the Rapidly Changing Hadoop Ecosystem
summary
Hadoop evolves from batch-only to a platform running Impala, Spark, Kafka and MLlib so a single copy of data serves interactive queries, streaming and machine learning; dozens of ETL/BI tools (Tableau, SAS) now connect natively. Real‑time means hundreds of milliseconds to a few seconds and about 20–30% of customers already run streaming apps; examples include sepsis detection in hospitals and credit‑risk model gains that save millions. Cloud use grows, with mainstream enterprise adoption estimated in 18–24 months.
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chapters (5)
- 0:00What are the key changes in the Hadoop ecosystem
- 1:44What practical problems do these changes solve
- 4:24Realtime applications
- 7:41Cloud computing
- 9:59Trends
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