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M Tuples published presentations and documents on DocSlides.

Python - Tuples Tuples are like

Python - Tuples Tuples are like

  • yoshiko-marsland
  • 0 Slides

. lists. -- Tuples are . another kind . of seque...

Representing and Querying Correlated Tuples in Probabilisti

Representing and Querying Correlated Tuples in Probabilisti

  • trish-goza
  • 33 Slides

Prithviraj Sen Amol Deshpande. outline. General I...

Lecture 11 Tuples Bryan Burlingame

Lecture 11 Tuples Bryan Burlingame

  • calandra-battersby
  • 0 Slides

Halloween 2018. Announcements. Homework 8 due up ...

Two-Pass Algorithms

Two-Pass Algorithms

  • pamella-moone
  • 15 Slides

Based on Sorting. SECTION 15.4. Rupinder. Singh...

SABRE: a Sensitive Attribute Bucketization and

SABRE: a Sensitive Attribute Bucketization and

  • alida-meadow
  • 28 Slides

REdistribution. framework for t-closeness. Autho...

CS240B Midterm Spring 2013

CS240B Midterm Spring 2013

  • marina-yarberry
  • 11 Slides

. Your Name:. and your ID:. Problem. . Max....

Chapter 5

Chapter 5

  • luanne-stotts
  • 46 Slides

Notes. P. 189: Sets, Bags, and Lists . To underst...

Harikrishnan Karunakaran

Harikrishnan Karunakaran

  • pamella-moone
  • 31 Slides

Sulabha Balan. ICICLES: Self-tuning Samples for ...

Continuous Processing

Continuous Processing

  • debby-jeon
  • 59 Slides

of . Preference Queries . in . Data Streams : a S...

Monitoring streams:

Monitoring streams:

  • briana-ranney
  • 48 Slides

a new class of data management applications. Don ...

Query Processing, Resource Management, and Approximation

Query Processing, Resource Management, and Approximation

  • min-jolicoeur
  • 21 Slides

in a Data Stream Management . System. Introductio...

Presented BY: Jason Chee

Presented BY: Jason Chee

  • mitsue-stanley
  • 12 Slides

15.1 . –. Introduction to physical-Query-plan ...

Classification Shailaja K.P

Classification Shailaja K.P

  • madison
  • 72 Slides

Introduction. Classification is a form of data ana...

By: Frederikos Leandrou

By: Frederikos Leandrou

  • winnie
  • 19 Slides

https://www.cs.ucy.ac.cy/courses/EPL646. 1. EPL646...

CS61A Lecture 8

CS61A Lecture 8

  • test
  • 28 Slides

Data Abstraction. Tom Magrino and Jon Kotker. UC ...

An Overview of Data Provenance

An Overview of Data Provenance

  • calandra-battersby
  • 50 Slides

Why – How . – . Where. What’s up with this ...

What is it? What kind of system need it?

What is it? What kind of system need it?

  • alexa-scheidler
  • 32 Slides

Elasticity. Computing resource or storag...

Query Processing

Query Processing

  • tawny-fly
  • 24 Slides

A query is stated using SQL or other languages, i...

Deco Query Processing

Deco Query Processing

  • phoebe-click
  • 16 Slides

Hector Garcia-Molina, Aditya Parameswaran, Hyunju...

Query Optimization

Query Optimization

  • lindy-dunigan
  • 54 Slides

Query Optimization Process. (simplified a bit). P...

6.830 Lecture 7

6.830 Lecture 7

  • faustina-dinatale
  • 40 Slides

B+Trees. & Column Stores. 9/30/2015. Signup:...

Ripple Joins for Online Aggregation

Ripple Joins for Online Aggregation

  • tatiana-dople
  • 42 Slides

By:. Peter J. Haas and Joseph M. . Hellerstein....

Implementation of relational operations

Implementation of relational operations

  • natalia-silvester
  • 47 Slides

(based on slides from UC Berkeley). Join Operator...

Database Systems

Database Systems

  • briana-ranney
  • 53 Slides

Basic SQL. Database Design -- Basic SQL. 1. Chapt...

Fine-grained Partitioning for Aggressive Data Skipping

Fine-grained Partitioning for Aggressive Data Skipping

  • celsa-spraggs
  • 28 Slides

Liwen. Sun, Michael J. Franklin, Sanjay Krishnan...

of Diophantine Quadruples

of Diophantine Quadruples

  • kittie-lecroy
  • 100 Slides

Adjugat es Philip Gibbs Diophantine m - tuples wi...

1 Large-Scale Machine Learning at Twitter

1 Large-Scale Machine Learning at Twitter

  • pamella-moone
  • 44 Slides

Jimmy Lin and Alek . Kolcz. Twitter, Inc.. Presen...

Making Time-stepped Applications

Making Time-stepped Applications

  • ellena-manuel
  • 43 Slides

Tick in . the . Cloud. Tao Zou. , Guozhang Wang, ...

UpSizeR

UpSizeR

  • alida-meadow
  • 21 Slides

Synthetically Scaling up . A Given Database State...

Processing Theta-Joins using

Processing Theta-Joins using

  • karlyn-bohler
  • 20 Slides

MapReduce. Authors: . Okcan. , . Riedewald. SIGMO...

Evaluating Window Joins over Unbounded Streams

Evaluating Window Joins over Unbounded Streams

  • min-jolicoeur
  • 49 Slides

Author: Jaewoo Kang, Jeffrey F. Naughton, Stratis...

Introducing Python

Introducing Python

  • tatiana-dople
  • 23 Slides

CS 4320, Spring 2015. Resources. We will be follo...

Real-time and Long-time with Storm and Hadoop

Real-time and Long-time with Storm and Hadoop

  • tatyana-admore
  • 47 Slides

Real-time and Long-time with Storm and . Hadoop. ...

The Complexity of Causality and Responsibility

The Complexity of Causality and Responsibility

  • danika-pritchard
  • 22 Slides

f. or Query Answers and non-Answers. Alexandra Me...

CS 440

CS 440

  • stefany-barnette
  • 47 Slides

Database Management Systems. Lecture 2 : Review o...

CS61A Lecture 11

CS61A Lecture 11

  • lindy-dunigan
  • 37 Slides

Immutable Trees. Jom. . Magrotker. UC Berkeley E...

Top-K Query Evaluation on Probabilistic Data

Top-K Query Evaluation on Probabilistic Data

  • lois-ondreau
  • 39 Slides

Christopher . Ré. , . Nilesh. . Dalvi. and Dan...

Relational Join

Relational Join

  • briana-ranney
  • 16 Slides

Advanced Data Structures. Equality Joins With One...

A Constraint Satisfaction Problem (CSP) is a combinatorial

A Constraint Satisfaction Problem (CSP) is a combinatorial

  • tatyana-admore
  • 4 Slides

by a . set of . variables. {A,B,C,…}, a set . ...

ICICLES: Self-tuning Samples for Approximate Query Answerin

ICICLES: Self-tuning Samples for Approximate Query Answerin

  • tatiana-dople
  • 27 Slides

By Venkatesh Ganti, Mong Li Lee, and Raghu Ramakr...

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