ArkFlow - High-performance Rust stream processing engine

#rust #tokio #arkflow

ArkFlow

github: https://github.com/chenquan/arkflow

High-performance Rust stream processing engine, providing powerful data stream processing capabilities, supporting multiple input/output sources and processors.

Features

High Performance: Built on Rust and Tokio async runtime, offering excellent performance and low latency
Multiple Data Sources: Support for Kafka, MQTT, HTTP, files, and other input/output sources
Powerful Processing Capabilities: Built-in SQL queries, JSON processing, Protobuf encoding/decoding, batch processing, and other processors
Extensible: Modular design, easy to extend with new input, output, and processor components

Installation

Building from Source

# Clone the repository
git clone https://github.com/chenquan/arkflow.git
cd arkflow

# Build the project
cargo build --release

# Run tests
cargo test

Quick Start

Create a configuration file config.yaml:

logging:
  level: info
streams:
  - input:
      type: "generate"
      context: '{ "timestamp": 1625000000000, "value": 10, "sensor": "temp_1" }'
      interval: 1s
      batch_size: 10

    pipeline:
      thread_num: 4
      processors:
        - type: "json_to_arrow"
        - type: "sql"
          query: "SELECT * FROM flow WHERE value >= 10"
        - type: "arrow_to_json"

    output:
      type: "stdout"

Run ArkFlow:

./target/release/arkflow --config config.yaml

Configuration Guide

ArkFlow uses YAML format configuration files, supporting the following main configuration items:

Top-level Configuration

logging:
  level: info  # Log level: debug, info, warn, error

streams:       # Stream definition list
  - input:      # Input configuration
      # ...
    pipeline:   # Processing pipeline configuration
      # ...
    output:     # Output configuration
      # ...

Input Components

ArkFlow supports multiple input sources:

Kafka: Read data from Kafka topics
MQTT: Subscribe to messages from MQTT topics
HTTP: Receive data via HTTP
File: Read data from files
Generator: Generate test data
SQL: Query data from databases

Example:

input:
  type: kafka
  brokers:
    - localhost:9092
  topics:
    - test-topic
  consumer_group: test-group
  client_id: arkflow
  start_from_latest: true

Processors

ArkFlow provides multiple data processors:

JSON: JSON data processing and transformation
SQL: Process data using SQL queries
Protobuf: Protobuf encoding/decoding
Batch Processing: Process messages in batches

Example:

pipeline:
  thread_num: 4
  processors:
    - type: json_to_arrow
    - type: sql
      query: "SELECT * FROM flow WHERE value >= 10"
    - type: arrow_to_json

Output Components

ArkFlow supports multiple output targets:

Kafka: Write data to Kafka topics
MQTT: Publish messages to MQTT topics
HTTP: Send data via HTTP
File: Write data to files
Standard Output: Output data to the console

Example:

output:
  type: kafka
  brokers:
    - localhost:9092
  topic: output-topic
  client_id: arkflow-producer

Examples

Kafka to Kafka Data Processing

streams:
  - input:
      type: kafka
      brokers:
        - localhost:9092
      topics:
        - test-topic
      consumer_group: test-group

    pipeline:
      thread_num: 4
      processors:
        - type: json_to_arrow
        - type: sql
          query: "SELECT * FROM flow WHERE value > 100"
        - type: arrow_to_json

    output:
      type: kafka
      brokers:
        - localhost:9092
      topic: processed-topic

Generate Test Data and Process

streams:
  - input:
      type: "generate"
      context: '{ "timestamp": 1625000000000, "value": 10, "sensor": "temp_1" }'
      interval: 1ms
      batch_size: 10000

    pipeline:
      thread_num: 4
      processors:
        - type: "json_to_arrow"
        - type: "sql"
          query: "SELECT count(*) FROM flow WHERE value >= 10 group by sensor"
        - type: "arrow_to_json"

    output:
      type: "stdout"