Fault-tolerant Mapreduce

Fault-Tolerant MapReduce is a distributed data processing framework that extends the MapReduce paradigm by incorporating mechanisms for error detection, task replication, and automated recovery to ensure reliable execution in the presence of node failures or system faults.

121

Publications

26.6K

Citations

405

Authors

149

Institutions

Publications per year

2017–2026

11

Authors

405

  1. IS
    Ion Stoica

    University of California, Berkeley, United States

    6 publications · 803 citations

    6

    h-index

  2. SS
    Scott Shenker

    University of California, Berkeley, United States

    5 publications · 705 citations

    5

    h-index

  3. MZ
    Matei Zaharia

    Stanford University, United States

    4 publications · 581 citations

    4

    h-index

  4. JR
    Josh Rosen

    University of California, Berkeley, United States

    4 publications · 471 citations

    4

    h-index

  5. RX
    Reynold Xin

    University of California, Berkeley, United States

    4 publications · 581 citations

    4

    h-index

1–5 of 405

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 3 publications · 192 citations

    3

    h-index

  2. Procedia Computer Science

    3 publications · 187 citations

    3

    h-index

  3. Communications of the ACM

    2 publications · 19.7K citations

    2

    h-index

  4. ACM Transactions on Graphics

    TOG · 2 publications · 198 citations

    2

    h-index

  5. Journal of Internet Services and Applications

    JISA · 2 publications · 30 citations

    2

    h-index

1–5