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1f7dca0225
This applies to small partition workload where index pages have high partition count, and the index doesn't fit in cache. It was observed that the count can be in the order of hundreds. In such a workload pages undergo constant population, LSA compaction, and LSA eviction, which has severe impact on CPU utilization.
Refs https://scylladb.atlassian.net/browse/SCYLLADB-620
This PR reduces the impact by several changes:
- reducing memory footprint in the partition index. Assuming partition key size is 16 bytes, the cost dropped from 96 bytes to 36 bytes per partition.
- flattening the object graph and amortizing storage. Storing entries directly in the vector. Storing all key values in a single managed_bytes. Making index_entry a trivial struct.
- index entries and key storage are now trivially moveable, and batched inside vector storage
so LSA migration can use memcpy(), which amortizes the cost per key. This reduces the cost of LSA segment compaction.
- LSA eviction is now pretty much constant time for the whole page
regardless of the number of entries, because elements are trivial and batched inside vectors.
Page eviction cost dropped from 50 us to 1 us.
Performance evaluated with:
scylla perf-simple-query -c1 -m200M --partitions=1000000
Before:
```
7774.96 tps (166.0 allocs/op, 521.7 logallocs/op, 54.0 tasks/op, 802428 insns/op, 430457 cycles/op, 0 errors)
7511.08 tps (166.1 allocs/op, 527.2 logallocs/op, 54.0 tasks/op, 804185 insns/op, 430752 cycles/op, 0 errors)
7740.44 tps (166.3 allocs/op, 526.2 logallocs/op, 54.2 tasks/op, 805347 insns/op, 432117 cycles/op, 0 errors)
7818.72 tps (165.2 allocs/op, 517.6 logallocs/op, 53.7 tasks/op, 794965 insns/op, 427751 cycles/op, 0 errors)
7865.49 tps (165.1 allocs/op, 513.3 logallocs/op, 53.6 tasks/op, 788898 insns/op, 425171 cycles/op, 0 errors)
```
After (+318%):
```
32492.40 tps (130.7 allocs/op, 12.8 logallocs/op, 36.1 tasks/op, 109236 insns/op, 103203 cycles/op, 0 errors)
32591.99 tps (130.4 allocs/op, 12.8 logallocs/op, 36.0 tasks/op, 108947 insns/op, 102889 cycles/op, 0 errors)
32514.52 tps (130.6 allocs/op, 12.8 logallocs/op, 36.0 tasks/op, 109118 insns/op, 103219 cycles/op, 0 errors)
32491.14 tps (130.6 allocs/op, 12.8 logallocs/op, 36.0 tasks/op, 109349 insns/op, 103272 cycles/op, 0 errors)
32582.90 tps (130.5 allocs/op, 12.8 logallocs/op, 36.0 tasks/op, 109269 insns/op, 102872 cycles/op, 0 errors)
32479.43 tps (130.6 allocs/op, 12.8 logallocs/op, 36.0 tasks/op, 109313 insns/op, 103242 cycles/op, 0 errors)
32418.48 tps (130.7 allocs/op, 12.8 logallocs/op, 36.1 tasks/op, 109201 insns/op, 103301 cycles/op, 0 errors)
31394.14 tps (130.7 allocs/op, 12.8 logallocs/op, 36.1 tasks/op, 109267 insns/op, 103301 cycles/op, 0 errors)
32298.55 tps (130.7 allocs/op, 12.8 logallocs/op, 36.1 tasks/op, 109323 insns/op, 103551 cycles/op, 0 errors)
```
When the workload is miss-only, with both row cache and index cache disabled (no cache maintenance cost):
perf-simple-query -c1 -m200M --duration 6000 --partitions=100000 --enable-index-cache=0 --enable-cache=0
Before:
```
9124.57 tps (146.2 allocs/op, 789.0 logallocs/op, 45.3 tasks/op, 889320 insns/op, 357937 cycles/op, 0 errors)
9437.23 tps (146.1 allocs/op, 789.3 logallocs/op, 45.3 tasks/op, 889613 insns/op, 357782 cycles/op, 0 errors)
9455.65 tps (146.0 allocs/op, 787.4 logallocs/op, 45.2 tasks/op, 887606 insns/op, 357167 cycles/op, 0 errors)
9451.22 tps (146.0 allocs/op, 787.4 logallocs/op, 45.3 tasks/op, 887627 insns/op, 357357 cycles/op, 0 errors)
9429.50 tps (146.0 allocs/op, 787.4 logallocs/op, 45.3 tasks/op, 887761 insns/op, 358148 cycles/op, 0 errors)
9430.29 tps (146.1 allocs/op, 788.2 logallocs/op, 45.3 tasks/op, 888501 insns/op, 357679 cycles/op, 0 errors)
