Files
scylladb/test/perf/tablet_load_balancing.cc
Yaniv Michael Kaul 43e337a663 db, test: add explicit includes for storage_service.hh and system_keyspace.hh
Add explicit includes that were previously available transitively through
service/storage_proxy.hh -> service/storage_service.hh.

This prepares for removing the unused storage_service.hh include from
storage_proxy.hh in a follow-up commit.

Speedup: prerequisite for storage_proxy.hh include chain reduction
(measured -5.8% wall-clock combined with all changes in this series,
same-session A/B: 16m14s -> 15m17s at -j16).
2026-04-16 18:22:41 +03:00

783 lines
32 KiB
C++

/*
* Copyright (C) 2024-present ScyllaDB
*/
/*
* SPDX-License-Identifier: LicenseRef-ScyllaDB-Source-Available-1.1
*/
#include <fmt/ranges.h>
#include <bit>
#include <seastar/core/sharded.hh>
#include <seastar/core/app-template.hh>
#include <seastar/core/sstring.hh>
#include <seastar/core/thread.hh>
#include <seastar/core/reactor.hh>
#include "locator/tablets.hh"
#include "service/tablet_allocator.hh"
#include "locator/tablet_replication_strategy.hh"
#include "locator/network_topology_strategy.hh"
#include "locator/load_sketch.hh"
#include "test/lib/topology_builder.hh"
#include "replica/tablets.hh"
#include "locator/tablet_replication_strategy.hh"
#include "db/config.hh"
#include "schema/schema_builder.hh"
#include "service/storage_proxy.hh"
#include "service/storage_service.hh"
#include "db/system_keyspace.hh"
#include "tools/utils.hh"
#include "test/perf/perf.hh"
#include "test/lib/log.hh"
#include "test/lib/cql_test_env.hh"
#include "test/lib/random_utils.hh"
#include "test/lib/key_utils.hh"
using namespace locator;
using namespace replica;
using namespace service;
using namespace tools::utils;
namespace bpo = boost::program_options;
static seastar::abort_source aborted;
static const sstring dc = "dc1";
static
cql_test_config tablet_cql_test_config() {
cql_test_config c;
return c;
}
static
future<table_id> add_table(cql_test_env& e, sstring test_ks_name = "") {
auto id = table_id(utils::UUID_gen::get_time_UUID());
co_await e.create_table([&] (std::string_view ks_name) {
if (!test_ks_name.empty()) {
ks_name = test_ks_name;
}
return *schema_builder(ks_name, id.to_sstring(), id)
.with_column("p1", utf8_type, column_kind::partition_key)
.with_column("r1", int32_type)
.build();
});
co_return id;
}
// Run in a seastar thread
static
sstring add_keyspace(cql_test_env& e, std::unordered_map<sstring, int> dc_rf, int initial_tablets = 0) {
static std::atomic<int> ks_id = 0;
auto ks_name = fmt::format("keyspace{}", ks_id.fetch_add(1));
sstring rf_options;
for (auto& [dc, rf] : dc_rf) {
rf_options += format(", '{}': {}", dc, rf);
}
e.execute_cql(fmt::format("create keyspace {} with replication = {{'class': 'NetworkTopologyStrategy'{}}}"
" and tablets = {{'enabled': true, 'initial': {}}}",
ks_name, rf_options, initial_tablets)).get();
return ks_name;
}
static
size_t get_tablet_count(const tablet_metadata& tm) {
size_t count = 0;
for (const auto& [table, tmap] : tm.all_tables_ungrouped()) {
count += std::accumulate(tmap->tablets().begin(), tmap->tablets().end(), size_t(0),
[] (size_t accumulator, const locator::tablet_info& info) {
return accumulator + info.replicas.size();
});
}
return count;
}
static
future<> apply_resize_plan(token_metadata& tm, const migration_plan& plan) {
for (auto [table_id, resize_decision] : plan.resize_plan().resize) {
co_await tm.tablets().mutate_tablet_map_async(table_id, [&resize_decision] (tablet_map& tmap) {
resize_decision.sequence_number = tmap.resize_decision().sequence_number + 1;
tmap.set_resize_decision(resize_decision);
return make_ready_future();
});
}
for (auto table_id : plan.resize_plan().finalize_resize) {
auto& old_tmap = tm.tablets().get_tablet_map(table_id);
testlog.info("Setting new tablet map of size {}", old_tmap.tablet_count() * 2);
tablet_map tmap(old_tmap.tablet_count() * 2);
tm.tablets().set_tablet_map(table_id, std::move(tmap));
}
}
// Reflects the plan in a given token metadata as if the migrations were fully executed.
