Results for “bulk-processing”

Designs and implements big data architectures, processes large-scale datasets with distributed systems, and optimizes data pipelines for throughput using Hadoop, Spark, and cloud platforms.

Implements Bulk API 2.0 REST calls for ingest and query jobs, covering CSV format requirements, locator pagination, and v1 vs v2 selection.

Guides when to use Salesforce Bulk API 2.0 and provides commands for importing, updating, upserting, deleting, and exporting records, along with CSV format requirements, limits, and error handling.

Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.

Process large-scale ML datasets with distributed streaming execution across CPU/GPU, supporting Parquet, CSV, JSON, images, and integration with PyTorch, TensorFlow, and Ray Train.

Scale pandas and NumPy workflows to larger-than-memory datasets using parallel and distributed computing.

Processes STIX 2.1 threat intelligence bundles from TAXII 2.1 servers, normalizing objects into platform-native schemas and routing them to consuming systems.