Shiv Iyer, Author at ChistaDATA Inc.

ClickHouse Troubleshooting: Understanding Estimated I/O and CPU Costs

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 ClickHouse Execution Plans

ClickHouse Execution Plans: Estimated vs Actual Row Counts

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: ClickHouse Data Masking

ClickHouse 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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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 Case-Sensitive Search 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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Overview of ClickHouse Architecture and Query Performance Techniques

Shiv Iyer

Introduction: ClickHouse Architecture Understanding the internals of ClickHouse reveals why it’s renowned for its exceptional performance, especially in the realm of online analytical processing (OLAP). ClickHouse is a column-oriented database management system (DBMS) that employs […]

ClickHouse Performance: Indexing and SQL Engineering for Cost-Efficiency

Shiv Iyer

The landscape of cloud-based database application development has been rapidly evolving, and with it, the importance of optimal SQL engineering and efficient indexing has become more pronounced than ever.

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ClickHouse High-Volume Data Ingestion: Server Configuration Guide

Shiv Iyer

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

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ClickHouse Index Granularity: Tuning index_granularity for Performance

Shiv Iyer

Understanding index granularity is crucial for troubleshooting performance issues in ClickHouse, especially when it comes to optimizing how ClickHouse uses indexes for query execution.

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Articles by Shiv Iyer

ClickHouse Troubleshooting: Understanding Estimated I/O and CPU Costs

ClickHouse Execution Plans: Estimated vs Actual Row Counts

ClickHouse Data Masking for Regulatory Compliance

Comprehensive Guide for ClickHouse Horizontal Scaling and Capacity Planning

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

ClickHouse Case-Sensitive Search with UPPER & LOWER Functions

Overview of ClickHouse Architecture and Query Performance Techniques

ClickHouse Performance: Indexing and SQL Engineering for Cost-Efficiency

ClickHouse High-Volume Data Ingestion: Server Configuration Guide

ClickHouse Index Granularity: Tuning index_granularity for Performance