static
future<> apply_plan(token_metadata& tm, const migration_plan& plan, locator::load_stats& load_stats) {
for (auto&& mig : plan.migrations()) {
co_await tm.tablets().mutate_tablet_map_async(mig.tablet.table, [&mig] (tablet_map& tmap) {
auto tinfo = tmap.get_tablet_info(mig.tablet.tablet);
tinfo.replicas = replace_replica(tinfo.replicas, mig.src, mig.dst);
tmap.set_tablet(mig.tablet.tablet, tinfo);
return make_ready_future();
});
// Move tablet size in load_stats to account for the migration
if (mig.src.host != mig.dst.host) {
auto& tmap = tm.tablets().get_tablet_map(mig.tablet.table);
const dht::token_range trange = tmap.get_token_range(mig.tablet.tablet);
lw_shared_ptr<locator::load_stats> new_stats = load_stats.migrate_tablet_size(mig.src.host, mig.dst.host, mig.tablet, trange);
if (new_stats) {
load_stats = std::move(*new_stats);
} else {
throw std::runtime_error(format("Unable to migrate tablet size in load_stats for migration: {}", mig));
}
}
}
co_await apply_resize_plan(tm, plan);
}
using seconds_double = std::chrono::duration<double>;
struct rebalance_stats {
seconds_double elapsed_time = seconds_double(0);
seconds_double max_rebalance_time = seconds_double(0);
uint64_t rebalance_count = 0;
rebalance_stats& operator+=(const rebalance_stats& other) {
elapsed_time += other.elapsed_time;
max_rebalance_time = std::max(max_rebalance_time, other.max_rebalance_time);
rebalance_count += other.rebalance_count;
return *this;
}
};
static
rebalance_stats rebalance_tablets(cql_test_env& e, locator::load_stats& load_stats, std::unordered_set<host_id> skiplist = {}) {
rebalance_stats stats;
abort_source as;
auto guard = e.get_raft_group0_client().start_operation(as).get();
auto& talloc = e.get_tablet_allocator().local();
auto& stm = e.shared_token_metadata().local();
// Sanity limit to avoid infinite loops.
// The x10 factor is arbitrary, it's there to account for more complex schedules than direct migration.
auto max_iterations = 1 + get_tablet_count(stm.get()->tablets()) * 10;
for (size_t i = 0; i < max_iterations; ++i) {
auto prev_lb_stats = *talloc.stats().for_dc(dc);
auto load_stats_p = make_lw_shared<locator::load_stats>(load_stats);
auto start_time = std::chrono::steady_clock::now();
auto plan = talloc.balance_tablets(stm.get(), nullptr, nullptr, load_stats_p, skiplist).get();
auto end_time = std::chrono::steady_clock::now();
auto lb_stats = *talloc.stats().for_dc(dc) - prev_lb_stats;
auto elapsed = std::chrono::duration_cast<seconds_double>(end_time - start_time);
rebalance_stats iteration_stats = {
.elapsed_time = elapsed,
.max_rebalance_time = elapsed,
.rebalance_count = 1,
};
stats += iteration_stats;
testlog.debug("Rebalance iteration {} took {:.3f} [s]: mig={}, bad={}, first_bad={}, eval={}, skiplist={}, skip: (load={}, rack={}, node={})",
i + 1, elapsed.count(),
lb_stats.migrations_produced,
lb_stats.bad_migrations,
lb_stats.bad_first_candidates,
lb_stats.candidates_evaluated,
lb_stats.migrations_from_skiplist,
lb_stats.migrations_skipped,
lb_stats.tablets_skipped_rack,
lb_stats.tablets_skipped_node);
if (plan.empty()) {
// We should not introduce inconsistency between on-disk state and in-memory state
// as that may violate invariants and cause failures in later operations
// causing test flakiness.
