New stable, fixed-length cache keys (#9126)
Summary:
This change standardizes on a new 16-byte cache key format for
block cache (incl compressed and secondary) and persistent cache (but
not table cache and row cache).
The goal is a really fast cache key with practically ideal stability and
uniqueness properties without external dependencies (e.g. from FileSystem).
A fixed key size of 16 bytes should enable future optimizations to the
concurrent hash table for block cache, which is a heavy CPU user /
bottleneck, but there appears to be measurable performance improvement
even with no changes to LRUCache.
This change replaces a lot of disjointed and ugly code handling cache
keys with calls to a simple, clean new internal API (cache_key.h).
(Preserving the old cache key logic under an option would be very ugly
and likely negate the performance gain of the new approach. Complete
replacement carries some inherent risk, but I think that's acceptable
with sufficient analysis and testing.)
The scheme for encoding new cache keys is complicated but explained
in cache_key.cc.
Also: EndianSwapValue is moved to math.h to be next to other bit
operations. (Explains some new include "math.h".) ReverseBits operation
added and unit tests added to hash_test for both.
Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126
Test Plan:
### Basic correctness
Several tests needed updates to work with the new functionality, mostly
because we are no longer relying on filesystem for stable cache keys
so table builders & readers need more context info to agree on cache
keys. This functionality is so core, a huge number of existing tests
exercise the cache key functionality.
### Performance
Create db with
`TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters`
And test performance with
`TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4`
using DEBUG_LEVEL=0 and simultaneous before & after runs.
Before ops/sec, avg over 100 runs: 121924
After ops/sec, avg over 100 runs: 125385 (+2.8%)
### Collision probability
I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity
over many months, by making some pessimistic simplifying assumptions:
* Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys)
* All of every file is cached for its entire lifetime
We use a simple table with skewed address assignment and replacement on address collision
to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output
with `./cache_bench -stress_cache_key -sck_keep_bits=40`:
```
Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day
Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached)
```
These come from default settings of 2.5M files per day of 32 MB each, and
`-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of
the 128-bit cache key. With file size of 2\*\*25 contiguous keys (pessimistic), our simulation
is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality.
More default assumptions, relatively pessimistic:
* 100 DBs in same process (doesn't matter much)
* Re-open DB in same process (new session ID related to old session ID) on average
every 100 files generated
* Restart process (all new session IDs unrelated to old) 24 times per day
After enough data, we get a result at the end:
```
(keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected)
```
If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data:
```
(keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected)
(keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected)
```
The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases:
```
197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected)
```
I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data.
Reviewed By: zhichao-cao
Differential Revision: D33171746
Pulled By: pdillinger
fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f
2021-12-17 01:13:55 +00:00
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// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
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// This source code is licensed under both the GPLv2 (found in the
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// COPYING file in the root directory) and Apache 2.0 License
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// (found in the LICENSE.Apache file in the root directory).
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#include "cache/cache_key.h"
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#include <algorithm>
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#include <atomic>
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#include "rocksdb/cache.h"
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#include "table/unique_id_impl.h"
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#include "util/hash.h"
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#include "util/math.h"
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namespace ROCKSDB_NAMESPACE {
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// Value space plan for CacheKey:
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//
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// session_etc64_ | offset_etc64_ | Only generated by
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// ---------------+---------------+------------------------------------------
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// 0 | 0 | Reserved for "empty" CacheKey()
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// 0 | > 0, < 1<<63 | CreateUniqueForCacheLifetime
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// 0 | >= 1<<63 | CreateUniqueForProcessLifetime
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// > 0 | any | OffsetableCacheKey.WithOffset
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CacheKey CacheKey::CreateUniqueForCacheLifetime(Cache *cache) {
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// +1 so that we can reserve all zeros for "unset" cache key
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uint64_t id = cache->NewId() + 1;
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// Ensure we don't collide with CreateUniqueForProcessLifetime
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assert((id >> 63) == 0U);
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return CacheKey(0, id);
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}
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CacheKey CacheKey::CreateUniqueForProcessLifetime() {
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// To avoid colliding with CreateUniqueForCacheLifetime, assuming
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// Cache::NewId counts up from zero, here we count down from UINT64_MAX.
