Summary:
Added `do_not_compress_roles` to `CompressedSecondaryCacheOptions` to disable compression on certain kinds of block. Filter blocks are now not compressed by CompressedSecondaryCache by default.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/11204

Test Plan: unit test added

Reviewed By: anand1976

Differential Revision: D43147698

Pulled By: pdillinger

fbshipit-source-id: db496975ae975fa18f157f93fe131a16315ac875

Summary:
This is several refactorings bundled into one to avoid having to incrementally re-modify uses of Cache several times. Overall, there are breaking changes to Cache class, and it becomes more of low-level interface for implementing caches, especially block cache. New internal APIs make using Cache cleaner than before, and more insulated from block cache evolution. Hopefully, this is the last really big block cache refactoring, because of rather effectively decoupling the implementations from the uses. This change also removes the EXPERIMENTAL designation on the SecondaryCache support in Cache. It seems reasonably mature at this point but still subject to change/evolution (as I warn in the API docs for Cache).

The high-level motivation for this refactoring is to minimize code duplication / compounding complexity in adding SecondaryCache support to HyperClockCache (in a later PR). Other benefits listed below.

* static_cast lines of code +29 -35 (net removed 6)
* reinterpret_cast lines of code +6 -32 (net removed 26)

## cache.h and secondary_cache.h
* Always use CacheItemHelper with entries instead of just a Deleter. There are several motivations / justifications:
  * Simpler for implementations to deal with just one Insert and one Lookup.
  * Simpler and more efficient implementation because we don't have to track which entries are using helpers and which are using deleters
  * Gets rid of hack to classify cache entries by their deleter. Instead, the CacheItemHelper includes a CacheEntryRole. This simplifies a lot of code (cache_entry_roles.h almost eliminated). Fixes https://github.com/facebook/rocksdb/issues/9428.
  * Makes it trivial to adjust SecondaryCache behavior based on kind of block (e.g. don't re-compress filter blocks).
  * It is arguably less convenient for many direct users of Cache, but direct users of Cache are now rare with introduction of typed_cache.h (below).
  * I considered and rejected an alternative approach in which we reduce customizability by assuming each secondary cache compatible value starts with a Slice referencing the uncompressed block contents (already true or mostly true), but we apparently intend to stack secondary caches. Saving an entry from a compressed secondary to a lower tier requires custom handling offered by SaveToCallback, etc.
* Make CreateCallback part of the helper and introduce CreateContext to work with it (alternative to https://github.com/facebook/rocksdb/issues/10562). This cleans up the interface while still allowing context to be provided for loading/parsing values into primary cache. This model works for async lookup in BlockBasedTable reader (reader owns a CreateContext) under the assumption that it always waits on secondary cache operations to finish. (Otherwise, the CreateContext could be destroyed while async operation depending on it continues.) This likely contributes most to the observed performance improvement because it saves an std::function backed by a heap allocation.
* Use char* for serialized data, e.g. in SaveToCallback, where void* was confusingly used. (We use `char*` for serialized byte data all over RocksDB, with many advantages over `void*`. `memcpy` etc. are legacy APIs that should not be mimicked.)
* Add a type alias Cache::ObjectPtr = void*, so that we can better indicate the intent of the void* when it is to be the object associated with a Cache entry. Related: started (but did not complete) a refactoring to move away from "value" of a cache entry toward "object" or "obj". (It is confusing to call Cache a key-value store (like DB) when it is really storing arbitrary in-memory objects, not byte strings.)
* Remove unnecessary key param from DeleterFn. This is good for efficiency in HyperClockCache, which does not directly store the cache key in memory. (Alternative to https://github.com/facebook/rocksdb/issues/10774)
* Add allocator to Cache DeleterFn. This is a kind of future-proofing change in case we get more serious about using the Cache allocator for memory tracked by the Cache. Right now, only the uncompressed block contents are allocated using the allocator, and a pointer to that allocator is saved as part of the cached object so that the deleter can use it. (See CacheAllocationPtr.) If in the future we are able to "flatten out" our Cache objects some more, it would be good not to have to track the allocator as part of each object.
* Removes legacy `ApplyToAllCacheEntries` and changes `ApplyToAllEntries` signature for Deleter->CacheItemHelper change.

