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75fb45df1b
This PR propagates the read coordinator logic so that read timeout and read failure exceptions are propagated without throwing on the coordinator side.
This PR is only concerned with exceptions which were originally thrown by the coordinator (in read resolvers). Exceptions propagated through RPC and RPC timeouts will still throw, although those exceptions will be caught and converted into exceptions-as-values by read resolvers.
This is a continuation of work started in #10014.
Results of `perf_simple_query --smp 1 --operations-per-shard 1000000` (read workload), compared with merge base (10880fb0a7):
```
BEFORE:
125085.13 tps ( 80.2 allocs/op, 12.2 tasks/op, 49010 insns/op)
125645.88 tps ( 80.2 allocs/op, 12.2 tasks/op, 49008 insns/op)
126148.85 tps ( 80.2 allocs/op, 12.2 tasks/op, 49005 insns/op)
126044.40 tps ( 80.2 allocs/op, 12.2 tasks/op, 49005 insns/op)
125799.75 tps ( 80.2 allocs/op, 12.2 tasks/op, 49003 insns/op)
AFTER:
127557.21 tps ( 80.2 allocs/op, 12.2 tasks/op, 49197 insns/op)
127835.98 tps ( 80.2 allocs/op, 12.2 tasks/op, 49198 insns/op)
127749.81 tps ( 80.2 allocs/op, 12.2 tasks/op, 49202 insns/op)
128941.17 tps ( 80.2 allocs/op, 12.2 tasks/op, 49192 insns/op)
129276.15 tps ( 80.2 allocs/op, 12.2 tasks/op, 49182 insns/op)
```
The PR does not introduce additional allocations on the read happy-path. The number of instructions used grows by about 200 insns/op. The increase in TPS is probably just a measurement error.
Closes #10092
* github.com:scylladb/scylla:
indexed_table_select_statement: return some exceptions as exception messages
result_combinators: add result_wrap_unpack
select_statement: return exceptions as errors in execute_without_checking_exception_message
select_statement: return exceptions without throwing in do_execute
select_statement: implement execute_without_checking_exception_message
select_statement: introduce helpers for working with failed results
query_pager: resultify relevant methods
storage_proxy: resultify (do_)query
storage_proxy: resultify query_singular
storage_proxy: propagate failed results through query_partition_key_range
storage_proxy: resultify query_partition_key_range_concurrent
storage_proxy: modify handle_read_error to also handle exception containers
abstract_read_executor: return result from execute()
abstract_read_executor: return and handle result from has_cl()
storage_proxy: resultify handling errors from read-repair
abstract_read_executor::reconcile: resultise handling of data_resolver->done()
abstract_read_executor::execute: resultify handling of data_resolver->done()
result_combinators: add result_discard_value
abstract_read_executor: resultify _result_promise
abstract_read_executor: return result from done()
abstract_read_resolver: fail promises by passing exception as value
abstract_read_resolver: resultify promises
exceptions: make it possible to return read_{timeout,failure}_exception as value
result_try: add as_inner/clone_inner to handle types
result_try: relax ConvertWithTo constraint
exception_container: switch impl to std::shared_ptr and make copyable
result_loop: add result_repeat
result_loop: add result_do_until
result_loop: add result_map_reduce
utils/result: add utilities for checking/creating rebindable results
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.