Summary:
RangeDelAggregatorV2 now supports ShouldDelete calls on
snapshot stripes and creation of range tombstone compaction iterators.
RangeDelAggregator is no longer used on any non-test code path, and will
be removed in a future commit.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4758
Differential Revision: D13439254
Pulled By: abhimadan
fbshipit-source-id: fe105bcf8e3d4a2df37a622d5510843cd71b0401
Summary:
To support the flush/compaction use cases of RangeDelAggregator
in v2, FragmentedRangeTombstoneIterator now supports dropping tombstones
that cannot be read in the compaction output file. Furthermore,
FragmentedRangeTombstoneIterator supports the "snapshot striping" use
case by allowing an iterator to be split by a list of snapshots.
RangeDelAggregatorV2 will use these changes in a follow-up change.
In the process of making these changes, other miscellaneous cleanups
were also done in these files.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4740
Differential Revision: D13287382
Pulled By: abhimadan
fbshipit-source-id: f5aeb03e1b3058049b80c02a558ee48f723fa48c
Summary:
Removed `one_time_use` flag, which removed the need for some
tests, and changed all `NewRangeTombstoneIterator` methods to return
`FragmentedRangeTombstoneIterators`.
These changes also led to removing `RangeDelAggregatorV2::AddUnfragmentedTombstones`
and one of the `MemTableListVersion::AddRangeTombstoneIterators` methods.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4692
Differential Revision: D13106570
Pulled By: abhimadan
fbshipit-source-id: cbab5432d7fc2d9cdfd8d9d40361a1bffaa8f845
Summary:
The old RangeDelAggregator did expensive pre-processing work
to create a collapsed, binary-searchable representation of range
tombstones. With FragmentedRangeTombstoneIterator, much of this work is
now unnecessary. RangeDelAggregatorV2 takes advantage of this by seeking
in each iterator to find a covering tombstone in ShouldDelete, while
doing minimal work in AddTombstones. The old RangeDelAggregator is still
used during flush/compaction for now, though RangeDelAggregatorV2 will
support those uses in a future PR.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4649
Differential Revision: D13146964
Pulled By: abhimadan
fbshipit-source-id: be29a4c020fc440500c137216fcc1cf529571eb3
Summary:
Rather than storing a `vector<RangeTombstone>`, we now store a
`vector<RangeTombstoneStack>` and a `vector<SequenceNumber>`. A
`RangeTombstoneStack` contains the start and end keys of a range tombstone
fragment, and indices into the seqnum vector to indicate which sequence
numbers the fragment is located at. The diagram below illustrates an
example:
```
tombstones_: [a, b) [c, e) [h, k)
| \ / \ / |
| \ / \ / |
v v v v
tombstone_seqs_: [ 5 3 10 7 2 8 6 ]
```
This format allows binary searching the tombstone list to use less key
comparisons, which helps in cases where there are many overlapping
tombstones. Also, this format makes it easier to add DBIter-like
semantics to `FragmentedRangeTombstoneIterator` in the future.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4632
Differential Revision: D13053103
Pulled By: abhimadan
fbshipit-source-id: e8220cc712fcf5be4d602913bb23ace8ea5f8ef0
Summary:
This allows tombstone fragmenting to only be performed when the table is opened, and cached for subsequent accesses.
