::pow(2.0, FLAGS_sck_table_bits),
|
|
|
|
mb_per_day / 86400.0, mb_per_day / 1024.0 / 1024.0);
|
|
|
|
multiplier_ = std::pow(2.0, 128 - FLAGS_sck_keep_bits) /
|
|
|
|
(FLAGS_sck_file_size_mb * 1024.0 * 1024.0);
|
|
|
|
printf(
|
|
|
|
"Multiply by %g to correct for simulation losses (but still assume "
|
|
|
|
"whole file cached)\n",
|
|
|
|
multiplier_);
|
|
|
|
restart_nfiles_ = FLAGS_sck_files_per_day / FLAGS_sck_restarts_per_day;
|
|
|
|
double without_ejection =
|
|
|
|
std::pow(1.414214, FLAGS_sck_keep_bits) / FLAGS_sck_files_per_day;
|
|
|
|
printf(
|
|
|
|
"Without ejection, expect random collision after %g days (%g "
|
|
|
|
"corrected)\n",
|
|
|
|
without_ejection, without_ejection * multiplier_);
|
|
|
|
double with_full_table =
|
|
|
|
std::pow(2.0, FLAGS_sck_keep_bits - FLAGS_sck_table_bits) /
|
|
|
|
FLAGS_sck_files_per_day;
|
|
|
|
printf(
|
|
|
|
"With ejection and full table, expect random collision after %g "
|
|
|
|
"days (%g corrected)\n",
|
|
|
|
with_full_table, with_full_table * multiplier_);
|
|
|
|
collisions_ = 0;
|
|
|
|
|
|
|
|
for (int i = 1; collisions_ < FLAGS_sck_min_collision; i++) {
|
|
|
|
RunOnce();
|
|
|
|
if (collisions_ == 0) {
|
|
|
|
printf(
|
|
|
|
"No collisions after %d x %u days "
|
|
|
|
" \n",
|
|
|
|
i, FLAGS_sck_duration);
|
|
|
|
} else {
|
|
|
|
double est = 1.0 * i * FLAGS_sck_duration / collisions_;
|
|
|
|
printf("%" PRIu64
|
|
|
|
" collisions after %d x %u days, est %g days between (%g "
|
|
|
|
"corrected) \n",
|
|
|
|
collisions_, i, FLAGS_sck_duration, est, est * multiplier_);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void RunOnce() {
|
|
|
|
const size_t db_count = FLAGS_sck_db_count;
|
|
|
|
dbs_.reset(new TableProperties[db_count]{});
|
|
|
|
const size_t table_mask = (size_t{1} << FLAGS_sck_table_bits) - 1;
|
|
|
|
table_.reset(new uint64_t[table_mask + 1]{});
|
|
|
|
if (FLAGS_sck_keep_bits > 64) {
|
|
|
|
FLAGS_sck_keep_bits = 64;
|
|
|
|
}
|
|
|
|
uint32_t shift_away = 64 - FLAGS_sck_keep_bits;
|
|
|
|
uint32_t shift_away_b = shift_away / 3;
|
|
|
|
uint32_t shift_away_a = shift_away - shift_away_b;
|
|
|
|
|
|
|
|
process_count_ = 0;
|
|
|
|
session_count_ = 0;
|
|
|
|
ResetProcess();
|
|
|
|
|
|
|
|
Random64 r{std::random_device{}()};
|
|
|
|
|
|
|
|
uint64_t max_file_count =
|
|
|
|
uint64_t{FLAGS_sck_files_per_day} * FLAGS_sck_duration;
|
|
|
|
uint64_t file_count = 0;
|
|
|
|
uint32_t report_count = 0;
|
|
|
|
uint32_t collisions_this_run = 0;
|
|
|
|
// Round robin through DBs
|
|
|
|
for (size_t db_i = 0;; ++db_i) {
|
|
|
|
if (db_i >= db_count) {
|
|
|
|
db_i = 0;
|
|
|
|
}
|
|
|
|
if (file_count >= max_file_count) {
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
if (!FLAGS_sck_footer_unique_id && r.OneIn(FLAGS_sck_reopen_nfiles)) {
|
|
|
|
ResetSession(db_i);
|
|
|
|
} else if (r.OneIn(restart_nfiles_)) {
|
|
|
|
ResetProcess();
|
|
|
|
}
|
|
|
|
OffsetableCacheKey ock;
|
|
|
|
dbs_[db_i].orig_file_number += 1;
|
|
|
|
// skip some file numbers, unless 1 DB so that that can simulate
|
|
|
|
// better (DB-independent) unique IDs
|
|
|
|
if (db_count > 1) {
|
|
|
|
dbs_[db_i].orig_file_number += (r.Next() & 3);
|
|
|
|
}
|
|
|
|
BlockBasedTable::SetupBaseCacheKey(&dbs_[db_i], "", 42, 42, &ock);
|
|
|
|
CacheKey ck = ock.WithOffset(0);
|
|
|
|
uint64_t stripped;
|
|
|
|
if (FLAGS_sck_randomize) {
|
|
|
|
stripped = GetSliceHash64(ck.AsSlice()) >> shift_away;
|
|
|
|
} else if (FLAGS_sck_footer_unique_id) {
|
|
|
|
uint32_t a = DecodeFixed32(ck.AsSlice().data() + 4) >> shift_away_a;
|
|
|
|