save_tablet_metadata(e.local_db(), stm.get()->tablets(), guard.write_timestamp()).get();
e.get_storage_service().local().update_tablet_metadata({}).get();
testlog.info("Rebalance took {:.3f} [s] after {} iteration(s)", stats.elapsed_time.count(), i + 1);
return stats;
}
stm.mutate_token_metadata([&] (token_metadata& tm) {
return apply_plan(tm, plan, load_stats);
}).get();
}
throw std::runtime_error("rebalance_tablets(): convergence not reached within limit");
}
struct params {
int iterations;
int nodes;
std::optional<int> tablets1;
std::optional<int> tablets2;
int rf1;
int rf2;
int shards;
int scale1 = 1;
int scale2 = 1;
double tablet_size_deviation_factor = 0.5;
};
struct table_balance {
double shard_overcommit;
double best_shard_overcommit;
double node_overcommit;
};
constexpr auto nr_tables = 2;
struct cluster_balance {
table_balance tables[nr_tables];
};
struct results {
cluster_balance init;
cluster_balance worst;
cluster_balance last;
rebalance_stats stats;
};
template<>
struct fmt::formatter<table_balance> : fmt::formatter<string_view> {
template <typename FormatContext>
auto format(const table_balance& b, FormatContext& ctx) const {
return fmt::format_to(ctx.out(), "{{shard={} (best={}), node={}}}",
b.shard_overcommit, b.best_shard_overcommit, b.node_overcommit);
}
};
template<>
struct fmt::formatter<cluster_balance> : fmt::formatter<string_view> {
template <typename FormatContext>
auto format(const cluster_balance& r, FormatContext& ctx) const {
return fmt::format_to(ctx.out(), "{{table1={}, table2={}}}", r.tables[0], r.tables[1]);
}
};
template<>
struct fmt::formatter<params> : fmt::formatter<string_view> {
template <typename FormatContext>
auto format(const params& p, FormatContext& ctx) const {
auto tablets1_per_shard = double(p.tablets1.value_or(0)) * p.rf1 / (p.nodes * p.shards);
auto tablets2_per_shard = double(p.tablets2.value_or(0)) * p.rf2 / (p.nodes * p.shards);
return fmt::format_to(ctx.out(), "{{iterations={}, nodes={}, tablets1={} ({:0.1f}/sh), tablets2={} ({:0.1f}/sh), rf1={}, rf2={}, shards={}, tablet_size_deviation_factor={}}}",
p.iterations, p.nodes,
p.tablets1.value_or(0), tablets1_per_shard,
p.tablets2.value_or(0), tablets2_per_shard,
p.rf1, p.rf2, p.shards, p.tablet_size_deviation_factor);
}
};
class tablet_size_generator {
std::default_random_engine _rnd_engine{std::random_device{}()};
std::normal_distribution<> _dist;
public:
explicit tablet_size_generator(double deviation_factor)
: _dist(default_target_tablet_size, default_target_tablet_size * deviation_factor) {
}
uint64_t generate() {
// We can't have a negative tablet size, which is why we need to minimize it to 0 (with std::max()).
// One consequence of this is that the average generated tablet size will actually
// be larger than default_target_tablet_size.
