Introduction 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 of memory blocks, […]
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 […]
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 […]
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 […]
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 […]
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 […]
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 […]
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 […]
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 […]
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 […]
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