50,6 k- Resources
- Engineering
ClickHouse engineering resources
How to convert Parquet to TSV
Convert a Parquet file to tab-separated values with one clickhouse-local command. Types are read from the Parquet footer, nothing is uploaded, and files larger than RAM stream through.
Last updated: 8 juin 2026
How to convert Parquet to NDJSON
Convert a Parquet file to NDJSON from your terminal with clickhouse-local — one command, no server and no upload, with the Parquet schema read straight from the file footer.
Last updated: 8 juin 2026
How to convert Parquet to JSONL
Convert a Parquet file to newline-delimited JSON (JSONL) with one clickhouse-local command — schema read from the Parquet footer, types carried into JSON, nested columns preserved. No server, no upload.
Last updated: 8 juin 2026
How to convert Parquet to JSON
Convert a Parquet file to JSON from your terminal with clickhouse-local — the schema is read from the Parquet footer, and typed and nested columns carry straight into JSON. No server, no upload.
Last updated: 8 juin 2026
How to convert Parquet to CSV
Convert a Parquet file to CSV from your terminal with clickhouse-local — one command, schema read from the file, types written as text, no upload and no server.
Last updated: 8 juin 2026
How to convert NDJSON to Parquet
Convert an NDJSON (or JSONL) file to Parquet with one clickhouse-local command — the schema is auto-inferred and nested objects and arrays are carried straight into Parquet, with no upload and no server.
Last updated: 8 juin 2026
How to convert JSONL to Parquet
Convert a JSONL file to Parquet with one command using clickhouse-local — column types are inferred automatically and nested objects become real Parquet structs, with no server and no upload.
Last updated: 8 juin 2026
How to convert JSON to Parquet
Convert a JSON or NDJSON file to Parquet with one clickhouse-local command — schema is inferred automatically and types are carried across, including nested objects, with no server and no upload.
Last updated: 8 juin 2026
How to convert CSV to TSV
Convert a CSV file to tab-separated values in one command with clickhouse-local. The header is kept, column types are carried over, and nothing is uploaded.
Last updated: 8 juin 2026
How to convert CSV to Parquet
Convert a CSV file to Parquet with one command using clickhouse-local — types are inferred from the CSV, you choose the compression codec, and there is no upload and no server.
Last updated: 8 juin 2026
How to analyze log files with SQL
Query raw nginx, Apache, or application logs in place with clickhouse-local. No server, no pipeline, no import step: one binary, SQL, and the file on disk.
Last updated: 8 juin 2026
OPTIMIZE TABLE ... FINAL in ClickHouse: when to use it, when to avoid it, and how merges work
Stop running OPTIMIZE TABLE FINAL in ClickHouse. Learn how parts and background merges work, avoid part explosions, and fix duplicates safely. Read now.
Last updated: 15 juin 2026
How to choose a database for real-time analytics in 2026
In 2026, the gap between "Data Warehouse" and "Real-Time Serving" has become the primary bottleneck for data teams. For the last decade, we've operated on a split model: transactional databases (OLTP) handled application state, and data warehouses (DWH) handled nightly reporting.
Last updated: 25 mars 2026
Unifying OLTP and OLAP: HTAP databases, zero-ETL, and best-of-breed architectures
A complete guide to unifying transactional and analytical workloads. Covers HTAP databases, zero-ETL integration, Postgres CDC, columnar databases, and how composable architectures beat converged systems.
Last updated: 29 mars 2026
What is OLAP?
OLAP is a category of database systems and workloads built for analytical queries across millions to billions of rows. This is what OLAP is, how MOLAP, ROLAP, and HOLAP differ, and why OLAP databases in 2026 run on columnar engines rather than pre-built cubes.
Last updated: 27 mai 2026