I manage the Redmond site of Gray Systems Lab (GSL) at Microsoft.
GSL is an applied research lab under Azure Data that focuses on research and development for databases, big-data, and cloud systems. My research focusses on improving the performance of large-scale data-intensive systems. Earlier, I was a postdoc associate in the Database Group at MIT CSAIL, working with Professors Sam Madden and Michael Stonebraker. I received my PhD from Saarland University, working with Prof. Jens Dittrich, During my PhD, I worked on flexible and scalable data storage for traditional databases as well as for MapReduce. Before that I completed masters studies at Max Planck Institute for Informatics and received bachelor degree from IIT Kanpur.
Research Interests
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Machine Learning for Databases
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Workload Optimization in Cloud Data Services
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Large-scale Data-intensive Systems
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Data Preparation and Design
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Big Data Analytics
Current Projects
Past Projects
Publications
DBLP, Google Scholar
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Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft
VLDB 2020, Tokyo, Japan. (to appear)
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Malay Bag, Alekh Jindal, Hiren Patel
Towards Plan-aware Resource Allocation in Serverless Query Processing
HotCloud 2020, Boston, USA. (to appear)
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Alekh Jindal
Applied Research Lessons from CloudViews Project
SIGMOD Record (to appear)
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Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao Le
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
SIGMOD 2020, Portland, USA.arXiv
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H M Sajjad Hossain, Lucas Rosenblatt, Gilbert Antonius, Irene Shaffer, Remmelt Ammerlaan, Abhishek Roy, Markus Weimer, Hiren Patel, Marc Friedman, Shi Qiao, Peter Orenberg, Soundarajan Srinivasan, Vijay Ramani, Alekh Jindal
PerfGuard: Deploying ML-for-Systems without Performance Regressions
MLOps Systems 2020, Austin, USA.
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Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Gowdal, Matteo Interlandi, Alekh Jindal, Kostantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
CIDR 2020, Amsterdam, Netherlands.
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Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Jarod Yin, Rathijit Sen, Subru Krishnan
Peregrine: Workload Optimization for Cloud Query Engines
SOCC 2019, Santa Cruz, California.
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Hiren Patel, Alekh Jindal, Clemens Szyperski
Big Data Processing at Microsoft: Hyper Scale, Massive Complexity, and Minimal Cost
SOCC 2019, Santa Cruz, California. (poster)
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Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
SparkCruise: Handsfree Computation Reuse in Spark
VLDB 2019/PVLDB, Los Angeles, USA. (Demo paper)
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Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Towards a Learning Optimizer for Shared Clouds
VLDB 2019/PVLDB, Los Angeles, USA.
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Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
arXiv:1906.06590 [cs.DB], June 2019
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Alekh Jindal, Anil Shanbhag, Yi Lu
Robust Data Partitioning
Encyclopedia of Big Data Technologies, 2019, Springer.
Invited Chapter
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Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Selecting Subexpressions to Materialize at Datacenter Scale
VLDB 2018/PVLDB, Rio de Janeiro, Brazil.
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Alekh Jindal, Shi Qiao, Hiren Patel, Jarod Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
Computation Reuse in Analytics Job Service at Microsoft
SIGMOD 2018, Houston, USA.
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Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
Query and Resource Optimization: Bridging the Gap
ICDE 2018, Paris, France (Short paper).
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Kristin Tufte, Kushal Datta, Alekh Jindal, David Maier, Robert L Bertini
Challenges and Opportunities in Transportation Data
Symposium on Smart Cities and Communities 2018, Portland, USA.
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Anil Shanbhag, Alekh Jindal, Samuel Madden, Jorge Quiane, Aaron Elmore
A Robust Partitioning Scheme for Ad-Hoc Query Workloads
SOCC 2017, Santa Clara, USA.
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Yi Lu, Anil Shanbhag, Alekh Jindal, Samuel Madden
AdaptDB: Adaptive Partitioning for Distributed Joins
VLDB 2017, Munich, Germany.
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Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Samuel Madden
IngestBase: A Declarative Data Ingestion System
arXiv:1701.06093 [cs.DB], Jan 2017
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Anil Shanbhag, Alekh Jindal, Yi Lu, Samuel Madden
Amoeba: A Shape changing Storage System for Big Data
VLDB 2016, New Delhi, India. (Demo paper)
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Ankur Dave, Alekh Jindal, Li Erran Li, Reynold Xin, Joseph Gonzalez, Matei Zaharia
GraphFrames: An Integrated API for Mixing Graph and Relational Queries
GRADES 2016, California, USA.
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Alekh Jindal, Samuel Madden, Malú Castellanos, Meichun Hsu
Graph Analytics using Vertica Relational Database
IEEE BigData 2015, Santa Clara, USA.
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Felix Martin Schuhknecht, Alekh Jindal, Jens Dittrich
An Experimental Evaluation and Analysis of Database Cracking
The VLDB Journal, August 2015
Special Issue on best papers of VLDB 2014
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Zuhair Khayyat, Ihab F. Ilyas, Alekh Jindal, Samuel Madden, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiane-Ruiz, Nan Tang, Si Yin
BigDansing: A System for Big Data Cleansing
SIGMOD 2015, Melbourne, Australia.
