ClickHouse DBA Script Archives | Page 2 of 10

ClickHouse Troubleshooting - Profiling Queries for Performance

ClickHouse Query Profiling for Performance Monitoring

Introduction Creating a Python CLI (Command-Line Interface) application for custom profiling of ClickHouse Server queries involves several components. The application will allow users to input queries via the command line, execute them on a ClickHouse […]

ClickHouse JOIN: Understanding the Internal Mechanics of JOIN operations

Shiv Iyer

Introduction ClickHouse JOIN operations are executed differently compared to traditional SQL databases, primarily due to its columnar storage architecture and distributed data processing capabilities. Understanding how JOINs work internally in ClickHouse involves looking at the […]

ClickHouse Performance: Optimizing HASH GROUP BY and ORDER BY Queries

Shiv Iyer

Introduction In the realm of database management, particularly with ClickHouse, query optimization is a critical aspect of ensuring efficient data processing and retrieval. Among the various queries, HASH GROUP BY and ORDER BY stand out […]

ClickHouse Troubleshooting: Understanding Estimated I/O and CPU Costs

Shiv Iyer

Introduction In ClickHouse, like many database systems, performance troubleshooting and query optimization often involve understanding various metrics, including estimated I/O (Input/Output) costs and estimated CPU (Central Processing Unit) costs. These metrics are crucial for identifying […]

ClickHouse Performance: Estimated & Actual Row Counts in Execution Plans

Shiv Iyer

Introduction Understanding the difference between the estimated and actual number of rows in ClickHouse execution plans is crucial for query optimization and performance tuning. Overview of Estimated & Actual Row Counts in ClickHouse Here’s an […]

ClickHouse Security: Implementing Data Masking for Regulatory Compliance

Shiv Iyer

Masking data in ClickHouse for data security and compliance involves altering the representation of the data to protect sensitive information. Data masking is essential in scenarios where you need to share data without exposing sensitive details, such as in development environments or with third-party analysts.

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ClickHouse Troubleshooting: Not Able to Connect to ClickHouse

Comprehensive Guide for ClickHouse Horizontal Scaling and Capacity Planning

Shiv Iyer

Calculating your company’s required real-time analytics capacity on ClickHouse involves several steps and considerations. It’s important to assess current and projected data volumes, query complexity, and the expected concurrency of queries.

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ClickHouse Horizontal Scaling: Optimal Read-Write Split Configuration and Execution

Shiv Iyer

Scaling ClickHouse horizontally while optimizing the split between read and write operations is a multi-step process that involves setting up a cluster with sharded and replicated tables.

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ClickHouse Search: Case-sensitive Searches with UPPER & LOWER Functions

Shiv Iyer

Implementing a case-sensitive search in ClickHouse, a column-oriented database management system, can be achieved by using the UPPER or LOWER functions. These functions convert text data to either uppercase or lowercase, respectively, allowing for a consistent comparison.

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ClickHouse Server Configuration for High-Volume Data Ingestion

Shiv Iyer

Optimizing ClickHouse for high-velocity and high-volume data loading involves several server configuration and tuning techniques.

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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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