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b06dffcc19
"0c6bbc8refactored `get_rpc_client_idx()` to select different clients for statement verbs depending on the current scheduling group. The goal was to allow statement verbs to be sent on different connections depending on the current scheduling group. The new connections use per-connection isolation. For backward compatibility the already existing connections fall-back to per-handler isolation used previously. The old statement connection, called the default statement connection, also used this. `get_rpc_client_idx()` was changed to select the default statement connection when the current scheduling group is the statement group, and a non-default connection otherwise. This inadvertently broke `scheduling_group_for_verb()` which also used this method to get the scheduling group to be used to isolate a verb at handle register time. This method needs the default client idx for each verb, but if verb registering is run under the system group it instead got the non-default one, resulting in the per-handler isolation not being set-up for the default statement connection, resulting in default statement verb handlers running in whatever scheduling group the process loop of the rpc is running in, which is the system scheduling group. This caused all sorts of problems, even beyond user queries running in the system group. Also as of0c6bbc8queries on the replicas are classified based on the scheduling group they are running on, so user reads also ended up using the system concurrency semaphore. In particular this caused severe problems with ranges scans, which in some cases ended up using different semaphores per page resulting in a crash. This could happen because when the page was read locally the code would run in the statement scheduling group, but when the request arrived from a remote coordinator via rpc, it was read in a system scheduling group. This caused a mismatch between the semaphore the saved reader was created with and the one the new page was read with. The result was that in some cases when looking up a paused reader from the wrong semaphore, a reader belonging to another read was returned, creating a disconnect between the lifecycle between readers and that of the slice and range they were referencing. This series fixes the underlying problem of the scheduling group influencing the verb handler registration, as well as adding some additional defenses if this semaphore mismatch ever happens in the future. Inactive read handles are now unique across all semaphores, meaning that it is not possible anymore that a handle succeeds in looking up a reader when used with the wrong semaphore. The range scan algorithm now also makes sure there is no semaphore mismatch between the one used for the current page and that of the saved reader from the previous page. I manually checked that each individual defense added is already preventing the crash from happening. Fixes: #6613 Fixes: #6907 Fixes: #6908 Tests: unit(dev), manual(run the crash reproducer, observe no crash) " * 'query-classification-regressions/v1' of https://github.com/denesb/scylla: multishard_mutation_query: use cached semaphore messaging: make verb handler registering independent of current scheduling group multishard_mutation_query: validate the semaphore of the looked-up reader reader_concurrency_semaphore: make inactive read handles unique across semaphores reader_concurrency_semaphore: add name() accessor reader_concurrency_semaphore: allow passing name to no-limit constructor (cherry picked from commit3f84d41880)
Scylla
Quick-start
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 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 and running Scylla with the frozen toolchain is as easy as:
$ ./tools/toolchain/dbuild ./configure.py
$ ./tools/toolchain/dbuild ninja build/release/scylla
$ ./tools/toolchain/dbuild ./build/release/scylla --developer-mode 1
Running Scylla
- Run Scylla
./build/release/scylla
- run Scylla with one CPU and ./tmp as work directory
./build/release/scylla --workdir tmp --smp 1
- For more run options:
./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 experimental support for the API of Amazon DynamoDB, but being experimental it needs to be explicitly enabled to be used. For more information on how to enable the experimental DynamoDB compatibility in Scylla, and the current limitations of this feature, see Alternator and Getting started with Alternator.
Documentation
Documentation can be found in ./docs and on the wiki. There is currently no clear definition of what goes where, so when looking for something be sure to check both. 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.
Building a CentOS-based Docker image
Build a Docker image with:
cd dist/docker/redhat
docker build -t <image-name> .
This build is based on executables downloaded from downloads.scylladb.com, not on the executables built in this source directory. See further instructions in dist/docker/redhat/README.md to build a docker image from your own executables.
Run the image with:
docker run -p $(hostname -i):9042:9042 -i -t <image name>