## typed_cache.h
Adds various "typed" interfaces to the Cache as internal APIs, so that most uses of Cache can use simple type safe code without casting and without explicit deleters, etc. Almost all of the non-test, non-glue code uses of Cache have been migrated. (Follow-up work: CompressedSecondaryCache deserves deeper attention to migrate.) This change expands RocksDB's internal usage of metaprogramming and SFINAE (https://en.cppreference.com/w/cpp/language/sfinae).

The existing usages of Cache are divided up at a high level into these new interfaces. See updated existing uses of Cache for examples of how these are used.
* PlaceholderCacheInterface - Used for making cache reservations, with entries that have a charge but no value.
* BasicTypedCacheInterface<TValue> - Used for primary cache storage of objects of type TValue, which can be cleaned up with std::default_delete<TValue>. The role is provided by TValue::kCacheEntryRole or given in an optional template parameter.
* FullTypedCacheInterface<TValue, TCreateContext> - Used for secondary cache compatible storage of objects of type TValue. In addition to BasicTypedCacheInterface constraints, we require TValue::ContentSlice() to return persistable data. This simplifies usage for the normal case of simple secondary cache compatibility (can give you a Slice to the data already in memory). In addition to TCreateContext performing the role of Cache::CreateContext, it is also expected to provide a factory function for creating TValue.
* For each of these, there's a "Shared" version (e.g. FullTypedSharedCacheInterface) that holds a shared_ptr to the Cache, rather than assuming external ownership by holding only a raw `Cache*`.

These interfaces introduce specific handle types for each interface instantiation, so that it's easy to see what kind of object is controlled by a handle. (Ultimately, this might not be worth the extra complexity, but it seems OK so far.)

Note: I attempted to make the cache 'charge' automatically inferred from the cache object type, such as by expecting an ApproximateMemoryUsage() function, but this is not so clean because there are cases where we need to compute the charge ahead of time and don't want to re-compute it.

## block_cache.h
This header is essentially the replacement for the old block_like_traits.h. It includes various things to support block cache access with typed_cache.h for block-based table.

## block_based_table_reader.cc
Before this change, accessing the block cache here was an awkward mix of static polymorphism (template TBlocklike) and switch-case on a dynamic BlockType value. This change mostly unifies on static polymorphism, relying on minor hacks in block_cache.h to distinguish variants of Block. We still check BlockType in some places (especially for stats, which could be improved in follow-up work) but at least the BlockType is a static constant from the template parameter. (No more awkward partial redundancy between static and dynamic info.) This likely contributes to the overall performance improvement, but hasn't been tested in isolation.

The other key source of simplification here is a more unified system of creating block cache objects: for directly populating from primary cache and for promotion from secondary cache. Both use BlockCreateContext, for context and for factory functions.

## block_based_table_builder.cc, cache_dump_load_impl.cc
Before this change, warming caches was super ugly code. Both of these source files had switch statements to basically transition from the dynamic BlockType world to the static TBlocklike world. None of that mess is needed anymore as there's a new, untyped WarmInCache function that handles all the details just as promotion from SecondaryCache would. (Fixes `TODO akanksha: Dedup below code` in block_based_table_builder.cc.)

## Everything else
Mostly just updating Cache users to use new typed APIs when reasonably possible, or changed Cache APIs when not.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10975

Test Plan:
tests updated

Performance test setup similar to https://github.com/facebook/rocksdb/issues/10626 (by cache size, LRUCache when not "hyper" for HyperClockCache):

