Files
scylladb/service/tablet_allocator.hh
Tomasz Grabiec b9c88fdf4b tablets: load balancer: Use random selection of candidates when moving tablets
In order to avoid per-table tablet load imbalance balance from forming
in the cluster after adding nodes, the load balancer now picks the
candidate tablet at random. This should keep the per-table
distribution on the target node similar to the distribution on the
source nodes.

Currently, candidate selection picks the first tablet in the
unordered_set, so the distribution depends on hashing in the unordered
set. Due to the way hash is calculated, table id dominates the hash
and a single table can be chosen more often for migration away. This
can result in imbalance of tablets for any given table after
bootstrapping a new node.

For example, consider the following results of a simulation which
starts with a 6-node cluster and does a sequence of node bootstraps
and decommissions.  One table has 4096 tablets and RF=1, and the other
has 256 tablets and RF=2.  Before the patch, the smaller table has
node overcommit of 2.34 in the worst topology state, while after the
patch it has overcommit of 1.65. overcommit is calculated as max load
(tablet count per node) dividied by perfect average load (all tablets / nodes):

  Run #861, params: {iterations=6, nodes=6, tablets1=4096 (10.7/sh), tablets2=256 (1.3/sh), rf1=1, rf2=2, shards=64}
  Overcommit       : init : {table1={shard=1.03, node=1.00}, table2={shard=1.51, node=1.01}}
  Overcommit       : worst: {table1={shard=1.23, node=1.10}, table2={shard=9.85, node=1.65}}
  Overcommit (old) : init : {table1={shard=1.03, node=1.00}, table2={shard=1.51, node=1.01}}
  Overcommit (old) : worst: {table1={shard=1.31, node=1.12}, table2={shard=64.00, node=2.34}}

The worst state before the patch had the following distribution of tablets for the smaller table:

  Load on host ba7f866d...: total=171, min=1, max=7, spread=6, avg=2.67, overcommit=2.62
  Load on host 4049ae8d...: total=102, min=0, max=6, spread=6, avg=1.59, overcommit=3.76
  Load on host 3b499995...: total=89, min=0, max=4, spread=4, avg=1.39, overcommit=2.88
  Load on host ad33bede...: total=63, min=0, max=3, spread=3, avg=0.98, overcommit=3.05
  Load on host 0c2e65dc...: total=57, min=0, max=3, spread=3, avg=0.89, overcommit=3.37
  Load on host 3f2d32d4...: total=27, min=0, max=2, spread=2, avg=0.42, overcommit=4.74
  Load on host 9de9f71b...: total=3, min=0, max=1, spread=1, avg=0.05, overcommit=21.33

One node has as many as 171 tablets of that table and the one has as few as 3.

After the patch, the worst distribution looks like this:

  Load on host 94a02049...: total=121, min=1, max=6, spread=5, avg=1.89, overcommit=3.17
  Load on host 65ac6145...: total=87, min=0, max=5, spread=5, avg=1.36, overcommit=3.68
  Load on host 856a66d1...: total=80, min=0, max=5, spread=5, avg=1.25, overcommit=4.00
  Load on host e3ac4a41...: total=77, min=0, max=4, spread=4, avg=1.20, overcommit=3.32
  Load on host 81af623f...: total=66, min=0, max=4, spread=4, avg=1.03, overcommit=3.88
  Load on host 4a038569...: total=47, min=0, max=2, spread=2, avg=0.73, overcommit=2.72
  Load on host c6ab3fe9...: total=34, min=0, max=3, spread=3, avg=0.53, overcommit=5.65

Most-loaded node has 121 tablets and least loaded node has 34 tablets.
It's still not good, a better distribution is possible, but it's an improvement.