// This will be especially pronounced as deviation_factor gets larger. For instance:
//
// deviation_factor | avg tablet size
// -----------------+----------------------------------------
// 1 | default_target_tablet_size * 1.08
// 1.5 | default_target_tablet_size * 1.22
// 2 | default_target_tablet_size * 1.39
// 3 | default_target_tablet_size * 1.76
return std::max(0.0, _dist(_rnd_engine));
}
};
void generate_tablet_sizes(double tablet_size_deviation_factor, locator::load_stats& stats, locator::shared_token_metadata& stm) {
tablet_size_generator tsg(tablet_size_deviation_factor);
for (auto&& [table, tmap] : stm.get()->tablets().all_tables_ungrouped()) {
tmap->for_each_tablet([&] (tablet_id tid, const tablet_info& ti) -> future<> {
for (const auto& replica : ti.replicas) {
const uint64_t tablet_size = tsg.generate();
locator::range_based_tablet_id rb_tid {table, tmap->get_token_range(tid)};
stats.tablet_stats[replica.host].tablet_sizes[rb_tid.table][rb_tid.range] = tablet_size;
testlog.trace("Generated tablet size {} for {}:{}", tablet_size, table, tid);
}
return make_ready_future<>();
}).get();
}
}
future<results> test_load_balancing_with_many_tables(params p, bool tablet_aware) {
auto cfg = tablet_cql_test_config();
results global_res;
co_await do_with_cql_env_thread([&] (auto& e) {
SCYLLA_ASSERT(p.nodes > 0);
SCYLLA_ASSERT(p.rf1 > 0);
SCYLLA_ASSERT(p.rf2 > 0);
const size_t n_hosts = p.nodes;
const size_t rf1 = p.rf1;
const size_t rf2 = p.rf2;
const shard_id shard_count = p.shards;
const int cycles = p.iterations;
const uint64_t shard_capacity = default_target_tablet_size * 100;
struct host_info {
host_id id;
endpoint_dc_rack dc_rack;
};
topology_builder topo(e);
std::vector<endpoint_dc_rack> racks;
std::vector<host_info> hosts;
locator::load_stats stats;
auto populate_racks = [&] (const size_t count) {
SCYLLA_ASSERT(count > 0);
racks.push_back(topo.rack());
for (size_t i = 0; i < count - 1; ++i) {
racks.push_back(topo.start_new_rack());
}
};
const sstring dc1 = topo.dc();
populate_racks(rf1);
// The rack for which we output stats
sstring test_rack = racks.front().rack;
const size_t rack_count = racks.size();
std::unordered_map<sstring, uint64_t> rack_capacity;
auto add_host = [&] (endpoint_dc_rack dc_rack) {
auto host = topo.add_node(service::node_state::normal, shard_count, dc_rack);
hosts.emplace_back(host, dc_rack);
const uint64_t capacity = shard_capacity * shard_count;
stats.capacity[host] = capacity;
stats.tablet_stats[host].effective_capacity = capacity;
rack_capacity[dc_rack.rack] += capacity;
testlog.info("Added new node: {} / {}:{}", host, dc_rack.dc, dc_rack.rack);
};
for (size_t i = 0; i < n_hosts; ++i) {
add_host(racks[i % rack_count]);
}
auto& stm = e.shared_token_metadata().local();
auto bootstrap = [&] (endpoint_dc_rack dc_rack) {
add_host(std::move(dc_rack));
global_res.stats += rebalance_tablets(e, stats);
};
auto decommission = [&] (host_id host) {
const auto it = std::ranges::find_if(hosts, [&] (const host_info& info) {
return info.id == host;
});
if (it == hosts.end()) {
throw std::runtime_error(format("No such host: {}", host));
}
topo.set_node_state(host, service::node_state::decommissioning);
global_res.stats += rebalance_tablets(e, stats);
if (stm.get()->tablets().has_replica_on(host)) {
throw std::runtime_error(format("Host {} still has replicas!", host));
}
