f2ed9fcd7e
Schema digest is calculated by querying for mutations of all schema
tables, then compacting them so that all tombstones in them are
dropped. However, even if the mutation becomes empty after compaction,
we still feed its partition key. If the same mutations were compacted
prior to the query, because the tombstones expire, we won't get any
mutation at all and won't feed the partition key. So schema digest
will change once an empty partition of some schema table is compacted
away.
Tombstones expire 7 days after schema change which introduces them. If
one of the nodes is restarted after that, it will compute a different
table schema digest on boot. This may cause performance problems. When
sending a request from coordinator to replica, the replica needs
schema_ptr of exact schema version request by the coordinator. If it
doesn't know that version, it will request it from the coordinator and
perform a full schema merge. This adds latency to every such request.
Schema versions which are not referenced are currently kept in cache
for only 1 second, so if request flow has low-enough rate, this
situation results in perpetual schema pulls.
After ae8d2a550d, it is more liekly to
run into this situation, because table creation generates tombstones
for all schema tables relevant to the table, even the ones which
will be otherwise empty for the new table (e.g. computed_columns).
This change inroduces a cluster feature which when enabled will change
digest calculation to be insensitive to expiry by ignoring empty
partitions in digest calculation. When the feature is enabled,
schema_ptrs are reloaded so that the window of discrepancy during
transition is short and no rolling restart is required.
A similar problem was fixed for per-node digest calculation in
18f484cc753d17d1e3658bcb5c73ed8f319d32e8. Per-table digest calculation
was not fixed at that time because we didn't persist enabled features
and they were not enabled early-enough on boot for us to depend on
them in digest calculation. Now they are enabled before non-system
tables are loaded so digest calculation can rely on cluster features.
Fixes #4485.
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++20 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 APIs - CQL and Thrift. 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 the ScyllaDB open source.
- The developers mailing list is for developers and people interested in following the development of ScyllaDB to discuss technical topics.