[go: up one dir, main page]

Knorr et al., 2022 - Google Patents

Proteus: A self-designing range filter

Knorr et al., 2022

View PDF
Document ID
10942280574180314271
Author
Knorr E
Lemaire B
Lim A
Luo S
Zhang H
Idreos S
Mitzenmacher M
Publication year
Publication venue
Proceedings of the 2022 International Conference on Management of Data

External Links

Snippet

We introduce Proteus, a novel self-designing approximate range filter, which configures itself based on sampled data in order to optimize its false positive rate (FPR) for a given space requirement. Proteus unifies the probabilistic and deterministic design spaces of state …
Continue reading at dl.acm.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386Retrieval requests
    • G06F17/30424Query processing
    • G06F17/30533Other types of queries
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386Retrieval requests
    • G06F17/30424Query processing
    • G06F17/30477Query execution
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386Retrieval requests
    • G06F17/30424Query processing
    • G06F17/30442Query optimisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30312Storage and indexing structures; Management thereof
    • G06F17/30321Indexing structures
    • G06F17/3033Hash tables
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30289Database design, administration or maintenance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587Details of specialised database models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30067File systems; File servers
    • G06F17/30129Details of further file system functionalities
    • G06F17/30144Details of monitoring file system events, e.g. by the use of hooks, filter drivers, logs
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30067File systems; File servers
    • G06F17/30091File storage and access structures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30943Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
    • G06F17/30946Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type indexing structures
    • G06F17/30958Graphs; Linked lists
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F12/00Accessing, addressing or allocating within memory systems or architectures
    • G06F12/02Addressing or allocation; Relocation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60Protecting data
    • G06F21/62Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled

Similar Documents

Publication Publication Date Title
Knorr et al. Proteus: A self-designing range filter
Li et al. FINEdex: a fine-grained learned index scheme for scalable and concurrent memory systems
Galakatos et al. Fiting-tree: A data-aware index structure
Zhang et al. Surf: Practical range query filtering with fast succinct tries
Kraska et al. The case for learned index structures
Bonomi et al. A two-phase algorithm for mining sequential patterns with differential privacy
Olma et al. Adaptive partitioning and indexing for in situ query processing
Zhang et al. SPRIG: A learned spatial index for range and kNN queries
Sabek et al. Can learned models replace hash functions?
KR20160011212A (en) Managing memory and storage space for a data operation
Anneser et al. Adaptive hybrid indexes
Wang et al. Rencoder: A space-time efficient range filter with local encoder
Alewiwi et al. Efficient top-k similarity document search utilizing distributed file systems and cosine similarity
Aluç et al. Building self-clustering RDF databases using Tunable-LSH
Zhang et al. Succinct range filters
Zhang et al. Hyper: A high-performance and memory-efficient learned index via hybrid construction
Sahli et al. ACME: A scalable parallel system for extracting frequent patterns from a very long sequence
Pandey et al. Beyond Bloom: A Tutorial on Future Feature-Rich Filters
Mao et al. Comparison and evaluation of state-of-the-art LSM merge policies
Firth et al. TAPER: query-aware, partition-enhancement for large, heterogenous graphs
Wang et al. Wormhole filters: Caching your hash on persistent memory
Zhu et al. NOCAP: Near-Optimal Correlation-Aware Partitioning Joins
Fan et al. Enabling space-time efficient range queries with REncoder
Zhu et al. Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees
Zhou et al. SLIPP: a space-efficient learned index for string keys