ChistaDATA
ClickHouse Memory: How to Configure Global Process Area Parameters
Introduction In ClickHouse, the global process area is implemented as a shared-memory segment that is shared between all instances of the ClickHouse server running on the same machine. This shared-memory segment is used to store […]
ClickHouse EXPLAIN: Determine JOIN Order in Query Execution Plan
Introduction In ClickHouse, the join order in an execution plan is determined by the query optimizer, which analyzes the query and generates an optimal plan for executing the query. The optimizer uses statistics about the […]
Using TOP Command to Measure ClickHouse Server Load & Queue Length
Introduction Measuring load and queue length of ClickHouse Server is important for troubleshooting performance bottleneck. The load is a measure of the amount of work that ClickHouse is currently doing or is capable of doing. […]
How to Monitor & Troubleshoot Log Contention in ClickHouse
Introduction Log contention in ClickHouse occurs when multiple write operations compete for the same log file, causing performance issues and potentially leading to data corruption. Here are some steps you can take to troubleshoot and […]
Monitoring Query Latency due to Wait and Latch Events in ClickHouse
Introduction In ClickHouse, you can monitor query latency and waits/latches using the system.query_log and system.metrics tables. Here is an example query that can be used to monitor query latency and wait/latch events: This query selects […]
ClickHouse Troubleshooting: How NULL Values affect Query Performance
Introduction NULL values in ClickHouse can affect performance in several ways. One way is that they can increase the size of data, which can lead to slower query execution times as more data needs to […]
ClickHouse Troubleshooting: How to Identify Blocks Causing Latch Contention
Introduction Latch contention in ClickHouse can have a significant impact on performance. A latch is a synchronization mechanism that allows multiple threads to access a shared resource, such as a data block, in a controlled […]
Streaming ClickHouse Data to Kafka
Introduction ClickHouse has an inbuilt Kafka table engine which is commonly used to read streaming messages from Apache Kafka and store it in ClickHouse. This is one of the important and widely used features of […]
ClickHouse Materialized Views: Using Live Views to Compute Real-time Moving Averages
Introduction ClickHouse Live Views can be used to compute real-time moving averages efficiently. Here’s how: Conclusion By using ClickHouse Live Views and defining the appropriate query, settings, and subscription, you can efficiently compute real-time moving […]