Samza is Apache's stream processing framework for real-time processing of Kafka or other message topics. Stateless (map/filter operations) or stateful (aggregations, joins) processing. Used by LinkedIn and other large-scale systems for analytics, fraud detection, recommendations, and data pipelines. Requires Java/Scala, understanding of distributed systems, and Kafka fundamentals. Learnable in 8–10 weeks. Overlaps with Spark, Flink, and other stream processors. Salaries $145K–$200K for stream processing engineers. Declining in favor of Kafka Streams and Flink but still actively used in large organizations.
Samza is Apache's open-source stream processing framework for real-time processing of events from Kafka or other message systems. Samza jobs read from message topics, process events (filtering, mapping, aggregating, joining), and write to output topics or external systems. Samza excels at low-latency, high-throughput event processing with exactly-once semantics (no duplicates or losses). Key concepts: stateless operations (simple transformations), stateful operations (aggregations, JOINs using local state stores), windowing (time-based grouping), and checkpointing (fault tolerance). Samza is tightly integrated with Kafka, designed for high-volume event streams.
| Mintaqa | Kichik mutaxassis | Oʻrta darajali | Katta mutaxassis |
|---|---|---|---|
| USA | $110k | $165k | $230k |
| UK | $65k | $105k | $150k |
| EU | $70k | $110k | $160k |
| CANADA | $100k | $155k | $220k |
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