34MB 1thread base.hyper -> kops/s: 0.745 io_bytes/op: 2.52504e+06 miss_ratio: 0.140906 max_rss_mb: 76.4844
34MB 1thread new.hyper -> kops/s: 0.751 io_bytes/op: 2.5123e+06 miss_ratio: 0.140161 max_rss_mb: 79.3594
34MB 1thread base -> kops/s: 0.254 io_bytes/op: 1.36073e+07 miss_ratio: 0.918818 max_rss_mb: 45.9297
34MB 1thread new -> kops/s: 0.252 io_bytes/op: 1.36157e+07 miss_ratio: 0.918999 max_rss_mb: 44.1523
34MB 32thread base.hyper -> kops/s: 7.272 io_bytes/op: 2.88323e+06 miss_ratio: 0.162532 max_rss_mb: 516.602
34MB 32thread new.hyper -> kops/s: 7.214 io_bytes/op: 2.99046e+06 miss_ratio: 0.168818 max_rss_mb: 518.293
34MB 32thread base -> kops/s: 3.528 io_bytes/op: 1.35722e+07 miss_ratio: 0.914691 max_rss_mb: 264.926
34MB 32thread new -> kops/s: 3.604 io_bytes/op: 1.35744e+07 miss_ratio: 0.915054 max_rss_mb: 264.488
233MB 1thread base.hyper -> kops/s: 53.909 io_bytes/op: 2552.35 miss_ratio: 0.0440566 max_rss_mb: 241.984
233MB 1thread new.hyper -> kops/s: 62.792 io_bytes/op: 2549.79 miss_ratio: 0.044043 max_rss_mb: 241.922
233MB 1thread base -> kops/s: 1.197 io_bytes/op: 2.75173e+06 miss_ratio: 0.103093 max_rss_mb: 241.559
233MB 1thread new -> kops/s: 1.199 io_bytes/op: 2.73723e+06 miss_ratio: 0.10305 max_rss_mb: 240.93
233MB 32thread base.hyper -> kops/s: 1298.69 io_bytes/op: 2539.12 miss_ratio: 0.0440307 max_rss_mb: 371.418
233MB 32thread new.hyper -> kops/s: 1421.35 io_bytes/op: 2538.75 miss_ratio: 0.0440307 max_rss_mb: 347.273
233MB 32thread base -> kops/s: 9.693 io_bytes/op: 2.77304e+06 miss_ratio: 0.103745 max_rss_mb: 569.691
233MB 32thread new -> kops/s: 9.75 io_bytes/op: 2.77559e+06 miss_ratio: 0.103798 max_rss_mb: 552.82
1597MB 1thread base.hyper -> kops/s: 58.607 io_bytes/op: 1449.14 miss_ratio: 0.0249324 max_rss_mb: 1583.55
1597MB 1thread new.hyper -> kops/s: 69.6 io_bytes/op: 1434.89 miss_ratio: 0.0247167 max_rss_mb: 1584.02
1597MB 1thread base -> kops/s: 60.478 io_bytes/op: 1421.28 miss_ratio: 0.024452 max_rss_mb: 1589.45
1597MB 1thread new -> kops/s: 63.973 io_bytes/op: 1416.07 miss_ratio: 0.0243766 max_rss_mb: 1589.24
1597MB 32thread base.hyper -> kops/s: 1436.2 io_bytes/op: 1357.93 miss_ratio: 0.0235353 max_rss_mb: 1692.92
1597MB 32thread new.hyper -> kops/s: 1605.03 io_bytes/op: 1358.04 miss_ratio: 0.023538 max_rss_mb: 1702.78
1597MB 32thread base -> kops/s: 280.059 io_bytes/op: 1350.34 miss_ratio: 0.023289 max_rss_mb: 1675.36
1597MB 32thread new -> kops/s: 283.125 io_bytes/op: 1351.05 miss_ratio: 0.0232797 max_rss_mb: 1703.83

Almost uniformly improving over base revision, especially for hot paths with HyperClockCache, up to 12% higher throughput seen (1597MB, 32thread, hyper). The improvement for that is likely coming from much simplified code for providing context for secondary cache promotion (CreateCallback/CreateContext), and possibly from less branching in block_based_table_reader. And likely a small improvement from not reconstituting key for DeleterFn.