Refs #16824

(cherry picked from commit 603abddca9)
2024-06-02 22:40:46 +00:00

135 lines
4.7 KiB
C++

/*
* Copyright (C) 2023-present ScyllaDB
*/
/*
* SPDX-License-Identifier: AGPL-3.0-or-later
*/
#pragma once
#include "replica/database_fwd.hh"
#include "locator/tablets.hh"
#include "tablet_allocator_fwd.hh"
#include "locator/token_metadata_fwd.hh"
namespace service {
using tablet_migration_info = locator::tablet_migration_info;
/// Represents intention to emit resize (split or merge) request for a
/// table, and finalize or revoke the request previously initiated.
struct table_resize_plan {
std::unordered_map<table_id, locator::resize_decision> resize;
std::unordered_set<table_id> finalize_resize;
size_t size() const { return resize.size() + finalize_resize.size(); }
void merge(table_resize_plan&& other) {
for (auto&& [id, other_resize] : other.resize) {
if (!resize.contains(id) || other_resize.sequence_number > resize[id].sequence_number) {
resize[id] = std::move(other_resize);
}
}
finalize_resize.merge(std::move(other.finalize_resize));
}
};
class migration_plan {
public:
using migrations_vector = utils::chunked_vector<tablet_migration_info>;
private:
migrations_vector _migrations;
table_resize_plan _resize_plan;
bool _has_nodes_to_drain = false;
public:
/// Returns true iff there are decommissioning nodes which own some tablet replicas.
bool has_nodes_to_drain() const { return _has_nodes_to_drain; }
const migrations_vector& migrations() const { return _migrations; }
bool empty() const { return _migrations.empty() && !_resize_plan.size(); }
size_t size() const { return _migrations.size() + _resize_plan.size(); }
size_t tablet_migration_count() const { return _migrations.size(); }
size_t resize_decision_count() const { return _resize_plan.size(); }
void add(tablet_migration_info info) {
_migrations.emplace_back(std::move(info));
}
void merge(migration_plan&& other) {
std::move(other._migrations.begin(), other._migrations.end(), std::back_inserter(_migrations));
_has_nodes_to_drain |= other._has_nodes_to_drain;
_resize_plan.merge(std::move(other._resize_plan));
}
void set_has_nodes_to_drain(bool b) {
_has_nodes_to_drain = b;
}
const table_resize_plan& resize_plan() const { return _resize_plan; }
void set_resize_plan(table_resize_plan resize_plan) {
_resize_plan = std::move(resize_plan);
}
};
class migration_notifier;
class tablet_allocator {
public:
struct config {
unsigned initial_tablets_scale = 1;
};
class impl {
public:
virtual ~impl() = default;
};
private:
std::unique_ptr<impl> _impl;
tablet_allocator_impl& impl();
public:
tablet_allocator(config cfg, service::migration_notifier& mn, replica::database& db);
public:
future<> stop();
/// Returns a tablet migration plan that aims to achieve better load balance in the whole cluster.
/// The plan is computed based on information in the given token_metadata snapshot
/// and thus should be executed and reflected, at least as pending tablet transitions, in token_metadata
/// before this is called again.
///
/// For any given global_tablet_id there is at most one tablet_migration_info in the returned plan.
///
/// To achieve full balance, do:
///
/// while (true) {
/// auto plan = co_await balance_tablets(get_token_metadata());
/// if (plan.empty()) {
/// break;
/// }
/// co_await execute(plan);
/// }
///
/// It is ok to invoke the algorithm with already active tablet migrations. The algorithm will take them into account
/// when balancing the load as if they already succeeded. This means that applying a series of migration plans
/// produced by this function will give the same result regardless of whether applying means they are fully executed or
/// only initiated by creating corresponding transitions in tablet metadata.
///
/// The algorithm takes care of limiting the streaming load on the system, also by taking active migrations into account.
///
future<migration_plan> balance_tablets(locator::token_metadata_ptr, locator::load_stats_ptr = {}, std::unordered_set<locator::host_id> = {});
void set_use_table_aware_balancing(bool);
future<locator::tablet_map> split_tablets(locator::token_metadata_ptr, table_id);
/// Should be called when the node is no longer a leader.
void on_leadership_lost();
};
}
template <>
struct fmt::formatter<service::tablet_migration_info> : fmt::formatter<string_view> {
auto format(const service::tablet_migration_info&, fmt::format_context& ctx) const -> decltype(ctx.out());
};