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The blocked task detector introduced in
113ed9e963 was seeing
the initialization phase of perf_ssttable as a blocked
task.
Tranform this part of the code in a futurized loop
to make to blocked task detector happy.
Signed-off-by: Benoît Canet <benoit@scylladb.com>
Message-Id: <20170413132506.17806-1-benoit@scylladb.com>
210 lines
7.7 KiB
C++
210 lines
7.7 KiB
C++
/*
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* Copyright (C) 2015 ScyllaDB
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*/
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/*
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* This file is part of Scylla.
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*
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* Scylla is free software: you can redistribute it and/or modify
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* it under the terms of the GNU Affero General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Scylla is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Scylla. If not, see <http://www.gnu.org/licenses/>.
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*/
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#pragma once
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#include "../sstable_test.hh"
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#include "sstables/sstables.hh"
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#include "mutation_reader.hh"
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#include <boost/accumulators/accumulators.hpp>
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#include <boost/accumulators/statistics.hpp>
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#include <boost/range/irange.hpp>
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using namespace sstables;
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class test_env {
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public:
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struct conf {
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unsigned partitions;
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unsigned key_size;
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unsigned num_columns;
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unsigned column_size;
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size_t buffer_size;
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sstring dir;
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};
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private:
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sstring dir() {
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return _cfg.dir + "/" + to_sstring(engine().cpu_id());
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}
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sstring random_string(unsigned size) {
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sstring str(sstring::initialized_later{}, size_t(size));
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for (auto& b: str) {
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b = _distribution(_generator);
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}
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return str;
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}
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sstring random_key() {
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return random_string(_cfg.key_size);
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}
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sstring random_column() {
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return random_string(_cfg.column_size);
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}
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conf _cfg;
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schema_ptr s;
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std::default_random_engine _generator;
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std::uniform_int_distribution<char> _distribution;
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lw_shared_ptr<memtable> _mt;
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std::vector<lw_shared_ptr<sstable>> _sst;
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schema_ptr create_schema() {
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std::vector<schema::column> columns;
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for (unsigned i = 0; i < _cfg.num_columns; ++i) {
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columns.push_back(schema::column{ to_bytes(sprint("column%04d", i)), utf8_type });
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}
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schema_builder builder(make_lw_shared(schema(generate_legacy_id("ks", "perf-test"), "ks", "perf-test",
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// partition key
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{{"name", utf8_type}},
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// clustering key
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{},
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// regular columns
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{ columns },
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// static columns
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{},
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// regular column name type
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utf8_type,
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// comment
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"Perf tests"
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)));
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return builder.build(schema_builder::compact_storage::no);
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}
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public:
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test_env(conf cfg) : _cfg(std::move(cfg))
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, s(create_schema())
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, _distribution('@', '~')
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, _mt(make_lw_shared<memtable>(s))
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{}
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future<> stop() { return make_ready_future<>(); }
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future<> fill_memtable() {
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auto idx = boost::irange(0, int(_cfg.partitions));
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return do_for_each(idx.begin(), idx.end(), [this] (auto iteration) {
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auto key = partition_key::from_deeply_exploded(*s, { this->random_key() });
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auto mut = mutation(key, this->s);
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for (auto& cdef: this->s->regular_columns()) {
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mut.set_clustered_cell(clustering_key::make_empty(), cdef, atomic_cell::make_live(0, utf8_type->decompose(this->random_column())));
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}
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this->_mt->apply(std::move(mut));
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return make_ready_future<>();
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});
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}
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future<> load_sstables(unsigned iterations) {
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_sst.push_back(make_lw_shared<sstable>(s, this->dir(), 0, sstable::version_types::ka, sstable::format_types::big));
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return _sst.back()->load();
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}
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using clk = std::chrono::steady_clock;
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static auto now() {
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return clk::now();
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}
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// Mappers below
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future<double> flush_memtable(int idx) {
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auto start = test_env::now();
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size_t partitions = _mt->partition_count();
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return test_setup::create_empty_test_dir(dir()).then([this, idx] {
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auto sst = sstables::test::make_test_sstable(_cfg.buffer_size, s, dir(), idx, sstable::version_types::ka, sstable::format_types::big);
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return sst->write_components(*_mt).then([sst] {});
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}).then([start, partitions] {
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auto end = test_env::now();
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auto duration = std::chrono::duration<double>(end - start).count();
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return partitions / duration;
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});
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}
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future<double> read_all_indexes(int idx) {
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return do_with(test(_sst[0]), [] (auto& sst) {
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auto start = test_env::now();
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auto total = make_lw_shared<size_t>(0);
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auto& summary = sst.get_summary();
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auto idx = boost::irange(0, int(summary.header.size));
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return do_for_each(idx.begin(), idx.end(), [&sst, total] (uint64_t entry) {
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return sst.read_indexes(entry).then([total] (auto il) {
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*total += il.size();
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});
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}).then([total, start] {
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auto end = test_env::now();
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auto duration = std::chrono::duration<double>(end - start).count();
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return *total / duration;
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});
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});
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}
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future<double> read_sequential_partitions(int idx) {
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return do_with(_sst[0]->read_rows(s), [this] (sstables::mutation_reader& r) {
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auto start = test_env::now();
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auto total = make_lw_shared<size_t>(0);
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auto done = make_lw_shared<bool>(false);
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return do_until([done] { return *done; }, [this, done, total, &r] {
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return r.read().then([] (auto sm) {
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return mutation_from_streamed_mutation(std::move(sm));
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}).then([this, done, total] (mutation_opt m) {
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if (!m) {
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*done = true;
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} else {
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auto row = m->partition().find_row(*s, clustering_key::make_empty());
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if (!row || row->size() != _cfg.num_columns) {
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throw std::invalid_argument("Invalid sstable found. Maybe you ran write mode with different num_columns settings?");
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} else {
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(*total)++;
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}
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}
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});
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}).then([total, start] {
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auto end = test_env::now();
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auto duration = std::chrono::duration<double>(end - start).count();
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return *total / duration;
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});
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});
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}
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};
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// The function func should carry on with the test, and return the number of partitions processed.
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// time_runs will then map reduce it, and return the aggregate partitions / sec for the whole system.
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template <typename Func>
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future<> time_runs(unsigned iterations, unsigned parallelism, distributed<test_env>& dt, Func func) {
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using namespace boost::accumulators;
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auto acc = make_lw_shared<accumulator_set<double, features<tag::mean, tag::error_of<tag::mean>>>>();
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auto idx = boost::irange(0, int(iterations));
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return do_for_each(idx.begin(), idx.end(), [parallelism, acc, &dt, func] (auto iter) {
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auto idx = boost::irange(0, int(parallelism));
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return parallel_for_each(idx.begin(), idx.end(), [&dt, func, acc] (auto idx) {
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return dt.map_reduce(adder<double>(), func, std::move(idx)).then([acc] (double result) {
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auto& a = *acc;
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a(result);
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return make_ready_future<>();
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});
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});
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}).then([acc, iterations, parallelism] {
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std::cout << sprint("%.2f", mean(*acc)) << " +- " << sprint("%.2f", error_of<tag::mean>(*acc)) << " partitions / sec (" << iterations << " runs, " << parallelism << " concurrent ops)\n";
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});
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}
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