What is he best known for?
The fields of study he is best known for:
- Database
- Operating system
- Programming language
His primary scientific interests are in Database, Data mining, Workload, SQL and Database design.
Many of his studies on Database involve topics that are commonly interrelated, such as Set.
His Data mining research includes elements of Sampling, Reverse index and Database index.
His Workload study incorporates themes from Database server, Index selection, Decision support system, Optimization problem and Data structure.
His SQL research focuses on Relational database management system and how it relates to Performance tuning, Backup and Distributed computing.
His work in Database design covers topics such as Database administrator which are related to areas like Physical data model.
His most cited work include:
- An overview of business intelligence technology (601 citations)
- Automated Selection of Materialized Views and Indexes in SQL Databases (560 citations)
- Integrating vertical and horizontal partitioning into automated physical database design (376 citations)
What are the main themes of his work throughout his whole career to date?
Vivek Narasayya mainly focuses on Database, Data mining, Workload, Set and Query optimization.
His study in Database concentrates on Database server, SQL, Database design, Relational database and Database tuning.
His research integrates issues of Scalability and Database administrator in his study of Database design.
His Data mining research incorporates themes from Sampling, Reverse index, Information retrieval and Sample.
As a member of one scientific family, he mostly works in the field of Set, focusing on Index and, on occasion, Wizard.
The concepts of his Query optimization study are interwoven with issues in Query plan, Online aggregation, Sargable and Theoretical computer science.
He most often published in these fields:
- Database (44.19%)
- Data mining (39.53%)
- Workload (22.67%)
What were the highlights of his more recent work (between 2018-2021)?
- Database (44.19%)
- Set (20.35%)
- Query optimization (20.35%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Database, Set, Query optimization, Search engine indexing and Data mining.
Vivek Narasayya studies Column which is a part of Database.
The Set study which covers Index that intersects with Query plan, Ranking, Information retrieval and Cost efficiency.
His research investigates the link between Query optimization and topics such as Joins that cross with problems in Bloom filter.
Vivek Narasayya combines subjects such as Performance tuning, Fuzzy logic and Join with his study of Search engine indexing.
His Data mining research focuses on Memory footprint and how it connects with Range.
Between 2018 and 2021, his most popular works were:
- Selectivity estimation for range predicates using lightweight models (36 citations)
- AI Meets AI: Leveraging Query Executions to Improve Index Recommendations (26 citations)
- Automatically Indexing Millions of Databases in Microsoft Azure SQL Database (14 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Database
- Programming language
Vivek Narasayya mostly deals with Data mining, Performance tuning, Search engine indexing, Set and Extensibility.
His work in the fields of Data mining, such as Query optimization, overlaps with other areas such as Estimation.
His work carried out in the field of Performance tuning brings together such families of science as Relational database, Service, Database and Index.
He undertakes multidisciplinary studies into Search engine indexing and Process in his work.
His Extensibility study often links to related topics such as Graphical user interface.
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