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2022-02-04 22:15:06 +00:00
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// If this ever becomes a point of contention, we could sub-divide the
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// space and use CoreLocalArray.
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New stable, fixed-length cache keys (#9126)
Summary:
This change standardizes on a new 16-byte cache key format for
block cache (incl compressed and secondary) and persistent cache (but
not table cache and row cache).
The goal is a really fast cache key with practically ideal stability and
uniqueness properties without external dependencies (e.g. from FileSystem).
A fixed key size of 16 bytes should enable future optimizations to the
concurrent hash table for block cache, which is a heavy CPU user /
bottleneck, but there appears to be measurable performance improvement
even with no changes to LRUCache.
This change replaces a lot of disjointed and ugly code handling cache
keys with calls to a simple, clean new internal API (cache_key.h).
(Preserving the old cache key logic under an option would be very ugly
and likely negate the performance gain of the new approach. Complete
replacement carries some inherent risk, but I think that's acceptable
with sufficient analysis and testing.)
The scheme for encoding new cache keys is complicated but explained
in cache_key.cc.
Also: EndianSwapValue is moved to math.h to be next to other bit
operations. (Explains some new include "math.h".) ReverseBits operation
added and unit tests added to hash_test for both.
Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126
Test Plan:
### Basic correctness
Several tests needed updates to work with the new functionality, mostly
because we are no longer relying on filesystem for stable cache keys
so table builders & readers need more context info to agree on cache
keys. This functionality is so core, a huge number of existing tests
exercise the cache key functionality.
### Performance
Create db with
`TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters`
And test performance with
`TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4`
using DEBUG_LEVEL=0 and simultaneous before & after runs.
Before ops/sec, avg over 100 runs: 121924
After ops/sec, avg over 100 runs: 125385 (+2.8%)
### Collision probability
I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity
over many months, by making some pessimistic simplifying assumptions:
* Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys)
* All of every file is cached for its entire lifetime
We use a simple table with skewed address assignment and replacement on address collision
to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output
with `./cache_bench -stress_cache_key -sck_keep_bits=40`:
```
Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day
Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached)
```
These come from default settings of 2.5M files per day of 32 MB each, and
`-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of
the 128-bit cache key. With file size of 2\*\*25 contiguous keys (pessimistic), our simulation
is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality.
More default assumptions, relatively pessimistic:
* 100 DBs in same process (doesn't matter much)
* Re-open DB in same process (new session ID related to old session ID) on average
every 100 files generated
* Restart process (all new session IDs unrelated to old) 24 times per day
After enough data, we get a result at the end:
```
(keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected)
```
If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data:
```
(keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected)
(keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected)
```
The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases:
```
197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected)
```
I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data.
Reviewed By: zhichao-cao
Differential Revision: D33171746
Pulled By: pdillinger
fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f
2021-12-17 01:13:55 +00:00
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static std::atomic<uint64_t> counter{UINT64_MAX};
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uint64_t id = counter.fetch_sub(1, std::memory_order_relaxed);
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// Ensure we don't collide with CreateUniqueForCacheLifetime
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assert((id >> 63) == 1U);
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return CacheKey(0, id);
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}
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// Value plan for CacheKeys from OffsetableCacheKey, assuming that
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// db_session_ids are generated from a base_session_id and
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// session_id_counter (by SemiStructuredUniqueIdGen+EncodeSessionId
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// in DBImpl::GenerateDbSessionId):
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//
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// Conceptual inputs:
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// db_id (unstructured, from GenerateRawUniqueId or equiv)
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// * could be shared between cloned DBs but rare
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// * could be constant, if session id suffices
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// base_session_id (unstructured, from GenerateRawUniqueId)
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// session_id_counter (structured)
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// * usually much smaller than 2**24
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// file_number (structured)
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// * usually smaller than 2**24
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// offset_in_file (structured, might skip lots of values)
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// * usually smaller than 2**32
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// max_offset determines placement of file_number to prevent
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// overlapping with offset
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//
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// Outputs come from bitwise-xor of the constituent pieces, low bits on left:
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//
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// |------------------------- session_etc64 -------------------------|
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// | +++++++++++++++ base_session_id (lower 64 bits) +++++++++++++++ |
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// |-----------------------------------------------------------------|
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// | session_id_counter ...| |
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// |-----------------------------------------------------------------|
