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HomeDBA

DBA

Troubleshooting High CPU Usage in ClickHouse
ClickHouse Security

Securing ClickHouse Data at Rest: A Guide to Implementing Filesystem-Level Encryption

Shiv Iyer
ClickHouse Data at Rest ClickHouse does not directly support Transparent Data Encryption (TDE) in the same way that some other database systems do, such as Oracle or SQL Server, which provide built-in TDE capabilities to […]
Mastering Chained Joins In Clickhouse
ClickHouse Performance

Enhancing Data Processing Workflows with Chained Materialized Views in ClickHouse

Shiv Iyer
Chained Materialized Views Chaining materialized views in ClickHouse is a powerful feature that can significantly enhance data processing workflows by creating layers of data transformation and aggregation. This technique involves creating a series of materialized […]
How NULL Values affect ClickHouse Query Performance
ClickHouse Performance

Optimizing High-Velocity, High-Volume ETL Operations with Data Skipping Indexes in ClickHouse

Shiv Iyer
ClickHouse ETL Optimization Data Skipping Indexes in ClickHouse are an effective optimization tool for enhancing query performance in high-velocity, high-volume ETL operations. These indexes help by allowing the database to skip over blocks of data […]
ClickHouse Performance

Strategic Considerations for Integrating ClickHouse with Row-based Systems: Balancing Performance and Architecture

Shiv Iyer
Introduction: ClickHouse Integration Strategy Switching from a row-based to a column-based database system like ClickHouse involves significant architectural changes and strategic planning. This transition can offer substantial performance benefits, especially for analytics and read-heavy operations, […]
ClickHouse Performance

Effective Strategies for Deleting Old Records in ClickHouse: Methods and Best Practices

Shiv Iyer
Deleting Old Records: Deleting old records in ClickHouse requires careful consideration due to its append-only and columnar nature, which does not inherently support row-level deletions as efficiently as traditional relational databases. ClickHouse is designed for […]
ClickHouse

Enhancing ClickHouse Performance: Strategic Insights on Partitioning, Indexing, and Monitoring

Shiv Iyer
ClickHouse Performance tuning Optimizing ClickHouse performance involves a multi-faceted approach that includes effective partitioning, strategic indexing, and diligent system monitoring. Each of these areas plays a crucial role in enhancing the efficiency and speed of […]
ClickHouse Performance

Optimizing Query Performance: Understanding Criterion Indexability in ClickHouse

Shiv Iyer
Criterion Indexability in ClickHouse Criterion indexability in ClickHouse refers to the database’s ability to utilise indexes for filtering data based on query conditions efficiently. ClickHouse, designed for fast analytical queries over large datasets, employs various […]
ClickHouse

Finding Missing Values in ClickHouse: Efficient Techniques for Data Comparison

Shiv Iyer
Finding Missing Values in ClickHouse Finding missing values in datasets is a common task in data analysis, especially when comparing two lists or tables to identify discrepancies. In ClickHouse, while there’s no built-in EXCEPT or […]
Materialized Column ClickHouse
ClickHouse Performance

Enhancing ClickHouse Query Efficiency: The Power of Materialized Columns in Practice

Shiv Iyer
Introduction Incorporating materialized columns into ClickHouse for managing complex filtering conditions represents a strategic optimization that significantly boosts database performance. This technique revolves around pre-calculating and storing the results of expressions directly within the table, […]
Long integer query optimization in ClickHouse
ClickHouse SQL Engineering

Optimizing Long Integer Queries in ClickHouse: Strategies for High-Speed Data Analysis

Shiv Iyer
Introduction – Long Integer Queries Navigating the terrain of querying long integer data (64-bit integers) in ClickHouse is a journey of optimising performance through strategic choices in data types, leveraging indexing, and fine-tuning query operations. […]

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* Everything changes over time – Our blogs/posts and comments changes over time, That’s how it should be! Whatever we comment from ChistaDATA Inc. Teams (including Shiv Iyer) and other stakeholders or guest bloggers posted here are never permanent, These things worked for us. But, there is no guarantee they will work for you too, When using the recommendations from ChistaDATA or MinervaDB or MinervaSQL or any other online resources / Google,  You must test the advice before applying them to your production systems, and always invest for a robust Database DR solution, Thank you for understanding. 

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