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Alekh Jindal
Robust Data Transformations
CIDR 2015, Asilomar, USA. (Abstract)
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Alekh Jindal, Samuel Madden, Malu Castellanos, Meichun Hsu
Graph Analytics using the Vertica Relational Database
arXiv:1412.5263 [cs.DB], Dec 17, 2014
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Alekh Jindal, Samuel Madden
GraphiQL: A Graph Intuitive Query Language for Relational Databases
IEEE BigData 2014, Washington DC, USA. (Acceptance rate: 18.5%) [slides]
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Alekh Jindal, Praynaa Rawlani, Eugene Wu, Samuel Madden, Amol Deshpande, Mike Stonebraker
Vertexica: Your Relational Friend for Graph Analytics!
VLDB 2014, Hangzhou, China. (Demo paper)
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Felix Martin Schuhknecht, Alekh Jindal, Jens Dittrich
The Uncracked Pieces in Database Cracking
VLDB 2014/PVLDB, Hangzhou, China. [Source Code]
Best Paper Award
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Alekh Jindal, Endre Palatinus, Vladimir Pavlov, Jens Dittrich
A Comparison of Knives for Bread Slicing
VLDB 2013/PVLDB, Riva, Italy.
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Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Samuel Madden
Cartilage: Adding Flexibility to the Hadoop Skeleton
SIGMOD 2013, New York, USA. (Demo paper) [poster]
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Barzan Mozafari, Carlo Curino, Alekh Jindal, Samuel Madden
Performance and Resource Modeling in Highly-Concurrent OLTP Workloads
SIGMOD 2013, New York, USA.
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Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Jens Dittrich
WWHow! Freeing Data Storage from Cages
CIDR 2013, Asilomar, USA.
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Alekh Jindal, Felix Martin Schuhknecht, Jens Dittrich, Karen Khachatryan, Alexander Bunte
How Achaeans Would Construct Columns in Troy
CIDR 2013, Asilomar, USA. [slides]
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Jens Dittrich, Jorge-Arnulfo Quiané-Ruiz, Stefan Richter, Stefan Schuh, Alekh Jindal, Jörg Schad
Only Aggressive Elephants are Fast Elephants
VLDB 2012/PVLDB, Istanbul, Turkey.
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Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Jens Dittrich
Trojan Data Layouts: Right Shoes for a Running Elephant
ACM SOCC 2011, Cascais, Portugal. [slides] [poster]
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Alekh Jindal, Jens Dittrich
Relax and Let the Database do the Partitioning Online
VLDB BIRTE 2011, Seattle, USA. TR [slides]
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Jens Dittrich, Alekh Jindal
Towards a one-size-fits-all Database Architecture
CIDR 2011, Outrageous Ideas and Vision Track, Asilomar, USA.
Best Outrageous Ideas and Vision Paper Award (CCC Blog)
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Jens Dittrich, Jorge-Arnulfo Quiane-Ruiz, Alekh Jindal, Yagiz Kargin, Vinay Setty, and Jörg Schad.
Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing)
VLDB 2010, Singapore.
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Alekh Jindal
The Mimicking Octopus: Towards a one-size-fits-all Database Architecture
VLDB 2010 PhD Workshop, Singapore. [slides] [poster]
Patents
- Computation Reuse in Analytics Job Service (US20190318025A1).
- Learning Optimizer for Shared Cloud (US20190303475A1).
- Selection of Subexpressions to Materialize for Datacenter Scale (US20190236189A1).
- Replicated data storage system and methods (WO2013139379).
- A method for storing and accessing data in a database system (WO2012032184, US20130226959).
Professional Activities
- 2021: PC Member, PVLDB
- 2020: PC Member, ICDE VLDB(Demo)
- 2019: PC Member, SIGMOD ICDE EDBT SOCC CIKM VLDB(Demo)
- 2018: PC Member, CIKM DEEM DASFAA TKDE Poster
- 2017: PC Member, PVLDB SIGMOD ICDE EDBT VLDB(Demo) SIGMOD(SRC)
Reviewer, DAPD
- 2016: Proceedings Chair, SIGMOD
PC Member, SIGMOD SIGMOD(Demo) VLDB(Demo) ICDE(Demo) EDBT(Vision)
- 2015: PC Member, PVLDB SIGMOD EDBT(Demo)
Reviewer, SIGMOD Record TON TKDE TODS
- 2014: PC Member, PVLDB
Referee, SIGMOD Record
- 2013: Reviewer, PVLDB SIGMOD ICDE CIKM DAPD
- 2012: Reviewer, PVLDB ICDE
- 2011: Reviewer, EDBT
- 2010: Reviewer, VLDB
Short CV
Education
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April 2013 - August 2015:
Postdoctoral Associate, CSAIL, Massachusetts Institute of Technology, USA.
Focus: Big Data Analytics. Research Teaching
Mentor: Prof. Samuel Madden
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February 2010 - August 2012:
Ph.D. (Summa Cum Laude), Computer Science, Saarland University, Germany.
Thesis: OctopusDB:Flexible and Scalable Storage Management for Arbitrary Database Engines. PDF
Supervisor: Prof. Jens Dittrich
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October 2008 - January 2010:
Master of Science (honors), Computer Science, Saarland University & Max Plank Institute for Informatics, Germany.
Thesis: Quality in Phrase Mining. PDF
Supervisors: Prof. Jens Dittrich, Prof. Gerhard Weikum
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July 2002 - June 2006:
Bachelor of Technology, Electrical Engineering, Indian Institute of Technology, Kanpur, India.
Thesis: Microcontroller Based Power Distribution Monitoring & Control. PDF
Supervisor: Prof. S. P. Das
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