qink 0.1.2

A real-time data processing framework

Qink

Qink is a powerful distributed data processing framework designed for efficiently consuming and processing partitioned data streams.

Features

• Partition-based Processing 📊: Handles partitioned data sources with exceptional efficiency, improving performance metrics.
• Parallel Processing ⚡: Processes multiple partitions simultaneously with configurable workers per partition.
• State Management 🛡️: Maintains processing state with reliability, ensuring fault tolerance.
• Checkpointing: Saves state at regular intervals to ensure data durability.
• Key-based Distribution: Distributes keys to workers with consistent precision for optimized processing.

Usage

import logging
from datetime import timedelta
from qink.lib.qink import Qink
from qink.lib.qink_storage_provider import YourStorageProvider
from qink.lib.qink_source import YourDataSource

# Configure Qink
logger = logging.getLogger("qink")
storage_provider = YourStorageProvider()
workers_per_partition = 4  # Customize for optimal performance
checkpoint_interval = timedelta(minutes=5)

# Initialize and start Qink
qink = Qink(
    logger=logger,
    storage_provider=storage_provider,
    workers_per_partition=workers_per_partition,
    checkpoint_interval=checkpoint_interval
)

# Connect to your data source
qink.source(YourDataSource()).start()

Testimonials

"Qink revolutionized our data pipeline efficiency." - Data Engineering Team Lead

"After implementing Qink, our processing speeds improved dramatically." - Enterprise Architect

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Copyright 2024 Quadible

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