Applied Research Lessons from CloudViews Project
Alekh Jindal
Sigmod Record | December 2020, Vol 49(3): pp. 37-42
Publications
Publications
Publications by Year
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AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
Towards Plan-aware Resource Allocation in Serverless Query Processing
Malay Bag, Alekh Jindal, Hiren Patel
USENIX conference on Hot Topics in Cloud Ccomputing | July 2020
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 2020
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Peregrine: Workload Optimization for Cloud Query Engines
Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
Symposium on Cloud Computing | November 2019
SparkCruise: handsfree computation reuse in Spark
Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
Very Large Data Bases | July 2019
Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
MSR-TR-2019-44 | June 2019
Published by Microsoft
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Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018
Publications by Research Area
-
Applied Research Lessons from CloudViews Project
Alekh Jindal
Sigmod Record | December 2020, Vol 49(3): pp. 37-42
AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
Towards Plan-aware Resource Allocation in Serverless Query Processing
Malay Bag, Alekh Jindal, Hiren Patel
USENIX conference on Hot Topics in Cloud Ccomputing | July 2020
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 2020
Peregrine: Workload Optimization for Cloud Query Engines
Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
Symposium on Cloud Computing | November 2019
SparkCruise: handsfree computation reuse in Spark
Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
Very Large Data Bases | July 2019
Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
MSR-TR-2019-44 | June 2019
Published by Microsoft
Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018
-
AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
Peregrine: Workload Optimization for Cloud Query Engines
Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
Symposium on Cloud Computing | November 2019
Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
-
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 2020
Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018
Publications by Type
-
Applied Research Lessons from CloudViews Project
Alekh Jindal
Sigmod Record | December 2020, Vol 49(3): pp. 37-42
-
Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
MSR-TR-2019-44 | June 2019
Published by Microsoft
-
AutoToken: predicting peak parallelism for big data analytics at Microsoft
Rathijit Sen, Alekh Jindal, Hiren Patel, Shi Qiao
Very Large Data Bases | July 2020
Towards Plan-aware Resource Allocation in Serverless Query Processing
Malay Bag, Alekh Jindal, Hiren Patel
USENIX conference on Hot Topics in Cloud Ccomputing | July 2020
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao le
SIGMOD 2020: International Conference on Management of Data | February 2020
Peregrine: Workload Optimization for Cloud Query Engines
Alekh Jindal, Hiren Patel, Abhishek Roy, Shi Qiao, Zhicheng Yin, Rathijit Sen, Subru Krishnan
Symposium on Cloud Computing | November 2019
SparkCruise: handsfree computation reuse in Spark
Abhishek Roy, Alekh Jindal, Hiren Patel, Ashit Gosalia, Subru Krishnan, Carlo Curino
Very Large Data Bases | July 2019
Towards a learning optimizer for shared clouds
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Very Large Data Bases | October 2018
Computation Reuse in Analytics Job Service at Microsoft
Alekh Jindal, Shi Qiao, Hiren Patel, Zhicheng Yin, Jieming Di, Malay Bag, Marc Friedman, Yifung Lin, Konstantinos Karanasos, Sriram Rao
2018 International Conference on Management of Data | May 2018
Query and Resource Optimization: Bridging the Gap
Lalitha Viswanathan, Alekh Jindal, Konstantinos Karanasos
International Conference on Data Engineering (ICDE) | April 2018
Selecting subexpressions to materialize at datacenter scale
Alekh Jindal, Konstantinos Karanasos, Sriram Rao, Hiren Patel
Very Large Data Bases (VLDB) | February 2018