Module 4: Loading Data into ClickHouse
- Using the INSERT INTO ... VALUES statement for small datasets
- Bulk loading data using INSERT INTO ... FORMAT (CSV, TSV, JSONEachRow)
- Loading data from files using clickhouse-client
- Integrating with external sources (e.g., Kafka Engine basics, S3 table function overview)
- Best practices for efficient data ingestion
Module 3: Data Types & MergeTree Family Engines
- Overview of ClickHouse Data Types (Numeric, String, Date/Time, Array, Nullable, etc.)
- Introduction to Table Engines concept
- Deep dive into the MergeTree engine: primary keys, sorting keys, and partitioning
- Exploring ReplacingMergeTree for de-duplication scenarios
- Understanding SummingMergeTree and AggregatingMergeTree for pre-aggregation
Module 2: Installation, Connecting, and Basic Schema
- Installation methods: Docker, Packages, Developer mode
- Connecting using clickhouse-client and other tools (e.g., DBeaver)
- Working with Databases (CREATE, SHOW, DROP)
- Creating basic Tables (CREATE TABLE).Understanding server configuration basics (config.xml, users.xml)
- Understanding server configuration basics (config.xml, users.xml)
Module 1: ClickHouse Introduction & Core Concepts
- Understanding OLAP vs. OLTP workloads
- ClickHouse Architecture Overview (Distributed nature, components)
- Key Concept: Columnar Storage (Rows vs. Columns) and its advantages
- Vectorized Query Execution Fundamentals
- Everyday Use Cases (Web Analytics, Logs, Time Series, Reporting)