Reviewed By: anand1976

Differential Revision: D42417818

Pulled By: pdillinger

fbshipit-source-id: f86bfdd584dce27c028b151ba56818ad14f7a432

Summary:
To support tuning secondary cache dynamically, add `SetCapacity()` and `GetCapacity()` for CompressedSecondaryCache.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10712

Test Plan: Unit Tests

Reviewed By: anand1976

Differential Revision: D39685212

Pulled By: gitbw95

fbshipit-source-id: 19573c67237011927320207732b5de083cb87240

Summary:
`enable_custom_split_merge` is added for enabling the custom split and merge feature, which split the compressed value into chunks so that they may better fit jemalloc bins.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10690

Test Plan:
Unit Tests
Stress Tests

Reviewed By: anand1976

Differential Revision: D39567604

Pulled By: gitbw95

fbshipit-source-id: f6d1d46200f365220055f793514601dcb0edc4b7

Summary:
**Summary:**
When a block is firstly `Lookup` from the secondary cache, we just insert a dummy block in the primary cache (charging the actual size of the block) and don’t erase the block from the secondary cache. A standalone handle is returned from `Lookup`. Only if the block is hit again, we erase it from the secondary cache and add it into the primary cache.

When a block is firstly evicted from the primary cache to the secondary cache, we just insert a dummy block (size 0) in the secondary cache. When the block is evicted again, it is treated as a hot block and is inserted into the secondary cache.

**Implementation Details**
Add a new state of LRUHandle: The handle is never inserted into the LRUCache (both hash table and LRU list) and it doesn't experience the above three states. The entry can be freed when refs becomes 0.  (refs >= 1 && in_cache == false && IS_STANDALONE == true)

The behaviors of  `LRUCacheShard::Lookup()` are updated if the secondary_cache is CompressedSecondaryCache:
1. If a handle is found in primary cache:
  1.1. If the handle's value is not nullptr, it is returned immediately.
  1.2. If the handle's value is nullptr, this means the handle is a dummy one. For a dummy handle, if it was retrieved from secondary cache, it may still exist in secondary cache.
    - 1.2.1. If no valid handle can be `Lookup` from secondary cache, return nullptr.
    - 1.2.2. If the handle from secondary cache is valid, erase it from the secondary cache and add it into the primary cache.
2. If a handle is not found in primary cache:
  2.1. If no valid handle can be `Lookup` from secondary cache, return nullptr.
  2.2.  If the handle from secondary cache is valid, insert a dummy block in the primary cache (charging the actual size of the block)  and return a standalone handle.

The behaviors of `LRUCacheShard::Promote()` are updated as follows:
1. If `e->sec_handle` has value, one of the following steps can happen:
  1.1. Insert a dummy handle and return a standalone handle to caller when `secondary_cache_` is `CompressedSecondaryCache` and e is a standalone handle.
  1.2. Insert the item into the primary cache and return the handle to caller.
  1.3. Exception handling.
3. If `e->sec_handle` has no value, mark the item as not in cache and charge the cache as its only metadata that'll shortly be released.

The behavior of  `CompressedSecondaryCache::Insert()` is updated:
1. If a block is evicted from the primary cache for the first time, a dummy item is inserted.
4. If a dummy item is found for a block, the block is inserted into the secondary cache.

The behavior of  `CompressedSecondaryCache:::Lookup()` is updated:
1. If a handle is not found or it is a dummy item, a nullptr is returned.
2. If `erase_handle` is true, the handle is erased.

The behaviors of  `LRUCacheShard::Release()` are adjusted for the standalone handles.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10527

Test Plan:
1. stress tests.
5. unit tests.
6. CPU profiling for db_bench.

Reviewed By: siying

Differential Revision: D38747613

Pulled By: gitbw95

fbshipit-source-id: 74a1eba7e1957c9affb2bd2ae3e0194584fa6eca

Summary:
RocksDB's `Cache` abstraction currently supports two priority levels for items: high (used for frequently accessed/highly valuable SST metablocks like index/filter blocks) and low (used for SST data blocks). Blobs are typically lower-value targets for caching than data blocks, since 1) with BlobDB, data blocks containing blob references conceptually form an index structure which has to be consulted before we can read the blob value, and 2) cached blobs represent only a single key-value, while cached data blocks generally contain multiple KVs. Since we would like to make it possible to use the same backing cache for the block cache and the blob cache, it would make sense to add a new, lower-than-low cache priority level (bottom level) for blobs so data blocks are prioritized over them.

