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APACHE HADOOP
Distributed storage and processing for big data and AI pipelines
Apache-2.0
ABOUT
AI and agentic systems need to store, manage, and process petabytes of distributed data (training corpora, logs, telemetry) across clusters. Hadoop solves reliable, fault-tolerant distributed storage and large-scale batch processing on commodity hardware without expensive proprietary infrastructure, enabling teams to build scalable data pipelines for ML training and inference.
INSTALL
brew install hadoopINTEGRATION GUIDE
1. Store and manage petabyte-scale training datasets for LLM fine-tuning across distributed HDFS clusters
2. Batch preprocess and transform raw web-crawl data into clean training corpora using MapReduce jobs
3. Archive and serve agent interaction logs and telemetry for downstream analytics and model improvement
4. Run distributed Spark ML training jobs on data stored in HDFS for production AI pipelines
TAGS
big-datadistributed-storagehdfsmapreduceyarndata-processingbatch-processing