dreml - Linux

Overview

dreml is a modern, high-performance tool for streaming data processing, real-time analytics, and continuous learning. It offers a fast, flexible, and scalable solution for processing massive amounts of data in motion.

Syntax

dreml [options] <source> <sink> [processor]

Options/Flags

  • -s, –source: The input data source (e.g., Kafka, S3, files)
  • -t, –sink: The output data sink (e.g., Kafka, S3, HDFS)
  • -p, –processor: The data processor to apply (e.g., filter, map, reduce)
  • –parallelism: The level of parallelism to use (default: 1)
  • –state-store: Path to the state store directory (e.g., RocksDB, Redis)
  • –checkpoint-interval: Interval (in milliseconds) for checkpointing state (default: 30000)
  • –help: Display help information

Examples

Streaming log processing:

dreml -s kafka -t s3 -p filter="level=ERROR"

Real-time fraud detection:

dreml -s kafka -t redis -p map="score=calculate_fraud_score(transaction)" -p filter="score>0.5"

Continuous learning:

dreml -s s3 -p train="model=train_classifier(data)" -t model-store -p serve="model=load_classifier(model-store)" -t kafka

Common Issues

  • Out-of-memory errors: Increase the available memory for the JVM or adjust the parallelism level.
  • Checkpointing failures: Ensure the --state-store directory has sufficient write permissions.
  • Slow processing: Optimize the data processors or increase the parallelism level.

Integration

  • Use dreml as a data source or sink for other data processing tools like Spark, Hadoop, or Flink.
  • Create scripts or command chains that combine dreml with other commands for complex data processing tasks.

Related Commands

  • Kafka
  • Flink
  • Spark
  • Redis