5.1万- Resources
- Engineering
ClickHouse engineering resources
Build a dashboard in Python with ClickHouse and Streamlit
In this guide, you'll learn how to build a Python dashboard using ClickHouse and Streamlit. We'll create a real-world example that visualizes Bluesky social media data, walking through everything from basic setup to interactive visualizations. Perfect for data scientists and analysts who want to share their insights through custom dashboards.
Last updated: 2025年6月2日
Instrumenting OpenAI with OpenTelemetry (OTel)
In this guide, we’ll learn how to instrument the OpenAI client with OpenTelemetry (OTel) so that we can generate and collect observability data about our LLM calls.
Last updated: 2025年8月1日
Real-time data visualization
This guide is all about real-time data visualization. We'll explore how it differs from normal visualization, see some examples, and learn about the tools we can use.
Last updated: 2025年4月11日
What is a columnar database?
A columnar database stores each column on disk separately to cut I/O and compress aggressively. Here is what that means in practice and when to use one.
Last updated: 2026年5月25日
ClickHouse concurrency: how to size for user-facing analytics
How to size ClickHouse for high-concurrency, user-facing analytics: turn active users into query load, benchmark under production-like conditions, and configure per-query limits, admission controls, workload scheduling, and replicas.
Last updated: 2026年7月2日
When to denormalize, when to join: A ClickHouse guide
Denormalization and normalization are both valid analytical data-modeling strategies. A decision framework for choosing where to denormalize, where to join, and which ClickHouse primitives bridge the gap.
Last updated: 2026年6月26日
How to query a REST API in Python
Read a JSON API response into a DataFrame with chDB. Use the pandas API you already know to filter and aggregate the response, running on ClickHouse's engine with no server to start.
Last updated: 2026年6月15日
How to convert Parquet to ORC
Convert a Parquet file to ORC with one clickhouse-local command. The schema is read from the Parquet footer and the types carry into ORC, with no server and no upload.
Last updated: 2026年6月6日
How to query a REST API with SQL
Run SQL straight against a live JSON or CSV HTTP endpoint with clickhouse local — fetch, filter, aggregate and join the response in one statement, with no download step.
Last updated: 2026年6月15日
Parse url-encoded form data with SQL
Turn an application/x-www-form-urlencoded body like a=1&b=hello into a queryable row with clickhouse local, with no parsing code and no import step.
Last updated: 2026年6月15日
What is Protobuf?
Protobuf (Protocol Buffers) is a schema-first, compact binary serialization format. This page explains its structure, the .proto schema requirement, and proves it by writing and reading a real Protobuf file.
Last updated: 2026年6月15日
Run SQL across multiple CSV or Parquet files
Query a whole directory of CSV or Parquet files as one table with clickhouse-local. A glob path reads them all, aggregates run across every file, and a virtual column tells you which file each row came from.
Last updated: 2026年6月15日
Read Avro from a schema registry with clickhouse-local
Read a plain .avro file with one command, and use the AvroConfluent format plus format_avro_schema_registry_url to read Confluent-framed Avro messages from a Kafka Schema Registry.
Last updated: 2026年6月15日
How to query a mysqldump file without importing
Run SQL against the tables inside a mysqldump .sql file directly with clickhouse-local. No MySQL server, no restore step — the INSERT statements are read as a table.
Last updated: 2026年6月15日
How to convert Avro to JSON
Convert an Avro file to JSON with one command using clickhouse-local. The schema is read from the Avro file itself, types are carried into JSON, and there is no upload and no server.
Last updated: 2026年6月15日