rocksdb

Commit Graph

Author	SHA1	Message	Date
Peter Dillinger	0050a73a4f	New stable, fixed-length cache keys (#9126 ) Summary: This change standardizes on a new 16-byte cache key format for block cache (incl compressed and secondary) and persistent cache (but not table cache and row cache). The goal is a really fast cache key with practically ideal stability and uniqueness properties without external dependencies (e.g. from FileSystem). A fixed key size of 16 bytes should enable future optimizations to the concurrent hash table for block cache, which is a heavy CPU user / bottleneck, but there appears to be measurable performance improvement even with no changes to LRUCache. This change replaces a lot of disjointed and ugly code handling cache keys with calls to a simple, clean new internal API (cache_key.h). (Preserving the old cache key logic under an option would be very ugly and likely negate the performance gain of the new approach. Complete replacement carries some inherent risk, but I think that's acceptable with sufficient analysis and testing.) The scheme for encoding new cache keys is complicated but explained in cache_key.cc. Also: EndianSwapValue is moved to math.h to be next to other bit operations. (Explains some new include "math.h".) ReverseBits operation added and unit tests added to hash_test for both. Fixes https://github.com/facebook/rocksdb/issues/7405 (presuming a root cause) Pull Request resolved: https://github.com/facebook/rocksdb/pull/9126 Test Plan: ### Basic correctness Several tests needed updates to work with the new functionality, mostly because we are no longer relying on filesystem for stable cache keys so table builders & readers need more context info to agree on cache keys. This functionality is so core, a huge number of existing tests exercise the cache key functionality. ### Performance Create db with `TEST_TMPDIR=/dev/shm ./db_bench -bloom_bits=10 -benchmarks=fillrandom -num=3000000 -partition_index_and_filters` And test performance with `TEST_TMPDIR=/dev/shm ./db_bench -readonly -use_existing_db -bloom_bits=10 -benchmarks=readrandom -num=3000000 -duration=30 -cache_index_and_filter_blocks -cache_size=250000 -threads=4` using DEBUG_LEVEL=0 and simultaneous before & after runs. Before ops/sec, avg over 100 runs: 121924 After ops/sec, avg over 100 runs: 125385 (+2.8%) ### Collision probability I have built a tool, ./cache_bench -stress_cache_key to broadly simulate host-wide cache activity over many months, by making some pessimistic simplifying assumptions: * Every generated file has a cache entry for every byte offset in the file (contiguous range of cache keys) * All of every file is cached for its entire lifetime We use a simple table with skewed address assignment and replacement on address collision to simulate files coming & going, with quite a variance (super-Poisson) in ages. Some output with `./cache_bench -stress_cache_key -sck_keep_bits=40`: ``` Total cache or DBs size: 32TiB Writing 925.926 MiB/s or 76.2939TiB/day Multiply by 9.22337e+18 to correct for simulation losses (but still assume whole file cached) ``` These come from default settings of 2.5M files per day of 32 MB each, and `-sck_keep_bits=40` means that to represent a single file, we are only keeping 40 bits of the 128-bit cache key. With file size of 2\\25 contiguous keys (pessimistic), our simulation is about 2\\(128-40-25) or about 9 billion billion times more prone to collision than reality. More default assumptions, relatively pessimistic: * 100 DBs in same process (doesn't matter much) * Re-open DB in same process (new session ID related to old session ID) on average every 100 files generated * Restart process (all new session IDs unrelated to old) 24 times per day After enough data, we get a result at the end: ``` (keep 40 bits) 17 collisions after 2 x 90 days, est 10.5882 days between (9.76592e+19 corrected) ``` If we believe the (pessimistic) simulation and the mathematical generalization, we would need to run a billion machines all for 97 billion days to expect a cache key collision. To help verify that our generalization ("corrected") is robust, we can make our simulation more precise with `-sck_keep_bits=41` and `42`, which takes more running time to get enough data: ``` (keep 41 bits) 16 collisions after 4 x 90 days, est 22.5 days between (1.03763e+20 corrected) (keep 42 bits) 19 collisions after 10 x 90 days, est 47.3684 days between (1.09224e+20 corrected) ``` The generalized prediction still holds. With the `-sck_randomize` option, we can see that we are beating "random" cache keys (except offsets still non-randomized) by a modest amount (roughly 20x less collision prone than random), which should make us reasonably comfortable even in "degenerate" cases: ``` 197 collisions after 1 x 90 days, est 0.456853 days between (4.21372e+18 corrected) ``` I've run other tests to validate other conditions behave as expected, never behaving "worse than random" unless we start chopping off structured data. Reviewed By: zhichao-cao Differential Revision: D33171746 Pulled By: pdillinger fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f	4 years ago
anand76	8ea0a2c1bd	Parallelize secondary cache lookup in MultiGet (#8405 ) Summary: Implement the ```WaitAll()``` interface in ```LRUCache``` to allow callers to issue multiple lookups in parallel and wait for all of them to complete. Modify ```MultiGet``` to use this to parallelize the secondary cache lookups in order to reduce the overall latency. A call to ```cache->Lookup()``` returns a handle that has an incomplete value (nullptr), and the caller can call ```cache->IsReady()``` to check whether the lookup is complete, and pass a vector of handles to ```WaitAll``` to wait for completion. If any of the lookups fail, ```MultiGet``` will read the block from the SST file. Another change in this PR is to rename ```SecondaryCacheHandle``` to ```SecondaryCacheResultHandle``` as it more accurately describes the return result of the secondary cache lookup, which is more like a future. Tests: 1. Add unit tests in lru_cache_test 2. Benchmark results with no secondary cache configured Master - ``` readrandom : 41.175 micros/op 388562 ops/sec; 106.7 MB/s (7277999 of 7277999 found) readrandom : 41.217 micros/op 388160 ops/sec; 106.6 MB/s (7274999 of 7274999 found) multireadrandom : 10.309 micros/op 1552082 ops/sec; (28908992 of 28908992 found) multireadrandom : 10.321 micros/op 1550218 ops/sec; (29081984 of 29081984 found) ``` This PR - ``` readrandom : 41.158 micros/op 388723 ops/sec; 106.8 MB/s (7290999 of 7290999 found) readrandom : 41.185 micros/op 388463 ops/sec; 106.7 MB/s (7287999 of 7287999 found) multireadrandom : 10.277 micros/op 1556801 ops/sec; (29346944 of 29346944 found) multireadrandom : 10.253 micros/op 1560539 ops/sec; (29274944 of 29274944 found) ``` Pull Request resolved: https://github.com/facebook/rocksdb/pull/8405 Reviewed By: zhichao-cao Differential Revision: D29190509 Pulled By: anand1976 fbshipit-source-id: 6f8eff6246712af8a297cfe22ea0d1c3b2a01bb0	4 years ago
sdong	674cf41732	Divide block_based_table_reader.cc (#6527 ) Summary: block_based_table_reader.cc is a giant file, which makes it hard for users to navigate the code. Divide the files to multiple files. Some class templates cannot be moved to .cc file. They are moved to .h files. It is still better than including them all in block_based_table_reader.cc. Pull Request resolved: https://github.com/facebook/rocksdb/pull/6527 Test Plan: "make all check" and "make release". Also build using cmake. Differential Revision: D20428455 fbshipit-source-id: ca713c698469f07f35bc0c271358c0874ed4eb28	6 years ago