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// | | ... file_number |
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// | | overflow & meta |
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// |-----------------------------------------------------------------|
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//
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//
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// |------------------------- offset_etc64 --------------------------|
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// | hash of: ++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
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// | * base_session_id (upper ~39 bits) |
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// | * db_id (~122 bits entropy) |
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// |-----------------------------------------------------------------|
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// | offset_in_file ............... | |
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// |-----------------------------------------------------------------|
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// | | file_number, 0-3 |
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// | | lower bytes |
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// |-----------------------------------------------------------------|
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//
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// Based on max_offset, a maximal number of bytes 0..3 is chosen for
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// including from lower bits of file_number in offset_etc64. The choice
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// is encoded in two bits of metadata going into session_etc64, though
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// the common case of 3 bytes is encoded as 0 so that session_etc64
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// is unmodified by file_number concerns in the common case.
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//
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// There is nothing preventing "file number overflow & meta" from meeting
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// and overlapping with session_id_counter, but reaching such a case requires
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// an intractable combination of large file offsets (thus at least some large
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// files), large file numbers (thus large number of files generated), and
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// large number of session IDs generated in a single process. A trillion each
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// (2**40) of session ids, offsets, and file numbers comes to 120 bits.
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// With two bits of metadata and byte granularity, this is on the verge of
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// overlap, but even in the overlap case, it doesn't seem likely that
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// a file from billions of files or session ids ago will still be live
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// or cached.
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//
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// In fact, if our SST files are all < 4TB (see
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// BlockBasedTable::kMaxFileSizeStandardEncoding), then SST files generated
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// in a single process are guaranteed to have unique cache keys, unless/until
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// number session ids * max file number = 2**86, e.g. 1 trillion DB::Open in
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// a single process and 64 trillion files generated. Even at that point, to
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// see a collision we would need a miraculous re-synchronization of session
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// id and file number, along with a live file or stale cache entry from
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// trillions of files ago.
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//
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// How https://github.com/pdillinger/unique_id applies here:
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// Every bit of output always includes "unstructured" uniqueness bits and
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// often combines with "structured" uniqueness bits. The "unstructured" bits
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// change infrequently: only when we cannot guarantee our state tracking for
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// "structured" uniqueness hasn't been cloned. Using a static
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// SemiStructuredUniqueIdGen for db_session_ids, this means we only get an
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// "all new" session id when a new process uses RocksDB. (Between processes,
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2022-02-04 22:15:06 +00:00
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// we don't know if a DB or other persistent storage has been cloned. We
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// assume that if VM hot cloning is used, subsequently generated SST files
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// do not interact.) Within a process, only the session_lower of the
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// db_session_id changes incrementally ("structured" uniqueness).
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New stable, fixed-length cache keys (#9126)
Summary:
This change standardizes on a new 16-byte cache key format for
block cache (incl compressed and secondary) and persistent cache (but
not table cache and row cache).
The goal is a really fast cache key with practically ideal stability and
uniqueness properties without external dependencies (e.g. from FileSystem).
A fixed key size of 16 bytes should enable future optimizations to the
concurrent hash table for block cache, which is a heavy CPU user /
bottleneck, but there appears to be measurable performance improvement
even with no changes to LRUCache.
This change replaces a lot of disjointed and ugly code handling cache
keys with calls to a simple, clean new internal API (cache_key.h).
(Preserving the old cache key logic under an option would be very ugly
and likely negate the performance gain of the new approach. Complete
replacement carries some inherent risk, but I think that's acceptable
with sufficient analysis and testing.)
The scheme for encoding new cache keys is complicated but explained
in cache_key.cc.
Also: EndianSwapValue is moved to math.h to be next to other bit
operations. (Explains some new include "math.h".) ReverseBits operation
added and unit tests added to hash_test for both.
Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126
Test Plan:
### Basic correctness
Several tests needed updates to work with the new functionality, mostly
because we are no longer relying on filesystem for stable cache keys
so table builders & readers need more context info to agree on cache
keys. This functionality is so core, a huge number of existing tests
exercise the cache key functionality.
### Performance
Create db with
`TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters`
And test performance with
`TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4`
using DEBUG_LEVEL=0 and simultaneous before & after runs.
Before ops/sec, avg over 100 runs: 121924
After ops/sec, avg over 100 runs: 125385 (+2.8%)
### Collision probability
I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity
over many months, by making some pessimistic simplifying assumptions:
* Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys)
* All of every file is cached for its entire lifetime
We use a simple table with skewed address assignment and replacement on address collision
to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output
with `./cache_bench -stress_cache_key -sck_keep_bits=40`:
```
Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day
Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached)
```
These come from default settings of 2.5M files per day of 32 MB each, and
`-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of
the 128-bit cache key. With file size of 2\*\*25 contiguous keys (pessimistic), our simulation
is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality.
More default assumptions, relatively pessimistic:
* 100 DBs in same process (doesn't matter much)
* Re-open DB in same process (new session ID related to old session ID) on average
every 100 files generated
* Restart process (all new session IDs unrelated to old) 24 times per day
After enough data, we get a result at the end:
```
(keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected)
```
If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data:
```
(keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected)
(keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected)
```
The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases:
```
197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected)
```
I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data.
Reviewed By: zhichao-cao
Differential Revision: D33171746
Pulled By: pdillinger
fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f
2021-12-17 01:13:55 +00:00
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//
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// This basically means that our offsets, counters and file numbers allow us
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// to do somewhat "better than random" (birthday paradox) while in the
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// degenerate case of completely new session for each tiny file, we still
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// have strong uniqueness properties from the birthday paradox, with ~103
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// bit session IDs or up to 128 bits entropy with different DB IDs sharing a
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// cache.
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//
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// More collision probability analysis:
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// Suppose a RocksDB host generates (generously) 2 GB/s (10TB data, 17 DWPD)
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// with average process/session lifetime of (pessimistically) 4 minutes.
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// In 180 days (generous allowable data lifespan), we generate 31 million GB
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// of data, or 2^55 bytes, and 2^16 "all new" session IDs.
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//
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// First, suppose this is in a single DB (lifetime 180 days):
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// 128 bits cache key size
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// - 55 <- ideal size for byte offsets + file numbers
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// - 2 <- bits for offsets and file numbers not exactly powers of two
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// - 2 <- bits for file number encoding metadata
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// + 2 <- bits saved not using byte offsets in BlockBasedTable::GetCacheKey
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// ----
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// 71 <- bits remaining for distinguishing session IDs
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// The probability of a collision in 71 bits of session ID data is less than
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// 1 in 2**(71 - (2 * 16)), or roughly 1 in a trillion. And this assumes all
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// data from the last 180 days is in cache for potential collision, and that
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// cache keys under each session id exhaustively cover the remaining 57 bits
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// while in reality they'll only cover a small fraction of it.
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//
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// Although data could be transferred between hosts, each host has its own
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|
|
// cache and we are already assuming a high rate of "all new" session ids.
|
|
|
|
// So this doesn't really change the collision calculation. Across a fleet
|
|
|
|
// of 1 million, each with <1 in a trillion collision possibility,
|
|
|
|
// fleetwide collision probability is <1 in a million.
|
|
|
|
//
|
|
|
|
// Now suppose we have many DBs per host, say 2**10, with same host-wide write
|
|
|
|
// rate and process/session lifetime. File numbers will be ~10 bits smaller
|
|
|
|
// and we will have 2**10 times as many session IDs because of simultaneous
|
|
|
|
// lifetimes. So now collision chance is less than 1 in 2**(81 - (2 * 26)),
|
|
|
|
// or roughly 1 in a billion.
