This page covers smaller utility commands for dependency checking, system profiling, benchmark discovery, and configuration validation.
(cli-check-deps)=
Check dependency status and provide installation guidance for different platforms.
--platform TEXT: Check dependencies for specific platform--verbose,-v: Show detailed dependency information--matrix: Show installation matrix and exit
benchbox check-deps
benchbox check-deps --platform databricks
benchbox check-deps --matrix
benchbox check-deps --verboseThe commands, in order, give an overview of all platform dependencies, check one platform, show the detailed installation matrix, and give verbose output with recommendations.
(cli-profile)=
Profile the current system to understand hardware capabilities and provide recommendations.
benchbox profileThis command analyzes:
- CPU cores and architecture
- Memory capacity and availability
- Disk space
- Operating system details
- Python environment
Provides recommendations for:
- Appropriate scale factors
- Concurrency settings
- Platform selection
(cli-benchmarks)=
Manage and browse available benchmark suites.
Display all available benchmark suites with descriptions.
benchbox benchmarks listShows information about:
- TPC-H, TPC-DS, TPC-DI (official TPC benchmarks)
- ClickBench, H2ODB (industry benchmarks)
- SSB, AMPLab (academic benchmarks)
- ReadPrimitives, WritePrimitives, TPC-Havoc (testing benchmarks)
(cli-validate)=
Validate BenchBox configuration files for syntax and completeness.
--config TEXT: Configuration file path (optional)
benchbox validate
benchbox validate --config ./custom-config.yamlThe first command validates the default configuration and the second validates a specific configuration file.
(cli-validate-results)=
Result integrity validation checks benchmark result JSON files for structural integrity, completeness, and statistical believability. It runs 20 checks across three tiers against hardcoded benchmark specifications.
There is no benchbox subcommand for it; benchbox validate checks
configuration files, not result bundles. With the installed package, use the
validate_results tool of the MCP server, which accepts one
result file or a directory of result files. Contributors working from a source
checkout can also run the standalone validate_results.py script, which wraps
the same validator.
See the Result Integrity Validation developer guide for the full check list.
Notes:
- Automatically excludes
.plans.jsonand.tuning.jsoncompanion files - Specs cover 21 of 22 benchmarks with 8 legacy alias mappings (e.g.,
star_schema→ssb);ai_primitivesis not yet covered
- Result Integrity Validation - Architecture and check details
- Configuration - Configuration file format and options
- Platforms - Platform management commands