d14d07a079
Commitce00d61917("db: implement large_data virtual tables with feature flag gating") changed these two tests to construct their mutation with a randomly generated partition key (simple_schema::make_pkey()) instead of the previously fixed pk "pv", with the comment that this avoids a "Failed to generate sharding metadata" error. simple_schema::make_pkey() delegates to tests::generate_partition_key(), which defaults to key_size{1, 128}, i.e. the partition key length is uniformly random in [1, 128] bytes. That interacts badly with the fact that both tests pick thresholds at exact byte boundaries of the MC sstable row encoding: - The large-data handler records a row's size as _data_writer->offset() - current_pos (sstables/mx/writer.cc: collect_row_stats()), i.e. the number of bytes the row took on disk. - For the first clustering row, the body includes a vint-encoded prev_row_size = pos - _prev_row_start. - _prev_row_start is captured at the start of the partition (consume_new_partition()) before the partition key is written to the data stream, so prev_row_size rolls in the partition key's serialized length (2-byte prefix + pk bytes) + deletion_time + static row size. A random-size partition key therefore perturbs the first clustering row's encoded size by 1-2 bytes across runs (the vint of prev_row_size crosses the 128 boundary), flipping the test's byte-exact threshold comparison. On seed 2104744000 this produced: critical check row_size_count == expected.size() has failed [3 != 2] Fix the two byte-exact-sensitive tests by reverting their partition key to the fixed s.new_mutation("pv") used beforece00d61917. Under smp=1 (which these tests run with, per -c1 in the test invocation) a fixed key is always shard-local, so no sharding-metadata issue arises here. The other tests modified byce00d61917(test_sstable_log_too_many_rows, test_sstable_log_too_many_dead_rows, test_sstable_too_many_collection_elements, test_large_data_records_round_trip, etc.) assert on row/element counts or use thresholds with enough slack that the partition key size does not matter, and are left unchanged. Add an explanatory comment to each fixed site so the pitfall is not re-introduced by a future refactor. Verified stable with: ./test.py --mode=dev test/boost/sstable_3_x_test.cc::test_sstable_write_large_row --repeat 100 --max-failures 1 ./test.py --mode=dev test/boost/sstable_3_x_test.cc::test_sstable_write_large_cell --repeat 100 --max-failures 1 ./test.py --mode=release test/boost/sstable_3_x_test.cc::test_sstable_write_large_row --repeat 100 --max-failures 1 ./test.py --mode=release test/boost/sstable_3_x_test.cc::test_sstable_write_large_cell --repeat 100 --max-failures 1 All four invocations: 100/100 passed. Fixes: SCYLLADB-1685 Closes scylladb/scylladb#29621
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.