topo.set_node_state(host, service::node_state::left);
testlog.info("Node decommissioned: {}", host);
rack_capacity[it->dc_rack.rack] -= stats.capacity.at(host);
hosts.erase(it);
stats.tablet_stats.erase(host);
};
auto ks1 = add_keyspace(e, {{dc1, rf1}}, p.tablets1.value_or(1));
auto ks2 = add_keyspace(e, {{dc1, rf2}}, p.tablets2.value_or(1));
auto id1 = add_table(e, ks1).get();
auto id2 = add_table(e, ks2).get();
schema_ptr s1 = e.local_db().find_schema(id1);
schema_ptr s2 = e.local_db().find_schema(id2);
generate_tablet_sizes(p.tablet_size_deviation_factor, stats, stm);
// Compute table size per rack, and collect all tablets per rack
std::unordered_map<sstring, std::unordered_map<table_id, uint64_t>> table_sizes_per_rack;
std::unordered_map<sstring, std::unordered_map<table_id, std::vector<uint64_t>>> tablet_sizes_in_rack;
for (auto& [host, tls] : stats.tablet_stats) {
auto host_i = std::ranges::find(hosts, host, &host_info::id);
if (host_i == hosts.end()) {
throw std::runtime_error(format("Host {} not found in hosts", host));
}
auto rack = host_i->dc_rack.rack;
for (auto& [table, ranges] : tls.tablet_sizes) {
for (auto& [trange, tablet_size] : ranges) {
table_sizes_per_rack[rack][table] += tablet_size;
tablet_sizes_in_rack[rack][table].push_back(tablet_size);
}
}
}
// Sort the tablet sizes per rack in descending order
for (auto& [rack, tables] : tablet_sizes_in_rack) {
for (auto& [table, tablets] : tables) {
std::ranges::sort(tablets, std::greater<uint64_t>());
}
}
struct node_used_size {
host_id host;
uint64_t used = 0;
};
// Compute best shard overcommit per table per rack
std::unordered_map<sstring, std::unordered_map<table_id, double>> best_shard_overcommit_per_rack;
auto compute_best_overcommit = [&] () {
auto node_size_compare = [] (const node_used_size& lhs, const node_used_size& rhs) {
return lhs.used > rhs.used;
};
for (auto& all_dc_rack : racks) {
auto rack = all_dc_rack.rack;
// Allocate tablet sizes to nodes
for (auto& [table, tablet_sizes]: tablet_sizes_in_rack.at(rack)) {
load_sketch load(e.shared_token_metadata().local().get(), make_lw_shared<locator::load_stats>(stats));
// Add nodes to load_sketch and to the nodes_used heap
std::vector<node_used_size> nodes_used;
for (const auto& [host_id, host_dc_rack] : hosts) {
if (rack == host_dc_rack.rack) {
load.ensure_node(host_id);
nodes_used.push_back({host_id, 0});
}
}
// Allocate tablets to nodes/shards
for (uint64_t tablet_size : tablet_sizes) {
std::pop_heap(nodes_used.begin(), nodes_used.end(), node_size_compare);
host_id add_to_host = nodes_used.back().host;
nodes_used.back().used += tablet_size;
std::push_heap(nodes_used.begin(), nodes_used.end(), node_size_compare);
// Add to the least loaded shard on the least loaded node
load.next_shard(add_to_host, 1, tablet_size);
}
// Get the best overcommit from all the nodes
min_max_tracker<locator::disk_usage::load_type> load_minmax;
for (const auto& n : nodes_used) {
load_minmax.update(load.get_shard_minmax(n.host));
}
const uint64_t table_size = table_sizes_per_rack.at(rack).at(table);
const double ideal_load = double(table_size) / rack_capacity.at(rack);
const double best_overcommit = load_minmax.max() / ideal_load;
best_shard_overcommit_per_rack[rack][table] = best_overcommit;
}
}
};
auto check_balance = [&] () -> cluster_balance {
cluster_balance res;
testlog.debug("tablet metadata: {}", stm.get()->tablets());