This task is a part of https://github.com/facebook/rocksdb/issues/10156

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10461

Reviewed By: siying

Differential Revision: D38672823

Pulled By: ltamasi

fbshipit-source-id: 90cf7362036563d79891f47be2cc24b827482743

Summary:
### **Summary:**
To minimize the internal fragmentation caused by the variable size of the compressed blocks, the original block is split according to the jemalloc bin size in `Insert()` and then merged back in `Lookup()`.  Based on the analysis of the results of the following tests, from the overall internal fragmentation perspective, this PR does mitigate the internal fragmentation issue.

_Do more myshadow tests with the latest commit. I finished several myshadow AB Testing and the results are promising. For the config of 4GB primary cache and 3GB secondary cache, Jemalloc resident stats shows consistently ~0.15GB memory saving; the allocated and active stats show similar memory savings. The CPU usage is almost the same before and after this PR._

To evaluate the issue of memory fragmentations and the benefits of this PR, I conducted two sets of local tests as follows.

**T1**
Keys:       16 bytes each (+ 0 bytes user-defined timestamp)
Values:     100 bytes each (50 bytes after compression)
Entries:    90000000
RawSize:    9956.4 MB (estimated)
FileSize:   5664.8 MB (estimated)

| Test Name | Primary Cache Size (MB) | Compressed Secondary Cache Size (MB) |
| - | - | - |
| T1_3 | 4000 | 4000 |
| T1_4 | 2000 | 3000 |

Populate the DB:
./db_bench --benchmarks=fillrandom --num=90000000 -db=/mem_fragmentation/db_bench_1
Overwrite it to a stable state:
./db_bench --benchmarks=overwrite --num=90000000 -use_existing_db -db=/mem_fragmentation/db_bench_1

Run read tests with differnt cache setting:
T1_3:
MALLOC_CONF="prof:true,prof_stats:true" ../rocksdb/db_bench --benchmarks=seekrandom  --threads=16 --num=90000000 -use_existing_db --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=4000000000 -compressed_secondary_cache_size=4000000000 -use_compressed_secondary_cache -db=/mem_fragmentation/db_bench_1 --print_malloc_stats=true > ~/temp/mem_frag/20220710/jemalloc_stats_json_T1_3_20220710 -duration=1800 &

T1_4:
MALLOC_CONF="prof:true,prof_stats:true" ../rocksdb/db_bench --benchmarks=seekrandom  --threads=16 --num=90000000 -use_existing_db --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=2000000000 -compressed_secondary_cache_size=3000000000 -use_compressed_secondary_cache -db=/mem_fragmentation/db_bench_1 --print_malloc_stats=true > ~/temp/mem_frag/20220710/jemalloc_stats_json_T1_4_20220710 -duration=1800 &

For T1_3 and T1_4, I also conducted the tests before and after this PR. The following table show the important jemalloc stats.

| Test Name | T1_3 | T1_3 after mem defrag | T1_4 | T1_4 after mem defrag |
| - | - | - | - | - |
| allocated (MB)  | 8728 | 8076 | 5518 | 5043 |
| available (MB)  | 8753 | 8092 | 5536 | 5051 |
| external fragmentation rate  | 0.003 | 0.002 | 0.003 | 0.0016 |
| resident (MB)  | 8956 | 8365 | 5655 | 5235 |

**T2**
Keys:       32 bytes each (+ 0 bytes user-defined timestamp)
Values:     256 bytes each (128 bytes after compression)
Entries:    40000000
RawSize:    10986.3 MB (estimated)
FileSize:   6103.5 MB (estimated)

| Test Name | Primary Cache Size (MB) | Compressed Secondary Cache Size (MB) |
| - | - | - |
| T2_3 | 4000 | 4000 |
| T2_4 | 2000 | 3000 |

Create DB (10GB):
./db_bench -benchmarks=fillrandom -use_direct_reads=true -num=40000000 -key_size=32 -value_size=256 -db=/mem_fragmentation/db_bench_2
Overwrite it to a stable state:
./db_bench --benchmarks=overwrite --num=40000000 -use_existing_db -key_size=32 -value_size=256 -db=/mem_fragmentation/db_bench_2

