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Jordan Tigani

PROFILE

Jordan Tigani

Worked on the ClickHouse/ClickBench repository to modernize and streamline database benchmarking workflows. Developed a Parquet-based data loading system, replacing the legacy CSV loader, and refactored benchmark scripts to ensure data is loaded before query execution, improving reliability and data fidelity. Introduced the PgDuckDB-MotherDuck Benchmark Suite, leveraging Docker and PostgreSQL to enable end-to-end performance testing with simplified configuration and enhanced documentation. Applied repository hygiene improvements by standardizing directory naming conventions. Utilized Python, Bash, and SQL to automate data loading, scripting, and environment setup, demonstrating a methodical approach to maintainability and reproducibility in database benchmarking and DevOps practices.

Overall Statistics

Feature vs Bugs

67%Features

Repository Contributions

8Total
Bugs
1
Commits
8
Features
2
Lines of code
686
Activity Months2

Work History

November 2024

6 Commits • 1 Features

Nov 1, 2024

November 2024 (ClickBench/ClickHouse): Delivered a robust PgDuckDB-MotherDuck Benchmark Suite and associated reliability improvements for end-to-end performance testing. Simplified configuration to exclusively use MotherDuck, improving setup reliability and onboarding. Refined Docker-based environments (host network for realism) and streamlined setup commands, with updated docs and helpful comments to boost maintainability. Implemented repository hygiene improvements to align with conventions while preserving functional behavior.

October 2024

2 Commits • 1 Features

Oct 1, 2024

October 2024 monthly summary for ClickBench (ClickHouse/ClickBench repo): Implemented Parquet-based data loading for the ClickBench dataset, replacing the legacy CSV loader. Refactored the benchmark script to load data from Parquet before running benchmark queries to ensure reliable, reproducible results. Removed the old log file that captured query execution times to streamline benchmarking and reduce noise. These changes improve data fidelity, shorten setup time, and align benchmarks with production data formats.

Activity

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Quality Metrics

Correctness85.0%
Maintainability87.4%
Architecture82.6%
Performance75.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

BashPythonSQLShell

Technical Skills

ClickHouseData LoadingDatabase BenchmarkingDatabase ManagementDevOpsDockerPostgreSQLSQLScriptingShell Scripting

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

ClickHouse/ClickBench

Oct 2024 Nov 2024
2 Months active

Languages Used

PythonSQLShellBash

Technical Skills

Data LoadingDatabase ManagementScriptingClickHouseDatabase BenchmarkingDevOps