compute_best_overcommit();
auto load_stats_p = make_lw_shared<locator::load_stats>(stats);
int table_index = 0;
for (auto s : {s1, s2}) {
auto table = s->id();
load_sketch load(stm.get(), load_stats_p);
load.populate(std::nullopt, table).get();
min_max_tracker<double> shard_overcommit_minmax;
min_max_tracker<double> node_overcommit_minmax;
auto rack = test_rack;
auto table_size = table_sizes_per_rack.at(rack).at(table);
auto ideal_load = double(table_size) / rack_capacity.at(rack);
min_max_tracker<double> shard_load_minmax;
min_max_tracker<double> node_load_minmax;
for (auto [h, host_dc_rack] : hosts) {
if (host_dc_rack.rack != rack) {
continue;
}
auto minmax = load.get_shard_minmax(h);
auto node_load = load.get_load(h);
auto overcommit = double(minmax.max()) / ideal_load;
testlog.info("Load on host {} for table {}: total={}, min={}, max={}, spread={}, ideal={}, overcommit={}",
h, s->cf_name(), node_load, minmax.min(), minmax.max(), minmax.max() - minmax.min(), ideal_load, overcommit);
node_load_minmax.update(node_load);
shard_load_minmax.update(minmax.max());
}
auto shard_overcommit = shard_load_minmax.max() / ideal_load;
auto best_shard_overcommit = best_shard_overcommit_per_rack.at(rack).at(table);
testlog.info("Shard overcommit: {} best: {}", shard_overcommit, best_shard_overcommit);
auto node_imbalance = node_load_minmax.max() - node_load_minmax.min();
auto node_overcommit = node_load_minmax.max() / ideal_load;
testlog.info("Node imbalance in min={}, max={}, spread={}, ideal={}, overcommit={}",
node_load_minmax.min(), node_load_minmax.max(), node_imbalance, ideal_load, node_overcommit);
shard_overcommit_minmax.update(shard_overcommit);
node_overcommit_minmax.update(node_overcommit);
res.tables[table_index++] = {
.shard_overcommit = shard_overcommit_minmax.max(),
.best_shard_overcommit = best_shard_overcommit,
.node_overcommit = node_overcommit_minmax.max(),
};
}
for (int i = 0; i < nr_tables; i++) {
auto t = res.tables[i];
global_res.worst.tables[i].shard_overcommit = std::max(global_res.worst.tables[i].shard_overcommit, t.shard_overcommit);
global_res.worst.tables[i].node_overcommit = std::max(global_res.worst.tables[i].node_overcommit, t.node_overcommit);
}
testlog.info("Overcommit: {}", res);
return res;
};
testlog.debug("tablet metadata: {}", stm.get()->tablets());
e.get_tablet_allocator().local().set_use_table_aware_balancing(tablet_aware);
check_balance();
rebalance_tablets(e, stats);
global_res.init = global_res.worst = check_balance();
for (int i = 0; i < cycles; i++) {
const auto [id, dc_rack] = hosts[0];
bootstrap(dc_rack);
check_balance();
decommission(id);
global_res.last = check_balance();
}
}, cfg);
co_return global_res;
}
void test_parallel_scaleout(const bpo::variables_map& opts) {
const shard_id shard_count = opts["shards"].as<int>();
const int nr_tables = opts["tables"].as<int>();
const int tablets_per_table = opts["tablets_per_table"].as<int>();
const int nr_racks = opts["racks"].as<int>();
const int initial_nodes = nr_racks * opts["nodes-per-rack"].as<int>();
const int extra_nodes = nr_racks * opts["extra-nodes-per-rack"].as<int>();
const double tablet_size_deviation_factor = opts["tablet-size-deviation-factor"].as<double>();
auto cfg = tablet_cql_test_config();
cfg.db_config->rf_rack_valid_keyspaces(true);
results global_res;
do_with_cql_env_thread([&] (auto& e) {
topology_builder topo(e);