On the same DB used in #4449, running `readrandom` results in the following:
```
readrandom : 0.983 micros/op 1017076 ops/sec; 78.3 MB/s (63103 of 100000 found)
```
Now that Get performance in the presence of range tombstones is reasonable, I also compared the performance between a DB with range tombstones, "expanded" range tombstones (several point tombstones that cover the same keys the equivalent range tombstone would cover, a common workaround for DeleteRange), and no range tombstones. The created DBs had 5 million keys each, and DeleteRange was called at regular intervals (depending on the total number of range tombstones being written) after 4.5 million Puts. The table below summarizes the results of a `readwhilewriting` benchmark (in order to provide somewhat more realistic results):
```
Tombstones? | avg micros/op | stddev micros/op | avg ops/s | stddev ops/s
----------------- | ------------- | ---------------- | ------------ | ------------
None | 0.6186 | 0.04637 | 1,625,252.90 | 124,679.41
500 Expanded | 0.6019 | 0.03628 | 1,666,670.40 | 101,142.65
500 Unexpanded | 0.6435 | 0.03994 | 1,559,979.40 | 104,090.52
1k Expanded | 0.6034 | 0.04349 | 1,665,128.10 | 125,144.57
1k Unexpanded | 0.6261 | 0.03093 | 1,600,457.50 | 79,024.94
5k Expanded | 0.6163 | 0.05926 | 1,636,668.80 | 154,888.85
5k Unexpanded | 0.6402 | 0.04002 | 1,567,804.70 | 100,965.55
10k Expanded | 0.6036 | 0.05105 | 1,667,237.70 | 142,830.36
10k Unexpanded | 0.6128 | 0.02598 | 1,634,633.40 | 72,161.82
25k Expanded | 0.6198 | 0.04542 | 1,620,980.50 | 116,662.93
25k Unexpanded | 0.5478 | 0.0362 | 1,833,059.10 | 121,233.81
50k Expanded | 0.5104 | 0.04347 | 1,973,107.90 | 184,073.49
50k Unexpanded | 0.4528 | 0.03387 | 2,219,034.50 | 170,984.32
```
After a large enough quantity of range tombstones are written, range tombstone Gets can become faster than reading from an equivalent DB with several point tombstones.
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4493
Differential Revision: D10842844
Pulled By: abhimadan
fbshipit-source-id: a7d44534f8120e6aabb65779d26c6b9df954c509
Summary:
Previously, range tombstones were accumulated from every level, which
was necessary if a range tombstone in a higher level covered a key in a lower
level. However, RangeDelAggregator::AddTombstones's complexity is based on
the number of tombstones that are currently stored in it, which is wasteful in
the Get case, where we only need to know the highest sequence number of range
tombstones that cover the key from higher levels, and compute the highest covering
sequence number at the current level. This change introduces this optimization, and
removes the use of RangeDelAggregator from the Get path.
In the benchmark results, the following command was used to initialize the database:
```
./db_bench -db=/dev/shm/5k-rts -use_existing_db=false -benchmarks=filluniquerandom -write_buffer_size=1048576 -compression_type=lz4 -target_file_size_base=1048576 -max_bytes_for_level_base=4194304 -value_size=112 -key_size=16 -block_size=4096 -level_compaction_dynamic_level_bytes=true -num=5000000 -max_background_jobs=12 -benchmark_write_rate_limit=20971520 -range_tombstone_width=100 -writes_per_range_tombstone=100 -max_num_range_tombstones=50000 -bloom_bits=8
```
...and the following command was used to measure read throughput:
```
./db_bench -db=/dev/shm/5k-rts/ -use_existing_db=true -benchmarks=readrandom -disable_auto_compactions=true -num=5000000 -reads=100000 -threads=32
```
The filluniquerandom command was only run once, and the resulting database was used
to measure read performance before and after the PR. Both binaries were compiled with
`DEBUG_LEVEL=0`.
Readrandom results before PR:
```
readrandom : 4.544 micros/op 220090 ops/sec; 16.9 MB/s (63103 of 100000 found)
```
Readrandom results after PR:
```
readrandom : 11.147 micros/op 89707 ops/sec; 6.9 MB/s (63103 of 100000 found)
```
So it's actually slower right now, but this PR paves the way for future optimizations (see #4493).
----
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4449
Differential Revision: D10370575
Pulled By: abhimadan
fbshipit-source-id: 9a2e152be1ef36969055c0e9eb4beb0d96c11f4d
Abhishek Madan