The Future of Hadoop: What Happened & What's Possible?
summary
Hadoop evolves from a brittle batch system into a scalable, reliable, secure kernel that other tools plug into: Pig and Hive add higher‑level queries, HBase and Impala add NoSQL and interactive SQL, and Spark and streaming add in‑memory and real‑time processing. The ecosystem removes single points of failure and broadens workloads; the claim is that virtually every workload — even online transaction processing per Google's paper — can be moved onto this enterprise data hub platform.
AI-written summary · about
chapters (9)
- 0:00Introduction
- 0:11The Challenge
- 0:50The Future
- 4:57Software
- 6:23Open Source
- 8:03Parallel
- 9:57Platform
- 11:48Transactions
- 13:51Conclusion
related talks
15mThe Future of Data
12mthe Rapidly Changing Hadoop Ecosystem
57mBig Data: Threat or Opportunity?
47mSolving Real & Big (Data) Problems Using Hadoop
01h 03mThe Future of Apache Hive and Hadoop 2.0: Bigger, Faster, Stronger
46mThe Evolution of the Open Data Ecosystem
56mResistance is Futile: What You Need to Know about Big Data
18mHadoop Ecosystem