Run read tests with differnt cache setting:
T2_3:
MALLOC_CONF="prof:true,prof_stats:true" ./db_bench  --benchmarks="mixgraph" -use_direct_io_for_flush_and_compaction=true -use_direct_reads=true -cache_size=4000000000 -compressed_secondary_cache_size=4000000000 -use_compressed_secondary_cache -keyrange_dist_a=14.18 -keyrange_dist_b=-2.917 -keyrange_dist_c=0.0164 -keyrange_dist_d=-0.08082 -keyrange_num=30 -value_k=0.2615 -value_sigma=25.45 -iter_k=2.517 -iter_sigma=14.236 -mix_get_ratio=0.85 -mix_put_ratio=0.14 -mix_seek_ratio=0.01 -sine_mix_rate_interval_milliseconds=5000 -sine_a=1000 -sine_b=0.000073 -sine_d=400000 -reads=80000000 -num=40000000 -key_size=32 -value_size=256 -use_existing_db=true -db=/mem_fragmentation/db_bench_2 --print_malloc_stats=true > ~/temp/mem_frag/jemalloc_stats_T2_3 -duration=1800  &

T2_4:
MALLOC_CONF="prof:true,prof_stats:true" ./db_bench  --benchmarks="mixgraph" -use_direct_io_for_flush_and_compaction=true -use_direct_reads=true -cache_size=2000000000 -compressed_secondary_cache_size=3000000000 -use_compressed_secondary_cache -keyrange_dist_a=14.18 -keyrange_dist_b=-2.917 -keyrange_dist_c=0.0164 -keyrange_dist_d=-0.08082 -keyrange_num=30 -value_k=0.2615 -value_sigma=25.45 -iter_k=2.517 -iter_sigma=14.236 -mix_get_ratio=0.85 -mix_put_ratio=0.14 -mix_seek_ratio=0.01 -sine_mix_rate_interval_milliseconds=5000 -sine_a=1000 -sine_b=0.000073 -sine_d=400000 -reads=80000000 -num=40000000 -key_size=32 -value_size=256 -use_existing_db=true -db=/mem_fragmentation/db_bench_2 --print_malloc_stats=true > ~/temp/mem_frag/jemalloc_stats_T2_4 -duration=1800  &

For T2_3 and T2_4, I also conducted the tests before and after this PR. The following table show the important jemalloc stats.

| Test Name |  T2_3 | T2_3 after mem defrag | T2_4 | T2_4 after mem defrag |
| -  | - | - | - | - |
| allocated (MB)  | 8425 | 8093 | 5426 | 5149 |
| available (MB)  | 8489 | 8138 | 5435 | 5158 |
| external fragmentation rate  | 0.008 | 0.0055 | 0.0017 | 0.0017 |
| resident (MB)  | 8676 | 8392 | 5541 | 5321 |

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10287

Test Plan: Unit tests.

Reviewed By: anand1976

Differential Revision: D37743362

Pulled By: gitbw95

fbshipit-source-id: 0010c5af08addeacc5ebbc4ffe5be882fb1d38ad

Summary:
This reverts commit 8d178090
because of a clear performance regression seen in internal dashboard
https://fburl.com/unidash/tpz75iee

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10434

Reviewed By: ltamasi

Differential Revision: D38256373

Pulled By: pdillinger

fbshipit-source-id: 134aa00f50dd7b1bbe037c227884a351342ec44b

Summary:
RocksDB's `Cache` abstraction currently supports two priority levels for items: high (used for frequently accessed/highly valuable SST metablocks like index/filter blocks) and low (used for SST data blocks). Blobs are typically lower-value targets for caching than data blocks, since 1) with BlobDB, data blocks containing blob references conceptually form an index structure which has to be consulted before we can read the blob value, and 2) cached blobs represent only a single key-value, while cached data blocks generally contain multiple KVs. Since we would like to make it possible to use the same backing cache for the block cache and the blob cache, it would make sense to add a new, lower-than-low cache priority level (bottom level) for blobs so data blocks are prioritized over them.

