62efe6616a
The primary motivation for this change is to reduce the time during which the Effective Replication Map (ERM) is retained by the mapreduce service. This ensures that long aggregate queries do not block topology operations. As ScyllaDB is generally transitioning towards tablets, and using tablets simplifies work dispatching, the decision was made to design the new algorithm specifically for tablets. The goal of the algorithm is to divide the work in such a way that each `tablet_replica` (that is <host, shard> pair) processes two tablets at a time. The new algorithm can be summarized as follows: 1. Prepare a tablet_replica -> partition_range mapping where the values cover the entire space. 2. For each tablet_replica, in parallel, take two partition ranges and dispatch them to the node hosting the replica. The ERM is released and re-acquired in each iteration, allowing the destination (i.e., tablet_replica) to change for each artition range (in such cases, the partition range is assigned to the appropriate tablet_replica). In step 1, the main difference compared to the old algorithm (dispatch_to_vnodes) is that partition ranges are assigned to a tablet_replica rather than just the host. In step 2, the main difference is that the work is divided into smaller batches, and the ERM is released and re-acquired for each batch. In the current implementation, each node can correctly handle every partition range, even if the mapreduce supercoordinator does not retain the ERM and the range is absent locally. This is because mapreduce_service::execute_on_this_shard creates a new pager that coordinates the partition range read, including obtaining its own ERM. However, every partition range that is absent locally is handled by shard 0. Therefore, proper routing of partition ranges is necessary to avoid shard 0 overload. This is why, in step 2, the ERM is retained during each batch processing, and the tablet_replica is refreshed for each processed range. Additionally, shard_id is added to mapreduce request. When shard_id is set, the entire partition range is handled by the specified shard. As the new tablet-aware mapreduce algorithm balances the workload across shards, shard_id ensure that the balance is preserved, even during events such as tablet splits. This patch series: - Refactors a bit mapreduce service, to facilitate having two algorithm versions (one for vnodes and one for tablets). - Implements tablet-aware dispatching algorithm. - Adds shard_id to mapreduce request and uses the information to handle requests entirely by selected shard. - Adds test_long_query_timeout_erm to verify the new functionality. Fixes: scylladb#21831 No backport, as it is rather new feature than a bugfix. Closes scylladb/scylladb#24383 * github.com:scylladb/scylladb: mapreduce: add missing comma and space in mapreduce_request operator<< mapreduce: add shard_id_hint to mapreduce request test: add test_long_query_timeout_erm mapreduce: add tablet-aware dispatching algorithm storage_proxy: make storage_proxy::is_alive public mapreduce: remove _shared_token_metadata from mapreduce_service mapreduce: move dispatching logic to dispatch_to_vnodes mapreduce: remove underscores from variable names mapreduce: move req_with_modified_pr handling to a new function mapreduce: change next_vnode lambda to get_next_partition_range function
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.