Author

SHA1

Message

Date

Peter Dillinger

0050a73a4f

New stable, fixed-length cache keys (#9126 )

Summary:
This change standardizes on a new 16-byte cache key format for
block cache (incl compressed and secondary) and persistent cache (but
not table cache and row cache).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Reviewed By: zhichao-cao

Differential Revision: D33171746

Pulled By: pdillinger

fbshipit-source-id: f16a57e369ed37be5e7e33525ace848d0537c88f

4 years ago

anand76

8ea0a2c1bd

Parallelize secondary cache lookup in MultiGet (#8405 )

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

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

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

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

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

Reviewed By: zhichao-cao

Differential Revision: D29190509

Pulled By: anand1976

fbshipit-source-id: 6f8eff6246712af8a297cfe22ea0d1c3b2a01bb0

4 years ago

sdong

674cf41732

Divide block_based_table_reader.cc (#6527 )

Summary:
block_based_table_reader.cc is a giant file, which makes it hard for users to navigate the code. Divide the files to multiple files.
Some class templates cannot be moved to .cc file. They are moved to .h files. It is still better than including them all in block_based_table_reader.cc.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/6527

Test Plan: "make all check" and "make release". Also build using cmake.

Differential Revision: D20428455

fbshipit-source-id: ca713c698469f07f35bc0c271358c0874ed4eb28

6 years ago

3 Commits (93a0e9f3faf2f90f39d58d7d8370748c2ee05197)