9454.08 tps (146.0 allocs/op, 787.3 logallocs/op, 45.3 tasks/op, 887545 insns/op, 357132 cycles/op, 0 errors)
```
After (+55%):
```
14484.84 tps (150.7 allocs/op, 6.5 logallocs/op, 44.7 tasks/op, 396164 insns/op, 229490 cycles/op, 0 errors)
14526.21 tps (150.8 allocs/op, 6.5 logallocs/op, 44.8 tasks/op, 396401 insns/op, 228824 cycles/op, 0 errors)
14567.53 tps (150.7 allocs/op, 6.5 logallocs/op, 44.7 tasks/op, 396319 insns/op, 228701 cycles/op, 0 errors)
14545.63 tps (150.6 allocs/op, 6.5 logallocs/op, 44.7 tasks/op, 395889 insns/op, 228493 cycles/op, 0 errors)
14626.06 tps (150.5 allocs/op, 6.5 logallocs/op, 44.7 tasks/op, 395254 insns/op, 227891 cycles/op, 0 errors)
14593.74 tps (150.5 allocs/op, 6.5 logallocs/op, 44.7 tasks/op, 395480 insns/op, 227993 cycles/op, 0 errors)
14538.10 tps (150.8 allocs/op, 6.5 logallocs/op, 44.8 tasks/op, 397035 insns/op, 228831 cycles/op, 0 errors)
14527.18 tps (150.8 allocs/op, 6.5 logallocs/op, 44.8 tasks/op, 396992 insns/op, 228839 cycles/op, 0 errors)
```
Same as above, but with summary ratio increased from 0.0005 to 0.005 (smaller pages):
Before:
```
33906.70 tps (146.1 allocs/op, 83.6 logallocs/op, 45.1 tasks/op, 170553 insns/op, 98104 cycles/op, 0 errors)
32696.16 tps (146.0 allocs/op, 83.5 logallocs/op, 45.1 tasks/op, 170369 insns/op, 98405 cycles/op, 0 errors)
33889.05 tps (146.1 allocs/op, 83.6 logallocs/op, 45.1 tasks/op, 170551 insns/op, 98135 cycles/op, 0 errors)
33893.24 tps (146.1 allocs/op, 83.5 logallocs/op, 45.1 tasks/op, 170488 insns/op, 98168 cycles/op, 0 errors)
33836.73 tps (146.1 allocs/op, 83.6 logallocs/op, 45.1 tasks/op, 170528 insns/op, 98226 cycles/op, 0 errors)
33897.61 tps (146.0 allocs/op, 83.5 logallocs/op, 45.1 tasks/op, 170428 insns/op, 98081 cycles/op, 0 errors)
33834.73 tps (146.1 allocs/op, 83.5 logallocs/op, 45.1 tasks/op, 170438 insns/op, 98178 cycles/op, 0 errors)
33776.31 tps (146.3 allocs/op, 83.9 logallocs/op, 45.2 tasks/op, 170958 insns/op, 98418 cycles/op, 0 errors)
33808.08 tps (146.3 allocs/op, 83.9 logallocs/op, 45.2 tasks/op, 170940 insns/op, 98388 cycles/op, 0 errors)
```
After (+18%):
```
40081.51 tps (148.2 allocs/op, 4.4 logallocs/op, 45.0 tasks/op, 121047 insns/op, 82231 cycles/op, 0 errors)
40005.85 tps (148.6 allocs/op, 4.4 logallocs/op, 45.2 tasks/op, 121327 insns/op, 82545 cycles/op, 0 errors)
39816.75 tps (148.3 allocs/op, 4.4 logallocs/op, 45.1 tasks/op, 121067 insns/op, 82419 cycles/op, 0 errors)
39953.11 tps (148.1 allocs/op, 4.4 logallocs/op, 45.0 tasks/op, 121027 insns/op, 82258 cycles/op, 0 errors)
40073.96 tps (148.2 allocs/op, 4.4 logallocs/op, 45.0 tasks/op, 121006 insns/op, 82313 cycles/op, 0 errors)
39882.25 tps (148.2 allocs/op, 4.4 logallocs/op, 45.0 tasks/op, 120925 insns/op, 82320 cycles/op, 0 errors)
39916.08 tps (148.3 allocs/op, 4.4 logallocs/op, 45.1 tasks/op, 121054 insns/op, 82393 cycles/op, 0 errors)
39786.30 tps (148.2 allocs/op, 4.4 logallocs/op, 45.0 tasks/op, 121027 insns/op, 82465 cycles/op, 0 errors)
38662.45 tps (148.3 allocs/op, 4.4 logallocs/op, 45.0 tasks/op, 121108 insns/op, 82312 cycles/op, 0 errors)
39849.42 tps (148.3 allocs/op, 4.4 logallocs/op, 45.1 tasks/op, 121098 insns/op, 82447 cycles/op, 0 errors)
```
Closes scylladb/scylladb#28603
* github.com:scylladb/scylladb:
sstables: mx: index_reader: Optimize parsing for no promoted index case
vint: Use std::countl_zero()
test: sstable_partition_index_cache_test: Validate scenario of pages with sparse promoted index placement
sstables: mx: index_reader: Amoritze partition key storage
managed_bytes: Hoist write_fragmented() to common header
utils: managed_vector: Use std::uninitialized_move() to move objects
sstables: mx: index_reader: Keep promoted_index info next to index_entry
sstables: mx: index_reader: Extract partition_index_page::clear_gently()
