MapReduce: Simplified Data Processing on Large Clusters by Dean and Ghemawat
Shares rank 4 of 7 research papers by recommenders
Recommended for its influential design for automatic, fault-tolerant parallel data processing that people say still holds up today.
Recommended for its influential design for automatic, fault-tolerant parallel data processing that people say still holds up today.
7 people gave an opinion
- recommend it
- 6
- criticize it
- 1
- approval share
- 86%
Recommended in 5 of 13 months
- November 2025: recommended
- December 2025: not recommended
- January 2026: recommended
- February 2026: not recommended
- March 2026: not recommended
- April 2026: recommended
- May 2026: not recommended
- June 2026: not recommended
- July 2026: recommended
- August 2026: not recommended
- September 2026: recommended
- October 2026: not recommended
- November 2026: not recommended (month in progress)
Why it doesn’t carry the badge
- 6 people recommend itNeeds 10 or more, not met.
- 6 recommenders for every criticNeeds 2 to 1 or better, met.
- Recommended in 5 of 13 monthsNeeds 4 or more, met.
The same three rules apply to every product, and the badge can’t be bought. How the badge works
What people say about it
The reasons people give, with the number of comments that give each one. Open a reason to read what they said.
Why people recommend it
Each mark is one comment
Fault-tolerant, automatic parallel data partitioning
“inventing a way to make map/reduce fault tolerant and automatic partitioning of data”
Comment from 10 Apr 2026 in “NASA Built Artemis II's Fault-Tolerant Computer” Parallelism that stays manageable to reason about
“it hit a kind of sweet spot between parallelism utility and complexity of knowledge or reasoning required of its users”
Comment from 6 Nov 2025 in “I want a good parallel language [video]” Technologies that still hold up
“They made impressive technologies that still hold up today”
Comment from 12 Jul 2026 in “The 'Father of the Internet' is finally retiring” Inspired people to work at Google
“Your original MapReduce paper is what inspired me to work for Google”
Comment from 9 Jan 2026 in “The Jeff Dean Facts”
Other research papers people recommend
The four most recommended other research papers, with the same counts for each, so you can compare like for like. The tick on each bar marks the 2 to 1 line the badge needs.
| Product | Recommend | Criticize | Approval | Months | Owned | Badge |
|---|---|---|---|---|---|---|
| The Ironies of Automation by Lisanne Bainbridge | 14 | 0 | 100% | 7 | — | Approved |
| Attention Is All You Need by Vaswani et al. | 14 | 2 | 88% | 7 | — | Approved |
| Structured Programming with go to Statementsby Donald Knuth | 7 | 1 | 88% | 4 | — | — |
| MapReduce: Simplified Data Processing on Large Clusters by Dean and GhemawatThis page | 6 | 1 | 86% | 5 | — | — |
| The Windows 95 User Interface: A Case Study in Usability Engineering by Microsoft | 6 | 0 | 100% | 2 | — | — |
What people said
5 of the 7 comments that mention it, newest first. Each links to the original comment.
“They made impressive technologies that still hold up today”
“inventing a way to make map/reduce fault tolerant and automatic partitioning of data”
“Your original MapReduce paper is what inspired me to work for Google”
“implementation was pretty average”
“it hit a kind of sweet spot between parallelism utility and complexity of knowledge or reasoning required of its users”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.