5285ccbb12
This series is split from another, bigger RFC series which provides manual remedies to deal with inconsistencies between the base table and its views. This part deals with ghost rows by providing a statement which fetches view rows from a given range, then reads its corresponding rows from the base table (cl=ALL), and finally removes rows which were not present in the base table at all, qualifying them as ghost rows. Motivations for introducing such a statement: * in case of detected inconsistencies, it can be used to fix materialized views without recreating them from scratch, which can take days and generates lots of throughput * a tool which periodically scrubs a materialized view can be easily created on top of this statement, especially that it's possible to remove ghost rows from a user-defined view token range; This series comes with a unit test. The reason for digging up this series is because it's still possible to end up with ghost rows in certain rather improbable scenarios, and we lack a way of fixing them without rebuilding the whole view. For instance, in case of a failed synchronous update to a local view, the user will be notified that the query failed, but a ghost row can be created nonetheless. The pruning statement introduced in this series would allow healing the failure locally, without rebuilding the whole view. Tests: unit(dev) Closes #10426 * github.com:scylladb/scylla: docs: add a paragraph on PRUNE MATERIALIZED VIEW statement service,test: add a test case for error during pruning tests: add ghost row deletion test case cql3: enable ghost row deletion via CQL cql3: add a statement for deleting ghost rows cql3: convert is_json statement parameter to enum pager: add ghost row deleting pager db,view: add delete ghost rows visitor
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 users mailing list 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.