ClickHouse在高并发写入场景下的性能优化实践（CPU利用率飙升）

SELECT * FROM system.metrics WHERE metric LIKE '%Write%' OR metric LIKE '%Insert%';
SELECT * FROM system.events WHERE event LIKE '%Write%' OR event LIKE '%Insert%' ORDER BY value DESC LIMIT 20;

// 简化后的关键代码逻辑
void MergeTreeDataWriter::writeTempPart(...) {
    // 获取表级锁
    auto lock = table->lockForShare();
    
    // 写入数据到临时分区
    // ...
    
    // 刷盘操作
    writer->flush();
    
    // 释放锁
}

<!-- config.xml 配置 -->
<profiles>
    <default>
        <max_insert_block_size>1048576</max_insert_block_size>
        <min_insert_block_size_rows>10000</min_insert_block_size_rows>
        <min_insert_block_size_bytes>10485760</min_insert_block_size_bytes>
    </default>
</profiles>

<merge_tree>
    <max_part_loading_threads>4</max_part_loading_threads>
    <number_of_free_threads_in_pool_to_lower_max_size_of_merge>4</number_of_free_threads_in_pool_to_lower_max_size_of_merge>
</merge_tree>

CREATE TABLE events (
    event_time DateTime,
    user_id UInt64,
    event_type String,
    data String
) ENGINE = MergeTree()
PARTITION BY toHour(event_time)
ORDER BY (event_time, user_id);

# 压测命令
for i in {1..100}; do
    clickhouse-client --query "INSERT INTO events VALUES (now(), $i, 'test', 'data')" &
done