273 citations · 547 across the 8 of their papers we have counts for
8 papers
APEX: A High-Performance Learned Index on Persistent Memory
Baotong Lu, Jialin Ding, Eric Lo +2
The recently released persistent memory (PM) offers high performance, persistence, and is cheaper than DRAM. This opens up new possibilities for indexes that operate and persist da…
Cortex: Harnessing Correlations to Boost Query Performance
Vikram Nathan, Jialin Ding, Tim Kraska +1
Databases employ indexes to filter out irrelevant records, which reduces scan overhead and speeds up query execution. However, this optimization is only available to queries that f…
The Case for Learned Spatial Indexes
Varun Pandey, Alexander van Renen, Andreas Kipf +3
Spatial data is ubiquitous. Massive amounts of data are generated every day from billions of GPS-enabled devices such as cell phones, cars, sensors, and various consumer-based appl…
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads
Jialin Ding, Vikram Nathan, Mohammad Alizadeh +1
Filtering data based on predicates is one of the most fundamental operations for any modern data warehouse. Techniques to accelerate the execution of filter expressions include clu…
Learning Multi-dimensional Indexes
Vikram Nathan, Jialin Ding, Mohammad Alizadeh +1
Scanning and filtering over multi-dimensional tables are key operations in modern analytical database engines. To optimize the performance of these operations, databases often crea…
LISA: Towards Learned DNA Sequence Search
Darryl Ho, Jialin Ding, Sanchit Misra +4
Next-generation sequencing (NGS) technologies have enabled affordable sequencing of billions of short DNA fragments at high throughput, paving the way for population-scale genomics…
ALEX: An Updatable Adaptive Learned Index
Jialin Ding, Umar Farooq Minhas, Jia Yu +9
Recent work on "learned indexes" has changed the way we look at the decades-old field of DBMS indexing. The key idea is that indexes can be thought of as "models" that predict the…
Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries
Edward Gan, Jialin Ding, Kai Sheng Tai +2
Interactive analytics increasingly involves querying for quantiles over sub-populations of high cardinality datasets. Data processing engines such as Druid and Spark use mergeable…