Python Script for Monitoring ClickHouse Disk I/O and Generating Flame Graphs

Generating disk I/O patterns from a ClickHouse server and converting them to a flame graph involves multiple steps. You need to capture the disk I/O activity, process the data, and then visualize it as a flame graph. Here's a Python script outline to demonstrate this process:

Python Script to Generate Disk I/O Patterns for Flame Graphs

1. Install Necessary Packages:

   • pyflamegraph: For generating flame graphs.

   • psutil: For monitoring system statistics like disk I/O.

   • clickhouse-driver: To interact with ClickHouse.

    pip install pyflamegraph psutil clickhouse-driver

1. Python Script:

import time
import psutil
import pyflamegraph
from clickhouse_driver import Client

def monitor_disk_io(duration_sec, interval_sec):
    start_time = time.time()
    io_data = []

    while time.time() - start_time < duration_sec:
        io_counters = psutil.disk_io_counters()
        io_data.append((time.time(), io_counters.read_bytes, io_counters.write_bytes))
        time.sleep(interval_sec)

    return io_data

def generate_flame_graph(io_data, output_file):
    flame_data = ""
    for idx in range(1, len(io_data)):
        timestamp, read_bytes, write_bytes = io_data[idx]
        prev_timestamp, prev_read_bytes, prev_write_bytes = io_data[idx - 1]
        flame_data += f"read {timestamp - prev_timestamp} {read_bytes - prev_read_bytes}\\\\n"
        flame_data += f"write {timestamp - prev_timestamp} {write_bytes - prev_write_bytes}\\\\n"

    with open(output_file, "w") as f:
        f.write(flame_data)

    pyflamegraph.create_flamegraph(input_file=output_file, output_file=f"flame_{output_file}")

def run_clickhouse_query(client, query):
    client.execute(query)

# Configuration
CLICKHOUSE_HOST = 'localhost'
DURATION_SEC = 60 # Total duration for monitoring
INTERVAL_SEC = 1  # Interval between readings
OUTPUT_FILE = 'disk_io_data.txt'
QUERY = 'SELECT * FROM your_table'  # Replace with your ClickHouse query

# Main Execution
client = Client(CLICKHOUSE_HOST)

# Start Disk I/O Monitoring in a separate thread
from threading import Thread
io_thread = Thread(target=monitor_disk_io, args=(DURATION_SEC, INTERVAL_SEC))
io_thread.start()

# Run ClickHouse Query
run_clickhouse_query(client, QUERY)

# Wait for Disk I/O Monitoring to complete
io_thread.join()

# Generate Flame Graph
io_data = monitor_disk_io(DURATION_SEC, INTERVAL_SEC)
generate_flame_graph(io_data, OUTPUT_FILE)

Explanation:

1. Disk I/O Monitoring: The script captures disk I/O statistics using psutil for a specified duration and interval.

2. Flame Graph Generation: The disk I/O data is then converted into a format compatible with pyflamegraph to generate a flame graph.

3. ClickHouse Query Execution: While the disk I/O is being monitored, a ClickHouse query is executed. Replace QUERY with your actual query.

4. Multi-threading: The script uses a separate thread to monitor disk I/O while the main thread executes the ClickHouse query.

5. Output: The script generates a flame graph showing disk read and write patterns during the query execution.

Important Notes:

• Ensure ClickHouse is running and accessible from the script.

• Customize the duration and interval for I/O monitoring as needed.

• The ClickHouse query should be representative of your typical workload for meaningful I/O pattern analysis.

• Install pyflamegraph and its dependencies in your environment. You might need additional setup for graphical rendering.

• This script provides a basic outline. Depending on the complexity of your ClickHouse queries and the specifics of your environment, you may need to adjust the script.