DataStore configuration

Configure DataStore execution engine, logging, caching, and profiling

DataStore provides comprehensive configuration options for execution engine selection, compatibility mode, logging, caching, profiling, and dtype correction.

Quick Reference

from chdb.datastore.config import config

# Quick setup presets
config.enable_debug()           # Enable verbose logging
config.use_chdb()               # Force ClickHouse engine
config.use_pandas()             # Force pandas engine
config.use_auto()               # Auto-select engine (default)
config.use_performance_mode()   # SQL-first, max throughput
config.use_pandas_compat()      # Full pandas compatibility (default)
config.enable_profiling()       # Enable performance profiling

All Configuration Options

Category	Option	Values	Default	Description
Logging	log_level	DEBUG/INFO/WARNING/ERROR	WARNING	Log verbosity
	log_format	”simple”, “verbose"	"simple”	Log message format
Cache	cache_enabled	True/False	True	Enable result caching
	cache_ttl	float (seconds)	0.0	Cache time-to-live
Engine	execution_engine	”auto”, “chdb”, “pandas"	"auto”	Execution engine
	cross_datastore_engine	”auto”, “chdb”, “pandas"	"auto”	Cross-DataStore operations
Compat	compat_mode	”pandas”, “performance"	"pandas”	Pandas compatibility vs SQL-first throughput
Profiling	profiling_enabled	True/False	False	Enable profiling
Dtype	correction_level	NONE/CRITICAL/HIGH/MEDIUM/ALL	HIGH	Dtype correction level

---

Configuration Methods

Logging Configuration

from chdb.datastore.config import config
import logging

# Set log level
config.set_log_level(logging.DEBUG)
config.set_log_level(logging.INFO)
config.set_log_level(logging.WARNING)  # Default
config.set_log_level(logging.ERROR)

# Set log format
config.set_log_format("simple")   # Default
config.set_log_format("verbose")  # More details

# Quick enable debug mode
config.enable_debug()  # Sets DEBUG level + verbose format

See Logging for details.

Cache Configuration

# Enable/disable caching
config.set_cache_enabled(True)   # Default
config.set_cache_enabled(False)  # Disable caching

# Set cache TTL (time-to-live)
config.set_cache_ttl(60.0)  # Cache expires after 60 seconds
config.set_cache_ttl(0.0)   # No expiration (default)

# Check current settings
print(config.cache_enabled)
print(config.cache_ttl)

Engine Configuration

# Set execution engine
config.set_execution_engine('auto')    # Auto-select (default)
config.set_execution_engine('chdb')    # Force ClickHouse
config.set_execution_engine('pandas')  # Force pandas

# Quick presets
config.use_auto()     # Auto-select
config.use_chdb()     # Force ClickHouse
config.use_pandas()   # Force pandas

# Cross-DataStore engine (for operations between different DataStores)
config.set_cross_datastore_engine('auto')
config.set_cross_datastore_engine('chdb')
config.set_cross_datastore_engine('pandas')

# Check current engine
print(config.execution_engine)

See Execution Engine for details.

Compatibility Mode

# Performance mode: SQL-first, no pandas compatibility overhead
config.use_performance_mode()
# or: config.set_compat_mode('performance')

# Pandas compatibility mode (default)
config.use_pandas_compat()
# or: config.set_compat_mode('pandas')

# Check current mode
print(config.compat_mode)  # 'pandas' or 'performance'

See Performance Mode for details.

Profiling Configuration

# Enable profiling
config.enable_profiling()
config.set_profiling_enabled(True)

# Disable profiling
config.set_profiling_enabled(False)

# Check if profiling is enabled
print(config.profiling_enabled)

See Profiling for details.

Dtype Correction

from chdb.datastore.dtype_correction.config import CorrectionLevel

# Set correction level
config.set_correction_level(CorrectionLevel.NONE)      # No correction
config.set_correction_level(CorrectionLevel.CRITICAL)  # Critical types only
config.set_correction_level(CorrectionLevel.HIGH)      # Default
config.set_correction_level(CorrectionLevel.MEDIUM)    # More corrections
config.set_correction_level(CorrectionLevel.ALL)       # All corrections

---

Using config Object

The config object is a singleton that manages all settings:

from chdb.datastore.config import config

# Read settings
print(config.log_level)
print(config.execution_engine)
print(config.cache_enabled)
print(config.profiling_enabled)

# Modify settings
config.set_log_level(logging.DEBUG)
config.set_execution_engine('chdb')
config.set_cache_enabled(False)
config.enable_profiling()

---

Configuration in Code

Per-Script Configuration

from chdb import datastore as pd
from chdb.datastore.config import config

# Configure at script start
config.enable_debug()
config.use_chdb()
config.enable_profiling()

# Your DataStore code
ds = pd.read_csv("data.csv")
result = ds.filter(ds['age'] > 25).groupby('city').agg({'salary': 'mean'})

Context Manager (Future)

# Planned feature: temporary configuration
with config.override(execution_engine='pandas'):
    result = ds.process()
# Original settings restored

---

Common Configuration Scenarios

Development/Debugging

from chdb.datastore.config import config

config.enable_debug()        # Verbose logging
config.enable_profiling()    # Performance tracking
config.set_cache_enabled(False)  # Disable caching for fresh results

Production

from chdb.datastore.config import config
import logging

config.set_log_level(logging.WARNING)  # Minimal logging
config.set_execution_engine('auto')    # Optimal engine selection
config.set_cache_enabled(True)         # Enable caching
config.set_profiling_enabled(False)    # Disable profiling overhead

Maximum Throughput

from chdb.datastore.config import config

config.use_performance_mode()    # SQL-first, no pandas overhead
config.set_cache_enabled(False)  # Disable cache for streaming

Performance Testing

from chdb.datastore.config import config

config.use_chdb()            # Force ClickHouse for benchmarks
config.enable_profiling()    # Track performance
config.set_cache_enabled(False)  # Disable cache for accurate timing

Pandas Compatibility Testing

from chdb.datastore.config import config

config.use_pandas()          # Force pandas engine
config.enable_debug()        # See what operations are used

---

Related Documentation

• Execution Engine - Engine selection details
• Performance Mode - SQL-first mode for maximum throughput
• Function Config - Per-function engine configuration
• Logging - Logging configuration
• Profiling - Performance profiling