d8a9fdddbd
In the test we perform 2 consecutive writes where the first write
is supposed to increase the view update backlog above the mv
admission control threshold and the second one is expected to be
rejected because of that.
On each node/shard we have 2 types of view update backlogs:
1. for deciding whether we should admit writes
2. for propagating the backlog information to other nodes/shards.
For the second write to be rejected, it must be performed on a node
and shard which updated its backlog of type 1.
The view update backlog of type 2. is immediately increased on the
base table replica. For this backlog to be registered as a backlog
of type 1., it needs to be either carried by gossip (happening once
every second) or by attaching it to a replica write response. We
don't want to increase the runtime of tests unnecessarily, so we don't
wait and we rely on the second mechanism. The response to the first
base table write (the one causing increase in the backlog) carries
the increased backlog to the coordinator of this write. So for the
second write to observe the increased backlog, it needs to be coordinated
on the same node+shard as the first write.
We make sure that both writes are coordinated on the same node+shard by
using prepared statements combined with setting the host in `run_async`.
Both writes target the same partition and with prepared statements we
route them directly to the correct shard.
That was the idea, at least. In practice, for the driver to learn the
correct shard, it first needs to learn the token->shard mapping from
the server. For vnodes it can expect a shard by calculating the token
of the affected partition, but for tablets, it had no opportunity to
learn the tablet->shard mapping so the first write may route to any shard.
Additionally, we aren't guaranteed that the driver established connections
to all shards on all nodes at the point of any write. So if a connection
finishes establishing between the two writes, this may also cause us to
coordinate these 2 writes on different shards, leading to a missed view
backlog growth and not-rejected second write.
We fix this in this patch by running the test using one shard on each node.
This way, as long as we perform both writes on the same node, they'll also
be coordinated on the same shard. This also makes the prepared statement and
BoundStatement unnecessary — we can use SimpleStatement with
FallthroughRetryPolicy directly.
Fixes: SCYLLADB-1957
Closes scylladb/scylladb#29862
(cherry picked from commit f3cf20803b)
Closes scylladb/scylladb#29873
Closes scylladb/scylladb#29879
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.