ClickHouse is a powerful open source relational database management system that offers high performance, scalability, reliability and data security. As ClickHouse is widely used in various industries, it is important to ensure that it is performing optimally and meeting the needs of the business. To achieve this, ChistaDATA offers an Ultra-Low-Level Performance Audit service for ClickHouse, which provides a detailed analysis of the database’s performance, scalability, reliability and data security.
The ChistaDATA Ultra-Low-Level Performance Audit service includes a comprehensive review of the ClickHouse database system, including server configuration, hardware, operating system, database schema, queries and indexes. The audit is performed by experienced ClickHouse performance engineers who use advanced tools and techniques to identify performance issues, scalability bottlenecks, reliability problems and data security risks.
The following white paper outlines the methodology, tools and techniques used by ChistaDATA to perform an ultra-low level performance audit for ClickHouse.
The ultra-low level performance audit for ClickHouse includes the following steps
Gather information: The first step is to gather information about the ClickHouse database system, including server configuration, hardware, operating system, database schema, queries and indexes. This information is gathered by interviewing the database administrators and developers, and by reviewing the system tables, ClickHouse query profiler and logs. Also ChistaDATA Inception System tool will provide intelligent suggestions to optimise performance and improve efficiency on ChistaDATA DBaaS environment soon.
Performance testing: ClickHouse provides various performance metrics that can be monitored and used to track the resource utilisation and performance of the database. These metrics include CPU usage, memory usage, disk IO, network IO and query throughput. The metrics can be collected and visualised using monitoring tools such as ChistaDATA Centralised Performance Monitoring tool, Grafana, Prometheus or Zabbix. Also the ChistaDATA Benchmarking tool to simulate a realistic workload on the database system and measure its response time, throughput and resource utilisation.
Query analysis: Query analysis involves examining the SQL queries executed by the database system and identifying queries that are slow, inefficient or causing performance problems. This is done using tools such as the ChistaDATA Anansi query profiler or system tables to analyse query performance metrics and generate query execution reports.
Compression analysis: ClickHouse has built-in column compression algorithms such as LZ4, ZSTD and Gzip that can be used to reduce storage space and improve query performance. By analysing the compression settings, you can identify the most effective compression algorithm for each column and optimise the storage engine accordingly.
Database schema analysis: Database schema analysis involves reviewing the database schema used by the database system and identifying issues related to normalisation, data types, constraints and data consistency. This is done using and schema dump and system tables such as the system.columns table to analyse the database schema and generate schema analysis reports.
Storage engine analysis: ClickHouse supports several storage engines including MergeTree, CollapsingMergeTree and Distributed. Each storage engine has its own strengths and weaknesses, and choosing the right storage engine can have a significant impact on query performance and resource utilisation.
Disk usage analysis: ClickHouse provides several system tables such as system.parts, system.disks and system.volumes that can be queried to retrieve information about disk usage, data distribution and disk space availability. By analysing disk usage, you can identify any disk related problems such as disk fragmentation, unbalanced data distribution or lack of disk space.
Security analysis: Security analysis involves reviewing the data security measures used by the database system and identifying vulnerabilities or risks that could lead to data breaches or unauthorised access. ClickHouse logs all incoming requests and their results in the access log. By analysing the access log, you can identify suspicious activity such as repeated failed login attempts, unusual query patterns or unauthorised access attempts.
Recommendations: Based on the analysis and findings, ChistaDATA provides recommendations for optimising the database system to improve performance, scalability, reliability and data security. These recommendations include tuning the server configuration, optimising queries and indexes, restructuring the database schema, providing a more appropriate storage engine and improving security measures.
This diagram shows a rough outline of the Inception System.
Tools and Techniques
ClickHouse’s Ultra-Low-Level Performance Audit involves the use of various tools and techniques to gather information, analyse performance and generate reports. These include
Performance testing tools: Performance testing tools include Apache JMeter, Locust or Gatling, which simulate a realistic workload on the database system and measure its response time, throughput and resource utilisation. Also ChistaDATA benchmarking tool to simulate a realistic workload on the database system and measure its response time, throughput and resource usage.
Query analysis tools: Query analysis tool include ClickHouse query profiler, ChistaDATA Anansi query profiler and system tables such as system.metrics, system.query_log and system.query_thread_log which analyse query performance metrics and generate reports on top query executions.
Compression analysis tools: Compression analysis tools include various tables such as column compression analysis, block compression analysis, dictionary analysis, compression benchmarks and compression settings analysis. Provides appropriate min_compress_block_size, max_compress_block_size and max_parts_to_modify_codec which can be used to optimise compression settings.
Database schema analysis tools: Database schema analysis tables include system.columns, system.tables, system.parts and schema dump, which analyse the database schema and generate schema analysis reports.
Storage engine analysis tools: Analyse the MergeTree family to determine the most appropriate table engine for your use case, optimise table parameters and improve query performance. You can also analyse the distributed engine to identify any data replication problems, network bottlenecks or data consistency issues and optimise the cluster configuration accordingly.
Disk usage analysis tools: Database disk analysis tables include system.parts, system.disks, and system.volumes, which analyse database disk usage, data distribution, and disk space availability.
Security analysis tools: The security analysis paths include access management, audit logging, encryption, network security and compliance management, which analyse the database security settings and generate security analysis reports.
Profiling tools: The profiling tools include query profiler, which collect low-level performance data at the kernel and hardware level to identify performance bottlenecks and resource utilization issues.
Monitoring tools: Monitoring tools include ChistaDATA Centralised Performance Monitoring, Grafana, Zabbix and Prometheus, which provide real-time monitoring and alerting for database system performance and availability. There are also some system tables that help with monitoring such as query_log, query_thread_log, query_profiler_real_time_period_ns, system_query_log, system_trace_log, system.metrics tables, memory_tracker, memory_usage, memory_stat, query_trace and trace_log.
Benchmarking tools: Benchmarking tools include the ChistaDATA benchmarking, which provides industry standard benchmarks for measuring the performance and scalability of the database system.
In addition to these tools, ChistaDATA also uses advanced techniques such as query optimisation, index tuning, database normalisation and security hardening to optimise the performance, scalability, reliability and data security of the database system.
The Ultra-Low-Level Performance Audit for ClickHouse includes the following deliverables
Performance report: This report provides a comprehensive analysis of the performance of the database system, including response time, throughput and resource utilisation metrics.
Query report: This report provides a detailed analysis of the SQL queries executed by the database system, including the slow queries, inefficient queries and queries causing performance problems.
Schema report: This report provides a detailed analysis of the database schema used by the database system, including issues related to normalisation, data types, constraints and data consistency.
Engine report: This report provides a detailed analysis of the database table engines used by the database system, including getting an overview of the storage engines used by all the tables in your database and identifying any tables that use a different or less efficient storage engine.
Security report: This report provides a detailed analysis of the data security measures used by the database system, including vulnerabilities or risks that could lead to data breaches or unauthorised access.
Recommendations report: This report provides recommendations for optimising the database system to improve its performance, scalability, reliability and data security.
The ClickHouse Ultra Low-Level Performance Audit provided by ChistaDATA is a comprehensive and detailed analysis of the performance, scalability, reliability and data security of the database system. Using advanced tools and techniques, ChistaDATA can identify potential performance problems, scalability bottlenecks, reliability issues and data security risks, and provide recommendations for optimising the database system. This audit is essential for organisations that rely on ClickHouse for their critical applications and want to ensure that it is performing optimally and meeting the needs of the business. ChistaDATA will provide all these solutions considering DBaaS environment all the time. Stay tuned!