Summary:
It called the autovector::push_back simply in autovector::emplace_back.
This was not efficient, and then optimazed this function through the
perfect forwarding.
This was the src and result of the benchmark(using the google'benchmark library, the type of elem in
autovector was std::string, and call emplace_back with the "char *" type):
https://gist.github.com/monadbobo/93448b89a42737b08cbada81de75c5cd
PS: The benchmark's result of previous PR was not accurate, and so I update the test case and result.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4606
Differential Revision: D13046813
Pulled By: sagar0
fbshipit-source-id: 19cde1bcadafe899aa454b703acb35737a1cc02d
Summary:
This is an implementation of non-exclusive locks for pessimistic transactions. It is relatively simple and does not prevent starvation (ie. it's possible that request for exclusive access will never be granted if there are always threads holding shared access). It is done by changing `KeyLockInfo` to hold an set a transaction ids, instead of just one, and adding a flag specifying whether this lock is currently held with exclusive access or not.
Some implementation notes:
- Some lock diagnostic functions had to be updated to return a set of transaction ids for a given lock, eg. `GetWaitingTxn` and `GetLockStatusData`.
- Deadlock detection is a bit more complicated since a transaction can now wait on multiple other transactions. A BFS is done in this case, and deadlock detection depth is now just a limit on the number of transactions we visit.
- Expirable transactions do not work efficiently with shared locks at the moment, but that's okay for now.
Closes https://github.com/facebook/rocksdb/pull/1573
Differential Revision: D4239097
Pulled By: lth
fbshipit-source-id: da7c074
Summary:
It is hard to measure acutal memory usage by std containers. Even
providing a custom allocator will miss count some of the usage. Here we
only do a wild guess on its memory usage.
Closes https://github.com/facebook/rocksdb/pull/1511
Differential Revision: D4179945
Pulled By: yiwu-arbug
fbshipit-source-id: 32ab929
Summary: This helps Windows port to format their changes, as discussed. Might have formatted some other codes too becasue last 10 commits include more.
Test Plan: Build it.
Reviewers: anthony, IslamAbdelRahman, kradhakrishnan, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D41961
Summary: Make RocksDb build and run on Windows to be functionally
complete and performant. All existing test cases run with no
regressions. Performance numbers are in the pull-request.
Test plan: make all of the existing unit tests pass, obtain perf numbers.
Co-authored-by: Praveen Rao praveensinghrao@outlook.com
Co-authored-by: Sherlock Huang baihan.huang@gmail.com
Co-authored-by: Alex Zinoviev alexander.zinoviev@me.com
Co-authored-by: Dmitri Smirnov dmitrism@microsoft.com
Summary: Replace exception by assertion in autovector
Test Plan: autovector_test
Reviewers: sdong, igor
Reviewed By: igor
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D29847
Summary: The prefix and postfix operators were mixed up in the autovector class.
Test Plan: Inspection
Reviewers: sdong, kailiu
Reviewed By: kailiu
Differential Revision: https://reviews.facebook.net/D21873
Summary:
Introducing RocksDBLite! Removes all the non-essential features and reduces the binary size. This effort should help our adoption on mobile.
Binary size when compiling for IOS (`TARGET_OS=IOS m static_lib`) is down to 9MB from 15MB (without stripping)
Test Plan: compiles :)
Reviewers: dhruba, haobo, ljin, sdong, yhchiang
Reviewed By: yhchiang
CC: leveldb
Differential Revision: https://reviews.facebook.net/D17835
Summary: this diff only replace the cases when we need to frequently create vector with small amount of entries. This diff doesn't aim to improve performance of a specific area, but more like a small scale test for the autovector and see how it works in real life.
Test Plan:
make check
I also ran the performance tests, however there is no performance gain/loss. All performance numbers are pretty much the same before/after the change.
Reviewers: dhruba, haobo, sdong, igor
CC: leveldb
Differential Revision: https://reviews.facebook.net/D14985
Summary:
A vector that leverages pre-allocated stack-based array to achieve better
performance for array with small amount of items.
Test Plan:
Added tests for both correctness and performance
Here is the performance benchmark between vector and autovector
Please note that in the test "Creation and Insertion Test", the test case were designed with the motivation described below:
* no element inserted: internal array of std::vector may not really get
initialize.
* one element inserted: internal array of std::vector must have
initialized.
* kSize elements inserted. This shows the most time we'll spend if we
keep everything in stack.
* 2 * kSize elements inserted. The internal vector of
autovector must have been initialized.
Note: kSize is the capacity of autovector
=====================================================
Creation and Insertion Test
=====================================================
created 100000 vectors:
each was inserted with 0 elements
total time elapsed: 128000 (ns)
created 100000 autovectors:
each was inserted with 0 elements
total time elapsed: 3641000 (ns)
created 100000 VectorWithReserveSizes:
each was inserted with 0 elements
total time elapsed: 9896000 (ns)
-----------------------------------
created 100000 vectors:
each was inserted with 1 elements
total time elapsed: 11089000 (ns)
created 100000 autovectors:
each was inserted with 1 elements
total time elapsed: 5008000 (ns)
created 100000 VectorWithReserveSizes:
each was inserted with 1 elements
total time elapsed: 24271000 (ns)
-----------------------------------
created 100000 vectors:
each was inserted with 4 elements
total time elapsed: 39369000 (ns)
created 100000 autovectors:
each was inserted with 4 elements
total time elapsed: 10121000 (ns)
created 100000 VectorWithReserveSizes:
each was inserted with 4 elements
total time elapsed: 28473000 (ns)
-----------------------------------
created 100000 vectors:
each was inserted with 8 elements
total time elapsed: 75013000 (ns)
created 100000 autovectors:
each was inserted with 8 elements
total time elapsed: 18237000 (ns)
created 100000 VectorWithReserveSizes:
each was inserted with 8 elements
total time elapsed: 42464000 (ns)
-----------------------------------
created 100000 vectors:
each was inserted with 16 elements
total time elapsed: 102319000 (ns)
created 100000 autovectors:
each was inserted with 16 elements
total time elapsed: 76724000 (ns)
created 100000 VectorWithReserveSizes:
each was inserted with 16 elements
total time elapsed: 68285000 (ns)
-----------------------------------
=====================================================
Sequence Access Test
=====================================================
performed 100000 sequence access against vector
size: 4
total time elapsed: 198000 (ns)
performed 100000 sequence access against autovector
size: 4
total time elapsed: 306000 (ns)
-----------------------------------
performed 100000 sequence access against vector
size: 8
total time elapsed: 565000 (ns)
performed 100000 sequence access against autovector
size: 8
total time elapsed: 512000 (ns)
-----------------------------------
performed 100000 sequence access against vector
size: 16
total time elapsed: 1076000 (ns)
performed 100000 sequence access against autovector
size: 16
total time elapsed: 1070000 (ns)
-----------------------------------
Reviewers: dhruba, haobo, sdong, chip
Reviewed By: dhruba
CC: leveldb
Differential Revision: https://reviews.facebook.net/D14655