|
|
|
|
//
|
|
|
|
// Suppose instead we generated random or hashed cache keys for each
|
|
|
|
// (compressed) block. For 1KB compressed block size, that is 2^45 cache keys
|
|
|
|
// in 180 days. Collision probability is more easily estimated at roughly
|
|
|
|
// 1 in 2**(128 - (2 * 45)) or roughly 1 in a trillion (assuming all
|
|
|
|
// data from the last 180 days is in cache, but NOT the other assumption
|
|
|
|
// for the 1 in a trillion estimate above).
|
|
|
|
//
|
|
|
|
//
|
2022-02-04 22:15:06 +00:00
|
|
|
// Collision probability estimation through simulation:
|
|
|
|
// A tool ./cache_bench -stress_cache_key broadly simulates host-wide cache
|
|
|
|
// activity over many months, by making some pessimistic simplifying
|
|
|
|
// assumptions. See class StressCacheKey in cache_bench_tool.cc for details.
|
|
|
|
// Here is some sample 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 (base) 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 (-sck_keep_bits=40):
|
|
|
|
//
|
|
|
|
// (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
|
|
|
|
// extrapolation, we would need to run a billion machines all for 97 billion
|
|
|
|
// days to expect a cache key collision. To help verify that our extrapolation
|
|
|
|
// ("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
|
|
|
|
// collision 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 extrapolated prediction is very close. If anything, we might have some
|
|
|
|
// very small losses of structured data (see class StressCacheKey in
|
|
|
|
// cache_bench_tool.cc) leading to more accurate & more attractive prediction
|
|
|
|
// with more bits kept.
|
|
|
|
//
|
|
|
|
// With the `-sck_randomize` option, we can see that typical workloads like
|
|
|
|
// above have lower collision probability than "random" cache keys (note:
|
|
|
|
// 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 (e.g. repeatedly launch a process to generate 1 file
|
|
|
|
// with SstFileWriter):
|
|
|
|
//
|
|
|
|
// (rand 40 bits) 197 collisions after 1 x 90 days, est 0.456853 days between
|
|
|
|
// (4.21372e+18 corrected)
|
|
|
|
//
|
|
|
|
// We can see that with more frequent process restarts (all new session IDs),
|
|
|
|
// we get closer to the "random" cache key performance:
|
|
|
|
//
|
|
|
|
// (-sck_restarts_per_day=5000): 140 collisions after 1 x 90 days, ...
|
|
|
|
// (5.92931e+18 corrected)
|
|
|
|
//
|
|
|
|
// Other tests have been run to validate other conditions behave as expected,
|
|
|
|
// never behaving "worse than random" unless we start chopping off structured
|
|
|
|
// data.
|
|
|
|
//
|
|
|
|
//
|
|
|
|
// Conclusion: Even in extreme cases, rapidly burning through "all new" IDs
|
|
|
|
// that only arise when a new process is started, the chance of any cache key
|
|
|
|
// collisions in a giant fleet of machines is negligible. Especially when
|
|
|
|
// processes live for hours or days, the chance of a cache key collision is
|
|
|
|
// likely more plausibly due to bad hardware than to bad luck in random
|
|
|
|
// session ID data. Software defects are surely more likely to cause corruption
|
|
|
|
// than both of those.
|
|
|
|
//
|
|
|
|
// TODO: Nevertheless / regardless, an efficient way to detect (and thus
|
|
|
|
// quantify) block cache corruptions, including collisions, should be added.
|
New stable, fixed-length cache keys (#9126)
Summary:
This change standardizes on a new 16-byte cache key format for
block cache (incl compressed and secondary) and persistent cache (but
not table cache and row cache).
The goal is a really fast cache key with practically ideal stability and
uniqueness properties without external dependencies (e.g. from FileSystem).
A fixed key size of 16 bytes should enable future optimizations to the
concurrent hash table for block cache, which is a heavy CPU user /
bottleneck, but there appears to be measurable performance improvement
even with no changes to LRUCache.
This change replaces a lot of disjointed and ugly code handling cache
keys with calls to a simple, clean new internal API (cache_key.h).
