clickhouse troubleshooting Archives | Page 4 of 5

ClickHouse Caches: Configuring Buffer Cache for High Performance

Introduction: ClickHouse Buffer Cache The ClickHouse Buffer Cache works by caching frequently accessed data in memory. This cache reduces disk I/O operations and speeds up query performance. The buffer cache is organized as a pool […]

Improving Fragmented ClickHouse Database Performance

How to Troubleshoot Performance of Fragmented ClickHouse Databases?

Shiv Iyer

Introduction A fragmented ClickHouse database can impact performance in several ways: Increased disk I/O: When a database is fragmented, the data is stored in multiple parts across the disk, so it takes more time […]

How to Use Indexes in ClickHouse - A Practical Guide

Practical Guide to Using Indexes in ClickHouse

Shiv Iyer

Introduction Indexes in ClickHouse are implemented as a separate data structure that is stored on disk alongside the table data. The index data structure is used to quickly locate the specific data rows that match […]

Runbook to Identify & Monitor Corrupted Indexes

Troubleshooting Corrupted Indexes in ClickHouse

Shiv Iyer

Introduction To troubleshoot index corruption in ClickHouse, you can follow these steps: Check the error logs: Look for any error messages related to index corruption in the ClickHouse logs. This can give you a clue […]

Troubleshooting Disk I/O Performance in ClickHouse

Shiv Iyer

Introduction Disk I/O performance is an absolutely critical element of high performance of ClickHouse servers & systems. Troubleshooting disk I/O performance upon observation of any anomalies is helpful in sustaining performance of your system. Runbook […]

Runbook for Troubleshooting ClickHouse Replication

Shiv Iyer

Introduction Replication is a critical part of horizontally scaling ClickHouse to meet growing user traffic and data size. Issues in replication are critical to resolve to maintain data integrity and ensure system scalability. In this […]

Runbook for Troubleshooting Excessive Logical IOs in ClickHouse

Monitoring and Troubleshooting Excessive Logical I/Os in ClickHouse

Shiv Iyer

Introduction Excessive logical I/Os in ClickHouse is a key reason for slow, sub-optimal, and expensive query performance and compromised scalability. In this detailed guide, we share tips & tricks to monitor and troubleshoot logical I/Os […]

How to implement Real-time Stream Processing in ClickHouse with Kafka

Shiv Iyer

Introduction Kafka is the ideal open source platform to implement real-time stream processing in ClickHouse for real-time analytics. At ChistaDATA Inc., we have extensive experience in working with Kafka in the context of ClickHouse for […]

Real-Time Performance Monitoring for ClickHouse Cluster Using Python Script

Shiv Iyer

Introduction There are several ways to monitor the performance of a ClickHouse cluster: Using built-in system tables: ClickHouse has several built-in system tables, such as system.metrics, system.metrics_events, and system.query_log, that provide detailed information about the […]

How to Recover ClickHouse After ZooKeeper Metadata is Corrupted?

ClickHouse Troubleshooting: How to Restore/Recover ClickHouse after ZooKeeper Metadata is Corrupted/Lost

ChistaDATA Inc.

Introduction When you are building a highly available ClickHouse Infrastrstucture for scale and performance we use ZooKeeper for ClickHouse Replication Management and Operations with ReplicatedMergeTree table engine. You can expect ZooKeeper to face data loss […]

* 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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