Travelled to:1 × Australia
5 × USA
Collaborated with:I.Stoica S.Shenker M.J.Franklin P.Wendell James J. Thomas P.Hanrahan T.Das J.Rosen R.S.Xin J.v.d.Hooff D.Lazar N.Zeldovich K.Ousterhout R.Xin A.Konwinski A.D.Joseph R.H.Katz M.Armbrust A.Ghodsi H.Li T.Hunter C.Engle A.Lupher A.Davidson A.Or C.Lian Y.Huai D.Liu J.K.Bradley X.Meng T.Kaftan
Talks about:stream (3) spark (3) scale (3) distribut (2) perform (2) analysi (2) shark (2) data (2) sql (2) heterogen (1)
Person: Matei Zaharia
DBLP: Zaharia:Matei
Contributed to:
2015
2015
2015201320132012
2008
2020Wrote 9 papers:
- SIGMOD-2015-ArmbrustXLHLBMK #relational #sql
- Spark SQL: Relational Data Processing in Spark (MA, RSX, CL, YH, DL, JKB, XM, TK, MJF, AG, MZ), pp. 1383–1394.
- SOSP-2015-HooffLZZ #analysis #named #scalability
- Vuvuzela: scalable private messaging resistant to traffic analysis (JvdH, DL, MZ, NZ), pp. 137–152.
- VLDB-2015-ArmbrustDDGORSW #performance #scalability #usability
- Scaling Spark in the Real World: Performance and Usability (MA, TD, AD, AG, AO, JR, IS, PW, RX, MZ), pp. 1840–1851.
- SIGMOD-2013-XinRZFSS #named #scalability #sql
- Shark: SQL and rich analytics at scale (RSX, JR, MZ, MJF, SS, IS), pp. 13–24.
- SOSP-2013-OusterhoutWZS #distributed #latency #named #scheduling
- Sparrow: distributed, low latency scheduling (KO, PW, MZ, IS), pp. 69–84.
- SOSP-2013-ZahariaDLHSS #fault tolerance #scalability #streaming
- Discretized streams: fault-tolerant streaming computation at scale (MZ, TD, HL, TH, SS, IS), pp. 423–438.
- SIGMOD-2012-EngleLXZFSS #data analysis #distributed #memory management #named #performance #using
- Shark: fast data analysis using coarse-grained distributed memory (CE, AL, RX, MZ, MJF, SS, IS), pp. 689–692.
- OSDI-2008-ZahariaKJKS #performance #pipes and filters
- Improving MapReduce Performance in Heterogeneous Environments (MZ, AK, ADJ, RHK, IS), pp. 29–42.
- ASPLOS-2020-ThomasHZ #framework #named #parallel #streaming
- Fleet: A Framework for Massively Parallel Streaming on FPGAs (JJT, PH, MZ), pp. 639–651.