Series: ClickHouse on Kubernetes

1
ReplicatedReplacingMergeTree

Now you have a large single node cluster with a ReplacingMergeTree table that can deduplicate itself. This time, you need more replicated nodes to serve more data users or improve the high availability.

2
ReplacingMergeTree

My favorite ClickHouse table engine is `ReplacingMergeTree`. The main reason is that it is similar to `MergeTree` but can automatically deduplicate based on columns in the `ORDER BY` clause, which is very useful.

3
MergeTree

After starting this series ClickHouse on Kubernetes, you can now configure your first single-node ClickHouse server. Let's dive into creating your first table and understanding the basic concepts behind the ClickHouse engine, its data storage, and some cool features

4
Monitoring ClickHouse on Kubernetes

Now that you have your first ClickHouse instance on Kubernetes and are starting to use it, you need to monitoring and observing what happens on it is an important task to achieve stability.

5
ClickHouse SELECT Advances

Dynamic column selection (also known as a `COLUMNS` expression) allows you to match some columns in a result with a re2 regular expression.

6
ClickHouse on Kubernetes

ClickHouse has been both exciting and incredibly challenging based on my experience migrating and scaling from Iceberg to ClickHouse, zero to a large cluster of trillions of rows. I have had to deal with many of use cases and resolve issues. I have been trying to take notes every day for myself, although it takes time to publish them as a series of blog posts. I hope I can do so on this ClickHouse on Kubernetes series.

Series: Rust Data Engineering

1
Fossil Data Platform Rewritten in Rust 🦀

My data engineering team at Fossil recently released some of Rust-based components of our Data Platform after faced performance and maintenance challenges of the old Python codebase. I would like to share the insights and lessons learned during the process of migrating Fossil's Data Platform from Python to Rust.

2
Rust Data Engineering: Processing Dataframes with Polars

If you're interested in data engineering with Rust, you might want to check out Polars, a Rust DataFrame library with Pandas-like API.

3
Data Engineering Tools written in Rust

This blog post will provide an overview of the data engineering tools available in Rust, their advantages and benefits, as well as a discussion on why Rust is a great choice for data engineering.

4
Rust và Data Engineering? 🤔

Đối với một Data Engineer như mình, ưu tiên chọn một ngôn ngữ dựa trên việc nó có giải quyết được hết hầu hết các nhu cầu và bài toán của mình hay không: Data Engineering, Distributed System và Web Development. Và cuối cùng mình dự định sẽ bắt đầu với Rust, bởi vì ...

Series: Information Retrieval

1
Đánh giá hệ thống Information Retrieval

Trong bài này chúng ta sẽ tìm hiểu về cách đánh giá các hệ thống Information Retrieval, thách thức của việc đánh giá và các độ đo phổ biến như Precision/Accuracy, Recall, R-precision, F-measure, MAP, ...

2
Information Retrieval - Vector Space Model

Hệ thống tra cứu thông tin - Information Retrieval. Một hệ thống tìm kiếm thông tin (Information Retrieval - IR) là một hệ thống tra cứu (thường là các tài liệu văn bản) từ một nguồn không có cấu trúc tự nhiên (thường là văn bản), chứa đựng một số thông tin nào đó từ một tập hợp lớn. Một trong những kỹ thuật phổ biến trong Information Retrieval đó là Vector Space Model.