(Preserving the old cache key logic under an option would be very ugly
and likely negate the performance gain of the new approach. Complete
replacement carries some inherent risk, but I think that's acceptable
with sufficient analysis and testing.)
The scheme for encoding new cache keys is complicated but explained
in cache_key.cc.
Also: EndianSwapValue is moved to math.h to be next to other bit
operations. (Explains some new include "math.h".) ReverseBits operation
added and unit tests added to hash_test for both.
Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause)
Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126
Test Plan:
### Basic correctness
Several tests needed updates to work with the new functionality, mostly
because we are no longer relying on filesystem for stable cache keys
so table builders & readers need more context info to agree on cache
keys. This functionality is so core, a huge number of existing tests
exercise the cache key functionality.
### Performance
Create db with
`TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters`
And test performance with
`TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4`
using DEBUG_LEVEL=0 and simultaneous before & after runs.
Before ops/sec, avg over 100 runs: 121924
After ops/sec, avg over 100 runs: 125385 (+2.8%)
### Collision probability
I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity
over many months, by making some pessimistic simplifying assumptions:
* Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys)
* All of every file is cached for its entire lifetime
We use a simple table with skewed address assignment and replacement on address collision
to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output
with `./cache_bench -stress_cache_key -sck_keep_bits=40`:
```
Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day
Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached)
```
These come from default settings of 2.5M files per day of 32 MB each, and
`-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of
the 128-bit cache key. With file size of 2\*\*25 contiguous keys (pessimistic), our simulation
is about 2\*\*(128-40-25) or about 9 billion billion times more prone to collision than reality.
More default assumptions, relatively pessimistic:
* 100 DBs in same process (doesn't matter much)
* Re-open DB in same process (new session ID related to old session ID) on average
every 100 files generated
* Restart process (all new session IDs unrelated to old) 24 times per day
After enough data, we get a result at the end:
```
(keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected)
```
If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data:
```
(keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected)
(keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected)
```
The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases:
```
197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected)
```
I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data.
Reviewed By: zhichao-cao
Differential Revision: D33171746
Pulled By: pdillinger
fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f
2021-12-17 01:13:55 +00:00
|
|
|
OffsetableCacheKey::OffsetableCacheKey(const std::string &db_id,
|
|
|
|
const std::string &db_session_id,
|
|
|
|
uint64_t file_number,
|
|
|
|
uint64_t max_offset) {
|
|
|
|
#ifndef NDEBUG
|
|
|
|
max_offset_ = max_offset;
|
|
|
|
#endif
|
|
|
|
// Closely related to GetSstInternalUniqueId, but only need 128 bits and
|
|
|
|
// need to include an offset within the file.
|
|
|
|
// See also https://github.com/pdillinger/unique_id for background.
|
|
|
|
uint64_t session_upper = 0; // Assignment to appease clang-analyze
|
|
|
|
uint64_t session_lower = 0; // Assignment to appease clang-analyze
|
|
|
|
{
|
|
|
|
Status s = DecodeSessionId(db_session_id, &session_upper, &session_lower);
|
|
|
|
if (!s.ok()) {
|
|
|
|
// A reasonable fallback in case malformed
|
|
|
|
Hash2x64(db_session_id.data(), db_session_id.size(), &session_upper,
|
|
|
|
&session_lower);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Hash the session upper (~39 bits entropy) and DB id (120+ bits entropy)
|
|
|
|
// for more global uniqueness entropy.
|
|
|
|
// (It is possible that many DBs descended from one common DB id are copied
|
|
|
|
// around and proliferate, in which case session id is critical, but it is
|
|
|
|
// more common for different DBs to have different DB ids.)
|
|
|
|
uint64_t db_hash = Hash64(db_id.data(), db_id.size(), session_upper);
|
|
|
|
|
|
|
|
// This establishes the db+session id part of the cache key.
|
|
|
|
//
|
|
|
|
// Exactly preserve (in common cases; see modifiers below) session lower to
|
|
|
|
// ensure that session ids generated during the same process lifetime are
|
|
|
|
// guaranteed unique.