uint32_t b = DecodeFixed32(ck.AsSlice().data() + 12) >> shift_away_b;
|
|
|
|
stripped = (uint64_t{a} << 32) + b;
|
|
|
|
} else {
|
|
|
|
uint32_t a = DecodeFixed32(ck.AsSlice().data()) << shift_away_a;
|
|
|
|
uint32_t b = DecodeFixed32(ck.AsSlice().data() + 12) >> shift_away_b;
|
|
|
|
stripped = (uint64_t{a} << 32) + b;
|
|
|
|
}
|
|
|
|
if (stripped == 0) {
|
|
|
|
// Unlikely, but we need to exclude tracking this value
|
|
|
|
printf("Hit Zero! \n");
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
file_count++;
|
|
|
|
uint64_t h = NPHash64(reinterpret_cast<char*>(&stripped), 8);
|
|
|
|
// Skew lifetimes
|
|
|
|
size_t pos =
|
|
|
|
std::min(Lower32of64(h) & table_mask, Upper32of64(h) & table_mask);
|
|
|
|
if (table_[pos] == stripped) {
|
|
|
|
collisions_this_run++;
|
|
|
|
// To predict probability of no collisions, we have to get rid of
|
|
|
|
// correlated collisions, which this takes care of:
|
|
|
|
ResetProcess();
|
|
|
|
} else {
|
|
|
|
// Replace
|
|
|
|
table_[pos] = stripped;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (++report_count == FLAGS_sck_files_per_day) {
|
|
|
|
report_count = 0;
|
|
|
|
// Estimate fill %
|
|
|
|
size_t incr = table_mask / 1000;
|
|
|
|
size_t sampled_count = 0;
|
|
|
|
for (size_t i = 0; i <= table_mask; i += incr) {
|
|
|
|
if (table_[i] != 0) {
|
|
|
|
sampled_count++;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
// Report
|
|
|
|
printf(
|
|
|
|
"%" PRIu64 " days, %" PRIu64 " proc, %" PRIu64
|
|
|
|
" sess, %u coll, occ %g%%, ejected %g%% \r",
|
|
|
|
file_count / FLAGS_sck_files_per_day, process_count_,
|
|
|
|
session_count_, collisions_this_run, 100.0 * sampled_count / 1000.0,
|
|
|
|
100.0 * (1.0 - sampled_count / 1000.0 * table_mask / file_count));
|
|
|
|
fflush(stdout);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
collisions_ += collisions_this_run;
|
|
|
|
}
|
|
|
|
|
|
|
|
void ResetSession(size_t i) {
|
|
|
|
dbs_[i].db_session_id = DBImpl::GenerateDbSessionId(nullptr);
|
|
|
|
session_count_++;
|
|
|
|
}
|
|
|
|
|
|
|
|
void ResetProcess() {
|
|
|
|
process_count_++;
|
|
|
|
DBImpl::TEST_ResetDbSessionIdGen();
|
|
|
|
for (size_t i = 0; i < FLAGS_sck_db_count; ++i) {
|
|
|
|
ResetSession(i);
|
|
|
|
}
|
|
|
|
if (FLAGS_sck_footer_unique_id) {
|
|
|
|
dbs_[0].orig_file_number = 0;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
private:
|
|
|
|
// Use db_session_id and orig_file_number from TableProperties
|
|
|
|
std::unique_ptr<TableProperties[]> dbs_;
|
|
|
|
std::unique_ptr<uint64_t[]> table_;
|
|
|
|
uint64_t process_count_ = 0;
|
|
|
|
uint64_t session_count_ = 0;
|
|
|
|
uint64_t collisions_ = 0;
|
|
|
|
uint32_t restart_nfiles_ = 0;
|
|
|
|
double multiplier_ = 0.0;
|
|
|
|
};
|
|
|
|
|
|
|
|
int cache_bench_tool(int argc, char** argv) {
|
|
|
|
ParseCommandLineFlags(&argc, &argv, true);
|
|
|
|
|
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
3 years ago
|
|
|
if (FLAGS_stress_cache_key) {
|
|
|
|
// Alternate tool
|
|
|
|
StressCacheKey().Run();
|
|
|
|
return 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (FLAGS_threads <= 0) {
|
|
|
|
fprintf(stderr, "threads number <= 0\n");
|
|
|
|
exit(1);
|
|
|
|
}
|
|
|
|
|
|
|
|
ROCKSDB_NAMESPACE::CacheBench bench;
|
|
|
|
if (FLAGS_populate_cache) {
|
|
|
|
bench.PopulateCache();
|
|
|
|
printf("Population complete\n");
|
|
|
|
printf("----------------------------\n");
|
|
|
|
}
|
|
|
|
if (bench.Run()) {
|
|
|
|
return 0;
|
|
|
|
} else {
|
|
|
|
return 1;
|
|
|
|
}
|
|
|
|
} // namespace ROCKSDB_NAMESPACE
|
|
|
|
} // namespace ROCKSDB_NAMESPACE
|
|
|
|
|
|
|
|
#endif // GFLAGS
|