This task is a part of https://github.com/facebook/rocksdb/issues/10156

Pull Request resolved: https://github.com/facebook/rocksdb/pull/10309

Reviewed By: ltamasi

Differential Revision: D38211655

Pulled By: gangliao

fbshipit-source-id: 65ef33337db4d85277cc6f9782d67c421ad71dd5

Summary:
###  **Summary:**
When both LRU Cache and CompressedSecondaryCache are configured together, there possibly are some data blocks double cached.

**Changes include:**
1. Update IS_PROMOTED to IS_IN_SECONDARY_CACHE to prevent confusions.
2. This PR updates SecondaryCacheResultHandle and use IsErasedFromSecondaryCache to determine whether the handle is erased in the secondary cache. Then, the caller can determine whether to SetIsInSecondaryCache().
3. Rename LRUSecondaryCache to CompressedSecondaryCache.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/9747

Test Plan:
**Test Scripts:**
1. Populate a DB. The on disk footprint is 482 MB. The data is set to be 50% compressible, so the total decompressed size is expected to be 964 MB.
./db_bench --benchmarks=fillrandom --num=10000000 -db=/db_bench_1

2. overwrite it to a stable state:
./db_bench --benchmarks=overwrite,stats --num=10000000 -use_existing_db -duration=10 --benchmark_write_rate_limit=2000000 -db=/db_bench_1

4. Run read tests with diffeernt cache setting:

T1:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=520000000  --statistics -db=/db_bench_1

T2:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=320000000 -compressed_secondary_cache_size=400000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1

T3:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=520000000 -compressed_secondary_cache_size=400000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1

T4:
./db_bench --benchmarks=seekrandom,stats --threads=16 --num=10000000 -use_existing_db -duration=120 --benchmark_write_rate_limit=52000000 -use_direct_reads --cache_size=20000000 -compressed_secondary_cache_size=500000000 --statistics -use_compressed_secondary_cache -db=/db_bench_1

**Before this PR**
| Cache Size | Compressed Secondary Cache Size | Cache Hit Rate |
|------------|-------------------------------------|----------------|
|520 MB | 0 MB | 85.5% |
|320 MB | 400 MB | 96.2% |
|520 MB | 400 MB | 98.3% |
|20 MB | 500 MB | 98.8% |

**Before this PR**
| Cache Size | Compressed Secondary Cache Size | Cache Hit Rate |
|------------|-------------------------------------|----------------|
|520 MB | 0 MB | 85.5% |
|320 MB | 400 MB | 99.9% |
|520 MB | 400 MB | 99.9% |
|20 MB | 500 MB | 99.2% |

Reviewed By: anand1976

Differential Revision: D35117499

Pulled By: gitbw95

fbshipit-source-id: ea2657749fc13efebe91a8a1b56bc61d6a224a12

Summary:
**Summary:**
RocksDB uses a block cache to reduce IO and make queries more efficient. The block cache is based on the LRU algorithm (LRUCache) and keeps objects containing uncompressed data, such as Block, ParsedFullFilterBlock etc. It allows the user to configure a second level cache (rocksdb::SecondaryCache) to extend the primary block cache by holding items evicted from it. Some of the major RocksDB users, like MyRocks, use direct IO and would like to use a primary block cache for uncompressed data and a secondary cache for compressed data. The latter allows us to mitigate the loss of the Linux page cache due to direct IO.

This PR includes a concrete implementation of rocksdb::SecondaryCache that integrates with compression libraries such as LZ4 and implements an LRU cache to hold compressed blocks.

Pull Request resolved: https://github.com/facebook/rocksdb/pull/9518

Test Plan:
In this PR, the lru_secondary_cache_test.cc includes the following tests:
1. The unit tests for the secondary cache with either compression or no compression, such as basic tests, fails tests.
2. The integration tests with both primary cache and this secondary cache .

**Follow Up:**

1. Statistics (e.g. compression ratio) will be added in another PR.
2. Once this implementation is ready, I will do some shadow testing and benchmarking with UDB to measure the impact.

Reviewed By: anand1976

Differential Revision: D34430930

Pulled By: gitbw95

fbshipit-source-id: 218d78b672a2f914856d8a90ff32f2f5b5043ded