|
|
|
|
//
|
|
|
|
// We put this first for CommonPrefixSlice(), so that a small-ish set of
|
|
|
|
// cache key prefixes to cover entries relevant to any DB.
|
|
|
|
session_etc64_ = session_lower;
|
|
|
|
// This provides extra entopy in case of different DB id or process
|
|
|
|
// generating a session id, but is also partly/variably obscured by
|
|
|
|
// file_number and offset (see below).
|
|
|
|
offset_etc64_ = db_hash;
|
|
|
|
|
|
|
|
// Into offset_etc64_ we are (eventually) going to pack & xor in an offset and
|
|
|
|
// a file_number, but we might need the file_number to overflow into
|
|
|
|
// session_etc64_. (There must only be one session_etc64_ value per
|
|
|
|
// file, and preferably shared among many files.)
|
|
|
|
//
|
|
|
|
// Figure out how many bytes of file_number we are going to be able to
|
|
|
|
// pack in with max_offset, though our encoding will only support packing
|
|
|
|
// in up to 3 bytes of file_number. (16M file numbers is enough for a new
|
|
|
|
// file number every second for half a year.)
|
|
|
|
int file_number_bytes_in_offset_etc =
|
|
|
|
(63 - FloorLog2(max_offset | 0x100000000U)) / 8;
|
|
|
|
int file_number_bits_in_offset_etc = file_number_bytes_in_offset_etc * 8;
|
|
|
|
|
|
|
|
// Assert two bits of metadata
|
|
|
|
assert(file_number_bytes_in_offset_etc >= 0 &&
|
|
|
|
file_number_bytes_in_offset_etc <= 3);
|
|
|
|
// Assert we couldn't have used a larger allowed number of bytes (shift
|
|
|
|
// would chop off bytes).
|
|
|
|
assert(file_number_bytes_in_offset_etc == 3 ||
|
|
|
|
(max_offset << (file_number_bits_in_offset_etc + 8) >>
|
|
|
|
(file_number_bits_in_offset_etc + 8)) != max_offset);
|
|
|
|
|
|
|
|
uint64_t mask = (uint64_t{1} << (file_number_bits_in_offset_etc)) - 1;
|
|
|
|
// Pack into high bits of etc so that offset can go in low bits of etc
|
|
|
|
// TODO: could be EndianSwapValue?
|
|
|
|
uint64_t offset_etc_modifier = ReverseBits(file_number & mask);
|
|
|
|
assert(offset_etc_modifier << file_number_bits_in_offset_etc == 0U);
|
|
|
|
|
|
|
|
// Overflow and 3 - byte count (likely both zero) go into session_id part
|
|
|
|
uint64_t session_etc_modifier =
|
|
|
|
(file_number >> file_number_bits_in_offset_etc << 2) |
|
|
|
|
static_cast<uint64_t>(3 - file_number_bytes_in_offset_etc);
|
|
|
|
// Packed into high bits to minimize interference with session id counter.
|
|
|
|
session_etc_modifier = ReverseBits(session_etc_modifier);
|
|
|
|
|
|
|
|
// Assert session_id part is only modified in extreme cases
|
|
|
|
assert(session_etc_modifier == 0 || file_number > /*3 bytes*/ 0xffffffU ||
|
|
|
|
max_offset > /*5 bytes*/ 0xffffffffffU);
|
|
|
|
|
|
|
|
// Xor in the modifiers
|
|
|
|
session_etc64_ ^= session_etc_modifier;
|
|
|
|
offset_etc64_ ^= offset_etc_modifier;
|
|
|
|
|
|
|
|
// Although DBImpl guarantees (in recent versions) that session_lower is not
|
|
|
|
// zero, that's not entirely sufficient to guarantee that session_etc64_ is
|
|
|
|
// not zero (so that the 0 case can be used by CacheKey::CreateUnique*)
|
|
|
|
if (session_etc64_ == 0U) {
|
|
|
|
session_etc64_ = session_upper | 1U;
|
|
|
|
}
|
|
|
|
assert(session_etc64_ != 0);
|
|
|
|
}
|
|
|
|
|
|
|
|
} // namespace ROCKSDB_NAMESPACE
|