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How to drop an Existing Histogram from a ClickHouse Column?
ClickHouse Internals

How to drop an Existing Histogram from a ClickHouse Column?

Shiv Iyer

Introduction To drop an existing histogram on a ClickHouse column and prevent the Auto Stats gathering job from creating it in the future, you can follow these steps: For example: Identify the column name that […]

ClickHouse EXPLAIN: Display & Analyze Execution Plans
ClickHouse Explain

ClickHouse EXPLAIN: Display & Analyze Execution Plans

Shiv Iyer

Introduction To display and read the execution plans for a SQL statement in ClickHouse, you can follow these steps using real-life data sets: For this example, we’ll use a simple SELECT statement to retrieve data […]

How to Identify Overlapping Date Ranges in ClickHouse
ClickHouse SQL Engineering

ClickHouse SQL Engineering: How to Identify Overlapping Date Ranges

Shiv Iyer

To identify overlapping date ranges in ClickHouse, you can use SQL queries that compare the start and end dates of each range to determine if there are any overlaps. Example to identify Overlapping Date Ranges […]

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ClickHouse Explain

Comprehensive Guide to ClickHouse EXPLAIN

ChistaDATA Inc.

Introduction Have you ever pondered over how database engines handle queries and optimize their execution? Have you ever wondered which queries are responsible for slowing down your database? Are you curious to know who is […]

Implementing Parallel Replicas with Dynamic Shards
ChistaDATA

ClickHouse Horizontal Scaling: Implementing Parallel Replicas with Dynamic Shards

ChistaDATA Inc.

Introduction ClickHouse is known for its exceptional performance, scalability, and flexibility. With its ability to handle massive amounts of data and process queries in real-time, ClickHouse is becoming increasingly popular among data analysts, developers, and […]

Using GROUPBY for Groupings, Rolllups and Cubes in ClickHouse
ClickHouse

Using GROUPBY for Groupings, Rollups and Cubes in ClickHouse

Shiv Iyer

Introduction Grouping, rollup, and cube are SQL query operations that allow for grouping and aggregation of data based on multiple dimensions or attributes. In ClickHouse, these operations are implemented using the GROUP BY clause, which […]

Comprehensive Guide to ChistaDATA's ClickHouse Performance Audit
ClickHouse Performance

Comprehensive Guide to ChistaDATA’s ClickHouse Performance Audit

ChistaDATA Inc.

Introduction ClickHouse is a powerful open source relational database management system that offers high performance, scalability, reliability and data security. As ClickHouse is widely used in various industries, it is important to ensure that it […]

Derived Tables for Query Performance in ClickHouse
ClickHouse Performance

Derived Tables for Query Performance in ClickHouse

Shiv Iyer

Introduction Derived tables are tables that are created on-the-fly as a result of a query. They are temporary tables that exist only for the duration of the query, and are not stored in the database. […]

ClickHouse Permutation by Recursion and Cross Join
ClickHouse Performance

ClickHouse Permutation by Recursion and Cross Join

Shiv Iyer

Permutation is the process of arranging a set of elements in all possible orders. ClickHouse supports two methods for computing permutations: recursion and cross join. Here’s how each method works, along with real-life data examples […]

Setup ClickHouse Cluster Replication with Zookeeper
ClickHouse Replication

Setup ClickHouse Cluster Replication with Zookeeper

ChistaDATA Inc.

Introduction ClickHouse is a powerful and versatile open-source columnar database management system known for its fast performance and high scalability. If you’re looking to build your own ClickHouse cluster, there are several options available, such […]

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ChistaDATA is committed to open source software and building high performance ColumnStores

In the spirit of freedom, independence and innovation. ChistaDATA Corporation is not affiliated with ClickHouse Corporation 

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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. 

Recent Posts from ChistaDATA

  • Mastering Nested JOINs in ClickHouse: A Complete Guide to Embedding JOINs within JOINs
  • Understanding the OpenTelemetry Collector: A Comprehensive Guide to Modern Telemetry Management
  • Building a Medallion Architecture with ClickHouse: A Complete Guide
  • Mastering Custom Partitioning Keys in ClickHouse: A Complete Guide
  • Why is ClickHouse So Fast? The Architecture Behind Lightning-Speed Analytics

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Contents

×
  • Introduction
  • Environment
  • Broad Level Action
  • Set hostnames for all servers
  • Install and Configure Zookeeper
  • Verify Zookeeper Installation and Connections
  • Install and Configure Clickhouse nodes.
  • Configure Zookeeper for clickhouse1 and clickhouse2
  • Macro Settings for clickhouse1 and clickhouse2 Servers
  • Define Cluster for clickhouse1 and clickhouse2 Servers.
  • Open the remote connection
  • Verify Clickhouse Cluster
  • Create a sample Database and Replicated table for Cluster
  • Conclusion
→ Index