locator::load_stats stats;
std::vector<endpoint_dc_rack> racks;
racks.push_back(topo.rack());
for (int i = 1; i < nr_racks; ++i) {
racks.push_back(topo.start_new_rack());
}
auto add_host = [&] (endpoint_dc_rack rack) {
auto host = topo.add_node(service::node_state::normal, shard_count, rack);
const uint64_t capacity = default_target_tablet_size * shard_count * 100;
stats.capacity[host] = capacity;
stats.tablet_stats[host].effective_capacity = capacity;
testlog.info("Added new node: {}", host);
};
auto add_hosts = [&] (int n) {
for (int i = 0; i < n; ++i) {
add_host(racks[i % racks.size()]);
}
};
add_hosts(initial_nodes);
testlog.info("Creating schema");
auto ks1 = add_keyspace(e, {{topo.dc(), nr_racks}}, tablets_per_table);
seastar::parallel_for_each(std::views::iota(0, nr_tables), [&] (int) -> future<> {
return add_table(e, ks1).discard_result();
}).get();
generate_tablet_sizes(tablet_size_deviation_factor, stats, e.shared_token_metadata().local());
testlog.info("Initial rebalancing");
rebalance_tablets(e, stats);
testlog.info("Scaleout");
add_hosts(extra_nodes);
global_res.stats += rebalance_tablets(e, stats);
}, cfg).get();
}
future<> run_simulation(const params& p, const sstring& name = "") {
testlog.info("[run {}] params: {}", name, p);
auto total_tablet_count = p.tablets1.value_or(0) * p.rf1 + p.tablets2.value_or(0) * p.rf2;
testlog.info("[run {}] tablet count: {}", name, total_tablet_count);
testlog.info("[run {}] tablet count / shard: {:.3f}", name, double(total_tablet_count) / (p.nodes * p.shards));
auto res = co_await test_load_balancing_with_many_tables(p, true);
testlog.info("[run {}] Overcommit : init : {}", name, res.init);
testlog.info("[run {}] Overcommit : worst: {}", name, res.worst);
testlog.info("[run {}] Overcommit : last : {}", name, res.last);
testlog.info("[run {}] Overcommit : time : {:.3f} [s], max={:.3f} [s], count={}", name,
res.stats.elapsed_time.count(), res.stats.max_rebalance_time.count(), res.stats.rebalance_count);
if (res.stats.elapsed_time > seconds_double(1)) {
testlog.warn("[run {}] Scheduling took longer than 1s!", name);
}
auto old_res = co_await test_load_balancing_with_many_tables(p, false);
testlog.info("[run {}] Overcommit (old) : init : {}", name, old_res.init);
testlog.info("[run {}] Overcommit (old) : worst: {}", name, old_res.worst);
testlog.info("[run {}] Overcommit (old) : last : {}", name, old_res.last);
testlog.info("[run {}] Overcommit : time : {:.3f} [s], max={:.3f} [s], count={}", name,
old_res.stats.elapsed_time.count(), old_res.stats.max_rebalance_time.count(), old_res.stats.rebalance_count);
for (int i = 0; i < nr_tables; ++i) {
if (res.worst.tables[i].shard_overcommit > old_res.worst.tables[i].shard_overcommit) {
testlog.warn("[run {}] table{} shard overcommit worse!", name, i + 1);
}
auto overcommit = res.worst.tables[i].shard_overcommit;
if (overcommit > 1.2) {
testlog.warn("[run {}] table{} shard overcommit {:.4f} > 1.2!", name, i + 1, overcommit);
}
}
}
future<> run_simulations(const boost::program_options::variables_map& app_cfg) {
for (auto i = 0; i < app_cfg["runs"].as<int>(); i++) {
constexpr int MIN_RF = 1;
constexpr int MAX_RF = 3;
auto shards = 1 << tests::random::get_int(0, 8);
auto rf1 = tests::random::get_int(MIN_RF, MAX_RF);
// FIXME: Once we allow for RF <= #racks (and not just RF == #racks), we can randomize this RF too.
