Alekh Jindal

Orcid: 0000-0001-8844-8165

Affiliations:
  • SmartApps, USA
  • Microsoft (former)


According to our database1, Alekh Jindal authored at least 62 papers between 2010 and 2024.

Collaborative distances:

Timeline

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Bibliography

2024
Sibyl: Forecasting Time-Evolving Query Workloads.
Proc. ACM Manag. Data, February, 2024

Turning Databases Into Generative AI Machines.
Proceedings of the 14th Conference on Innovative Data Systems Research, 2024

2023
GEqO: ML-Accelerated Semantic Equivalence Detection.
Proc. ACM Manag. Data, December, 2023

Diversity, Equity and Inclusion Activities in Database Conferences: A 2022 Report.
SIGMOD Rec., June, 2023

Front Matter.
Proc. VLDB Endow., 2023

PikePlace: Generating Intelligence for Marketplace Datasets.
Proc. VLDB Endow., 2023

Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning.
Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

Predictive Price-Performance Optimization for Serverless Query Processing.
Proceedings of the Proceedings 26th International Conference on Extending Database Technology, 2023

2022
Query Optimizer as a Service: An Idea Whose Time Has Come!
SIGMOD Rec., 2022

Diversity and Inclusion Activities in Database Conferences: A 2021 Report.
SIGMOD Rec., 2022

Pipemizer: An Optimizer for Analytics Data Pipelines.
Proc. VLDB Endow., 2022

Deploying a Steered Query Optimizer in Production at Microsoft.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Towards Optimal Resource Allocation for Big Data Analytics.
Proceedings of the 25th International Conference on Extending Database Technology, 2022

2021
Phoebe: A Learning-based Checkpoint Optimizer.
Proc. VLDB Endow., 2021

AutoExecutor: Predictive Parallelism for Spark SQL Queries.
Proc. VLDB Endow., 2021

SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft.
Proc. VLDB Endow., 2021

The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward.
Proc. VLDB Endow., 2021

Machine Learning for Cloud Data Systems: the Promise, the Progress, and the Path Forward.
Proc. VLDB Endow., 2021

PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost!
Proc. VLDB Endow., 2021

Optimal Resource Allocation for Serverless Queries.
CoRR, 2021

Steering Query Optimizers: A Practical Take on Big Data Workloads.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Production Experiences from Computation Reuse at Microsoft.
Proceedings of the 24th International Conference on Extending Database Technology, 2021

Magpie: Python at Speed and Scale using Cloud Backends.
Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

2020
Applied Research Lessons from CloudViews Project.
SIGMOD Rec., 2020

AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft.
Proc. VLDB Endow., 2020

Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation.
Proc. VLDB Endow., 2020

Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings.
Proceedings of the 2020 International Conference on Management of Data, 2020

Towards Plan-aware Resource Allocation in Serverless Query Processing.
Proceedings of the 12th USENIX Workshop on Hot Topics in Cloud Computing, 2020


2019
Robust Data Partitioning.
Proceedings of the Encyclopedia of Big Data Technologies., 2019

SparkCruise: Handsfree Computation Reuse in Spark.
Proc. VLDB Endow., 2019

Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems.
CoRR, 2019

Big Data Processing at Microsoft: Hyper Scale, Massive Complexity, and Minimal Cost.
Proceedings of the ACM Symposium on Cloud Computing, SoCC 2019, 2019

Peregrine: Workload Optimization for Cloud Query Engines.
Proceedings of the ACM Symposium on Cloud Computing, SoCC 2019, 2019

2018
Towards a Learning Optimizer for Shared Clouds.
Proc. VLDB Endow., 2018

Selecting Subexpressions to Materialize at Datacenter Scale.
Proc. VLDB Endow., 2018

Computation Reuse in Analytics Job Service at Microsoft.
Proceedings of the 2018 International Conference on Management of Data, 2018

Query and Resource Optimization: Bridging the Gap.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017
AdaptDB: Adaptive Partitioning for Distributed Joins.
Proc. VLDB Endow., 2017

INGESTBASE: A Declarative Data Ingestion System.
CoRR, 2017

A robust partitioning scheme for ad-hoc query workloads.
Proceedings of the 2017 Symposium on Cloud Computing, SoCC 2017, Santa Clara, CA, USA, 2017

2016
An experimental evaluation and analysis of database cracking.
VLDB J., 2016

Amoeba: A Shape changing Storage System for Big Data.
Proc. VLDB Endow., 2016

GraphFrames: an integrated API for mixing graph and relational queries.
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems, Redwood Shores, CA, USA, June 24, 2016

2015
BigDansing: A System for Big Data Cleansing.
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31, 2015

Robust Data Transformations.
Proceedings of the Seventh Biennial Conference on Innovative Data Systems Research, 2015

Graph analytics using vertica relational database.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
VERTEXICA: Your Relational Friend for Graph Analytics!
Proc. VLDB Endow., 2014

GRAPHiQL: A graph intuitive query language for relational databases.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013
The Uncracked Pieces in Database Cracking.
Proc. VLDB Endow., 2013

A Comparison of Knives for Bread Slicing.
Proc. VLDB Endow., 2013

Performance and resource modeling in highly-concurrent OLTP workloads.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

CARTILAGE: adding flexibility to the Hadoop skeleton.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

How Achaeans Would Construct Columns in Troy.
Proceedings of the Sixth Biennial Conference on Innovative Data Systems Research, 2013

WWHow! Freeing Data Storage from Cages.
Proceedings of the Sixth Biennial Conference on Innovative Data Systems Research, 2013

2012
OctopusDB : flexible and scalable storage management for arbitrary database engines.
PhD thesis, 2012

Only Aggressive Elephants are Fast Elephants.
Proc. VLDB Endow., 2012

2011
Trojan data layouts: right shoes for a running elephant.
Proceedings of the ACM Symposium on Cloud Computing in conjunction with SOSP 2011, 2011

Towards a One Size Fits All Database Architecture.
Proceedings of the Fifth Biennial Conference on Innovative Data Systems Research, 2011

Relax and Let the Database Do the Partitioning Online.
Proceedings of the Enabling Real-Time Business Intelligence - 5th International Workshop, 2011

2010
Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing).
Proc. VLDB Endow., 2010


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