cdb1499898
The interval class's memory footprint isn't important for single objects, but intervals are frequently held in moderately sized collections. In #3335 this caused a stall. Therefore reducing interval's memory footprint and reduce allocation pressure. This series does this by consolidating badly-padded booleans in the object tree spanned by interval into 5 booleans that are consecutive in memory. This reduces the space required by these booleans from 40 bytes to 8 bytes. perf-simple-query report (with refresh-pgo-profiles.sh for each measurement): before: 252127.60 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37128 insns/op, 18147 cycles/op, 0 errors) INFO 2025-06-07 21:00:34,010 [shard 0:main] group0_tombstone_gc_handler - Setting reconcile time to 1749319231 (min id=4dbed2f4-43c9-11f0-cbc6-87d1a08b4ca4) 246492.37 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37153 insns/op, 18411 cycles/op, 0 errors) 253633.11 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37127 insns/op, 17941 cycles/op, 0 errors) 254029.93 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37155 insns/op, 17951 cycles/op, 0 errors) 254465.76 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37123 insns/op, 17906 cycles/op, 0 errors) throughput: mean= 252149.75 standard-deviation=3282.75 median= 253633.11 median-absolute-deviation=1880.17 maximum=254465.76 minimum=246492.37 instructions_per_op: mean= 37137.24 standard-deviation=15.71 median= 37127.54 median-absolute-deviation=14.45 maximum=37155.24 minimum=37122.79 cpu_cycles_per_op: mean= 18071.19 standard-deviation=212.25 median= 17950.62 median-absolute-deviation=130.10 maximum=18411.50 minimum=17906.13 after: 252561.26 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37039 insns/op, 18075 cycles/op, 0 errors) 256876.44 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37022 insns/op, 17785 cycles/op, 0 errors) 257084.38 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37030 insns/op, 17840 cycles/op, 0 errors) 257305.35 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37042 insns/op, 17804 cycles/op, 0 errors) 258088.53 tps ( 66.1 allocs/op, 0.0 logallocs/op, 14.1 tasks/op, 37028 insns/op, 17778 cycles/op, 0 errors) throughput: mean= 256383.19 standard-deviation=2185.22 median= 257084.38 median-absolute-deviation=922.16 maximum=258088.53 minimum=252561.26 instructions_per_op: mean= 37032.17 standard-deviation=8.06 median= 37030.46 median-absolute-deviation=6.44 maximum=37041.83 minimum=37021.93 cpu_cycles_per_op: mean= 17856.60 standard-deviation=124.70 median= 17804.16 median-absolute-deviation=71.24 maximum=18075.50 minimum=17777.95 A small improvement is observed in instructions_per_op. It could be random fluctuations in the compiler performance, or maybe the default constructor/destructor of interval are meaningful even in this simple test. Small performance improvement, so not a backport candidate. Closes scylladb/scylladb#24232 * github.com:scylladb/scylladb: interval: reduce sizeof interval: change start()/end() not to return references to data members interval: rename start_ref() back to start() (and end_ref() etc). interval: rename start() to start_ref() (and end() etc). test: wrapping_interval_test: add more tests for intervals
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.
Contributing to Scylla
If you want to report a bug or submit a pull request or a patch, please read the contribution guidelines.
If you are a developer working on Scylla, please read the developer guidelines.
Contact
- The community forum and Slack channel are for users to discuss configuration, management, and operations of ScyllaDB.
- The developers mailing list is for developers and people interested in following the development of ScyllaDB to discuss technical topics.