Efficient Continuous Multi-Query Processing over Graph Streams
Efficient Continuous Multi-Query Processing over Graph Streams
|
Yükleniyor...
 Hızlı erişim için Tubidy'yi favorilerinize ekleyin.
Lütfen bekleyiniz...
Type
Size

 İlgili Videolar

Efficient Continuous Multi-Query Processing over Graph Streams

Efficient Continuous Multi-Query Processing over Graph Streams

|
Incremental Stream Query Merging (EDBT-2023)

Incremental Stream Query Merging (EDBT-2023)

|
ICDE'20 Presentation-Interactive Cleaning for Progressive Visualization through Composite Questions

ICDE'20 Presentation-Interactive Cleaning for Progressive Visualization through Composite Questions

|
Weaving Enterprise Knowledge Graphs: The Case of Company Ownership Graphs

Weaving Enterprise Knowledge Graphs: The Case of Company Ownership Graphs

|
EDBT2020 - Improved Cardinality Estimation by Learning Queries Containment Rates

EDBT2020 - Improved Cardinality Estimation by Learning Queries Containment Rates

|
Knowledge Graphs: The Power of Graph-Based Search

Knowledge Graphs: The Power of Graph-Based Search

|
Tutorial Over-Graph - Respond Tool

Tutorial Over-Graph - Respond Tool

|
PIRL 2020: Transactional Graph Processing in Persistent Memory

PIRL 2020: Transactional Graph Processing in Persistent Memory

|
NODES 2023 - Advanced Pathfinding, Simple Queries, and Efficient Execution – Pick Three

NODES 2023 - Advanced Pathfinding, Simple Queries, and Efficient Execution – Pick Three

|
Q-Store: Distributed, Multi-partition Transactions... EDBT 2020

Q-Store: Distributed, Multi-partition Transactions... EDBT 2020

|
AStream: Ad-hoc Shared Stream Processing (SIGMOD 2019, Research paper)

AStream: Ad-hoc Shared Stream Processing (SIGMOD 2019, Research paper)

|
ICDE 2020 Talk: Turbine: Facebook’s Service Management Platform for Stream Processing

ICDE 2020 Talk: Turbine: Facebook’s Service Management Platform for Stream Processing

|
[SIGMOD 2021] Instance-Optimized Data Layouts for Cloud Analytics Workloads

[SIGMOD 2021] Instance-Optimized Data Layouts for Cloud Analytics Workloads

|
Unified stream and batch processing with Apache Flink’s relational APIs - Fabian Hueske

Unified stream and batch processing with Apache Flink’s relational APIs - Fabian Hueske

|
High Speed Continuous & Reliable Data Ingest into Hadoop

High Speed Continuous & Reliable Data Ingest into Hadoop

|
Seongyun Ko, POSTECH, TurboGraph++: A Scalable and Fast Graph Analytics System (20m)

Seongyun Ko, POSTECH, TurboGraph++: A Scalable and Fast Graph Analytics System (20m)

|
Digital Business Transformation in Data Streaming Era

Digital Business Transformation in Data Streaming Era

|
Disco: Efficient Distributed Window Aggregation - Lawrence Benson @ EDBT 2020 - BIFOLD Berlin

Disco: Efficient Distributed Window Aggregation - Lawrence Benson @ EDBT 2020 - BIFOLD Berlin

|
Query Planning for Continuous Aggregation Queries over a Network of Data Aggregators

Query Planning for Continuous Aggregation Queries over a Network of Data Aggregators

|
Modernize through database consolidation

Modernize through database consolidation

|
Copyright. All rights reserved © 2025
Rosebank, Johannesburg, South Africa

Favorilere Ekle