// For now, the values must be equal.
auto rf2 = rf1;
auto scale1 = 1 << tests::random::get_int(0, 5);
auto scale2 = 1 << tests::random::get_int(0, 5);
auto nodes = tests::random::get_int(rf1 + rf2, 2 * MAX_RF);
// results in a deviation factor of 0.0 - 2.0
auto tablet_size_deviation_factor = tests::random::get_int(0, 200) / 100.0;
params p {
.iterations = app_cfg["iterations"].as<int>(),
.nodes = nodes,
.tablets1 = std::bit_ceil<size_t>(div_ceil(shards * nodes, rf1) * scale1),
.tablets2 = std::bit_ceil<size_t>(div_ceil(shards * nodes, rf2) * scale2),
.rf1 = rf1,
.rf2 = rf2,
.shards = shards,
.scale1 = scale1,
.scale2 = scale2,
.tablet_size_deviation_factor = tablet_size_deviation_factor
};
auto name = format("#{}", i);
co_await run_simulation(p, name);
}
}
namespace perf {
void run_add_dec(const bpo::variables_map& opts) {
if (opts.contains("runs")) {
run_simulations(opts).get();
} else {
params p {
.iterations = opts["iterations"].as<int>(),
.nodes = opts["nodes"].as<int>(),
.tablets1 = opts["tablets1"].as<int>(),
.tablets2 = opts["tablets2"].as<int>(),
.rf1 = opts["rf1"].as<int>(),
.rf2 = opts["rf2"].as<int>(),
.shards = opts["shards"].as<int>(),
.tablet_size_deviation_factor = opts["tablet-size-deviation-factor"].as<double>(),
};
run_simulation(p).get();
}
}
using operation_func = std::function<void(const bpo::variables_map&)>;
const std::vector<operation_option> global_options {};
const std::vector<operation_option> global_positional_options{};
const std::map<operation, operation_func> operations_with_func{
{
{{"rolling-add-dec",
"Sequence of bootstraps and decommissions with two tables",
"",
{
typed_option<int>("runs", "Number of simulation runs."),
typed_option<int>("iterations", 8, "Number of topology-changing cycles in each run."),
typed_option<int>("tablets1", 512, "Number of tablets for the first table."),
typed_option<int>("tablets2", 128, "Number of tablets for the second table."),
typed_option<int>("rf1", 1, "Replication factor for the first table."),
typed_option<int>("rf2", 1, "Replication factor for the second table."),
typed_option<int>("nodes", 3, "Number of nodes in the cluster."),
typed_option<int>("shards", 30, "Number of shards per node."),
typed_option<double>("tablet-size-deviation-factor", 0.5, "Deviation factor for the tablet size random generator.")
}
}, &run_add_dec},
{{"parallel-scaleout",
"Simulates a single scale-out involving simultaneous addition of multiple nodes per rack",
"",
{
typed_option<int>("tablets_per_table", 256, "Number of tablets per table."),
typed_option<int>("tables", 70, "Table count."),
typed_option<int>("nodes-per-rack", 5, "Number of initial nodes per rack."),
typed_option<int>("extra-nodes-per-rack", 3, "Number of nodes to add per rack."),
typed_option<int>("racks", 2, "Number of racks."),
typed_option<int>("shards", 88, "Number of shards per node."),
typed_option<double>("tablet-size-deviation-factor", 0.5, "Deviation factor for the tablet size random generator.")
}
}, &test_parallel_scaleout},
}
};
int scylla_tablet_load_balancing_main(int argc, char** argv) {
const auto operations = operations_with_func | std::views::keys | std::ranges::to<std::vector>();
tool_app_template::config app_cfg{
.name = "perf-load-balancing",
.description = "Tests tablet load balancer in various scenarios",
.logger_name = testlog.name(),
.lsa_segment_pool_backend_size_mb = 100,
.operations = std::move(operations),
.global_options = &global_options,
.global_positional_options = &global_positional_options,
.db_cfg_ext = db_config_and_extensions()
};
tool_app_template app(std::move(app_cfg));
return app.run_async(argc, argv, [] (const operation& operation, const bpo::variables_map& app_config) {
auto stop_test = defer([] {
aborted.request_abort();
});
try {
operations_with_func.at(operation)(app_config);
return 0;
} catch (seastar::abort_requested_exception&) {
// Ignore
}
return 1;
});
}
} // namespace perf