sstables: mx: index_reader: Shave-off 16 bytes from index_entry by using raw_token
sstables: mx: index_reader: Reduce allocation_section overhead during index page parsing by batching allocation
sstables: mx: index_reader: Keep index_entry directly in the vector
dht: Introduce raw_token
test: perf_simple_query: Add 'sstable-format' command-line option
test: perf_simple_query: Add 'sstable-summary-ratio' command-line option
test: perf-simple-query: Add option to disable index cache
test: cql_test_env: Respect enable-index-cache config
(cherry picked from commit 5e7fb08bf3)
Closes scylladb/scylladb#29136
Closes scylladb/scylladb#29140
Scylla
What is Scylla?
Scylla is the real-time big data database that is API-compatible with Apache Cassandra and Amazon DynamoDB. Scylla embraces a shared-nothing approach that increases throughput and storage capacity to realize order-of-magnitude performance improvements and reduce hardware costs.
For more information, please see the ScyllaDB web site.
Build Prerequisites
Scylla is fairly fussy about its build environment, requiring very recent versions of the C++23 compiler and of many libraries to build. The document HACKING.md includes detailed information on building and developing Scylla, but to get Scylla building quickly on (almost) any build machine, Scylla offers a frozen toolchain, This is a pre-configured Docker image which includes recent versions of all the required compilers, libraries and build tools. Using the frozen toolchain allows you to avoid changing anything in your build machine to meet Scylla's requirements - you just need to meet the frozen toolchain's prerequisites (mostly, Docker or Podman being available).
Building Scylla
Building Scylla with the frozen toolchain dbuild is as easy as:
$ git submodule update --init --force --recursive
$ ./tools/toolchain/dbuild ./configure.py
$ ./tools/toolchain/dbuild ninja build/release/scylla
For further information, please see:
- Developer documentation for more information on building Scylla.
- Build documentation on how to build Scylla binaries, tests, and packages.
- Docker image build documentation for information on how to build Docker images.
Running Scylla
To start Scylla server, run:
$ ./tools/toolchain/dbuild ./build/release/scylla --workdir tmp --smp 1 --developer-mode 1
This will start a Scylla node with one CPU core allocated to it and data files stored in the tmp directory.
The --developer-mode is needed to disable the various checks Scylla performs at startup to ensure the machine is configured for maximum performance (not relevant on development workstations).
Please note that you need to run Scylla with dbuild if you built it with the frozen toolchain.
For more run options, run:
$ ./tools/toolchain/dbuild ./build/release/scylla --help
Testing
See test.py manual.
Scylla APIs and compatibility
By default, Scylla is compatible with Apache Cassandra and its API - CQL. There is also support for the API of Amazon DynamoDB™, which needs to be enabled and configured in order to be used. For more information on how to enable the DynamoDB™ API in Scylla, and the current compatibility of this feature as well as Scylla-specific extensions, see Alternator and Getting started with Alternator.
Documentation
Documentation can be found here. Seastar documentation can be found here. User documentation can be found here.
Training
Training material and online courses can be found at Scylla University. The courses are free, self-paced and include hands-on examples. They cover a variety of topics including Scylla data modeling, administration, architecture, basic NoSQL concepts, using drivers for application development, Scylla setup, failover, compactions, multi-datacenters and how Scylla integrates with third-party applications.
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