21 citations · 95 across the 21 of their papers we have counts for
22 papers
Guided Table Retrieval for Structured Data Search
Alekh Jindal, Jyoti Pandey, Christina Pavlopoulou +5
Answering natural language questions over structured databases requires identifying the relevant tables and determining how to join them---a task that demands both schema knowledge…
Reverse Migration of Cloud Applications to On-premises
Alekh Jindal, Jyoti Pandey, Christina Pavlopoulou +5
Cloud has become ubiquitous to modern applications due to its agility and scalability. However, regulated industries still prefer to deploy on-premises due to security and complian…
Generating Query Context for Relational Databases
Alekh Jindal, Jyoti Pandey, Christina Pavlopoulou +5
Relational databases are the systems of record for business applications, and there is growing demand to query them through natural language interfaces. A key challenge is that AI…
Tursio Database Search: How far are we from ChatGPT?
Sulbha Jain, Shivani Tripathi, Shi Qiao +1
Business users need to search enterprise databases using natural language, just as they now search the web using ChatGPT or Perplexity. However, existing benchmarks -- designed for…
Tursio for Credit Unions: Structured Data Search with Automated Context Graphs
Shivani Tripathi, Ravi Shetye, Shi Qiao +1
Extracting actionable insights from structured databases in regulated industries, such as credit unions, is often hindered by complex schemas, legacy systems, and stringent data go…
Scalable Join Inference for Large Context Graphs
Shivani Tripathi, Ravi Shetye, Shi Qiao +1
Context graphs are essential for modern AI applications including question answering, pattern discovery, and data analysis. Building accurate context graphs from structured databas…
Making Databases Searchable with Deep Context
Alekh Jindal, Shi Qiao, Shivani Tripathi +15
Databases are the most critical assets for enterprises, and yet they remain largely inaccessible to people who make the most important decisions. In this paper, we describe the Tur…
Prompt Migration: Stabilizing GenAI Applications with Evolving Large Language Models
Shivani Tripathi, Pushpanjali Nema, Aditya Halder +2
Generative AI is transforming business applications by enabling natural language interfaces and intelligent automation. However, the underlying large language models (LLMs) are evo…
Searching Clinical Data Using Generative AI
Karan Hanswadkar, Anika Kanchi, Shivani Tripathi +3
Artificial Intelligence (AI) is making a major impact on healthcare, particularly through its application in natural language processing (NLP) and predictive analytics. The healthc…
Sibyl: Forecasting Time-Evolving Query Workloads
Hanxian Huang, Tarique Siddiqui, Rana Alotaibi +6
Database systems often rely on historical query traces to perform workload-based performance tuning. However, real production workloads are time-evolving, making historical queries…
GEqO: ML-Accelerated Semantic Equivalence Detection
Brandon Haynes, Rana Alotaibi, Anna Pavlenko +3
Large scale analytics engines have become a core dependency for modern data-driven enterprises to derive business insights and drive actions. These engines support a large number o…
Deploying a Steered Query Optimizer in Production at Microsoft
Wangda Zhang, Matteo Interlandi, Paul Mineiro +6
Modern analytical workloads are highly heterogeneous and massively complex, making generic query optimizers untenable for many customers and scenarios. As a result, it is important…
Predictive Price-Performance Optimization for Serverless Query Processing
Rathijit Sen, Abhishek Roy, Alekh Jindal
We present an efficient, parametric modeling framework for predictive resource allocations, focusing on the amount of computational resources, that can optimize for a range of pric…
Phoebe: A Learning-based Checkpoint Optimizer
Yiwen Zhu, Matteo Interlandi, Abhishek Roy +5
Easy-to-use programming interfaces paired with cloud-scale processing engines have enabled big data system users to author arbitrarily complex analytical jobs over massive volumes…
Optimal Resource Allocation for Serverless Queries
Anish Pimpley, Shuo Li, Anubha Srivastava +7
Optimizing resource allocation for analytical workloads is vital for reducing costs of cloud-data services. At the same time, it is incredibly hard for users to allocate resources…
Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation
Olga Poppe, Tayo Amuneke, Dalitso Banda +23
Microsoft Azure is dedicated to guarantee high quality of service to its customers, in particular, during periods of high customer activity, while controlling cost. We employ a Dat…
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings
Tarique Siddiqui, Alekh Jindal, Shi Qiao +2
Query processing over big data is ubiquitous in modern clouds, where the system takes care of picking both the physical query execution plans and the resources needed to run those…
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
Ashvin Agrawal, Rony Chatterjee, Carlo Curino +19
Machine learning (ML) has proven itself in high-value web applications such as search ranking and is emerging as a powerful tool in a much broader range of enterprise scenarios inc…
Query and Resource Optimizations: A Case for Breaking the Wall in Big Data Systems
Alekh Jindal, Lalitha Viswanathan, Konstantinos Karanasos
Modern big data systems run on cloud environments where resources are shared amongst several users and applications. As a result, declarative user queries in these environments nee…
INGESTBASE: A Declarative Data Ingestion System
Alekh Jindal, Jorge-Arnulfo Quiane-Ruiz, Samuel Madden
Big data applications have fast arriving data that must be quickly ingested. At the same time, they have specific needs to preprocess and transform the data before it could be put…
Graph Analytics using the Vertica Relational Database
Alekh Jindal, Samuel Madden, Malu Castellanos +1
Graph analytics is becoming increasingly popular, with a deluge of new systems for graph analytics having been proposed in the past few years. These systems often start from the as…
Only Aggressive Elephants are Fast Elephants
Jens Dittrich, Jorge-Arnulfo Quiané-Ruiz, Stefan Richter +3
Yellow elephants are slow. A major reason is that they consume their inputs entirely before responding to an elephant rider's orders. Some clever riders have trained their yellow e…