Log scale of N

1
Log scale of N Log scale of N a b a b

description

Log scale of N. Log scale of N. a b. a b. - PowerPoint PPT Presentation

Transcript of Log scale of N

Page 1: Log scale of N

Log

sca

le o

f N

Log

sca

le o

f N

a b a b

Analysis of Long Queries in a Large Scale Search Log

Analysis of Long Queries in a Large Scale Search Log

Implementation of a O nα n log n)) Point Visibility ...

Implementation of a O nα n log n)) Point Visibility ...

Large scale near real-time log indexing with Flume and SolrCloud

Large scale near real-time log indexing with Flume and SolrCloud

Visualizing data · y = b + mx. Log-log plots 10 100 1000 10000 1 100 10000 1000000 100000000 10000000000 1000000000000 100000000000000 Three functions on a log-log scale Linear Squared

Visualizing data · y = b + mx. Log-log plots 10 100 1000 10000 1 100 10000 1000000 100000000 10000000000 1000000000000 100000000000000 Three functions on a log-log scale Linear Squared

Large Scale Log Analytics with Solr (from Lucene Revolution 2015)

Large Scale Log Analytics with Solr (from Lucene Revolution 2015)

Tufts University ECE and CS Departmentsaloupis/comp160/class... · 2. log. 4/3. n ~= 2 . 2.4. 2. log < 5 n. n * log. Created Date: 3/5/2018 4:25:47 AM

Tufts University ECE and CS Departmentsaloupis/comp160/class... · 2. log. 4/3. n ~= 2 . 2.4. 2. log < 5 n. n * log. Created Date: 3/5/2018 4:25:47 AM

Solving Recurrence Relations T(n)= 2T(n/2)+n = 2*(2T(n/4)+n/2)+n = 4*T(n/4) +2*n = 8*T(n/8) + 3*n = 2 (log n) * T(1) + (log n) * n = n * 1 + n log n O(n.

Solving Recurrence Relations T(n)= 2T(n/2)+n = 2*(2T(n/4)+n/2)+n = 4*T(n/4) +2*n = 8*T(n/8) + 3*n = 2 (log n) * T(1) + (log n) * n = n * 1 + n log n O(n.

CSC 213 – Large Scale Programming Lecture 18: Zen & the Art of O (log n ) Search.

CSC 213 – Large Scale Programming Lecture 18: Zen & the Art of O (log n ) Search.

R. W. Ericksonecen5797/course_material/... · 2018-10-19 · 20 log 10 f f 0 n 20n log 10 f f 0 f f 0 – 2 f f 0 2 0dB –20dB –40dB –60dB 20dB 40dB 60dB f log scale 0.1f f 0

R. W. Ericksonecen5797/course_material/... · 2018-10-19 · 20 log 10 f f 0 n 20n log 10 f f 0 f f 0 – 2 f f 0 2 0dB –20dB –40dB –60dB 20dB 40dB 60dB f log scale 0.1f f 0

Sorting Algorithms - Freeabdulrab.free.fr/CoursHA/SortingAlgorithmes.pdf · Algorithms with complexities like O(1), O(n), O(Log n), O(n Log n) are usually used. Algorithms with complexities

Sorting Algorithms - Freeabdulrab.free.fr/CoursHA/SortingAlgorithmes.pdf · Algorithms with complexities like O(1), O(n), O(Log n), O(n Log n) are usually used. Algorithms with complexities

Fluent Bit: Log Forwarding at Scale

Fluent Bit: Log Forwarding at Scale

Data Structuresgiri/teach/3530/f16/Lectures/...2004/03/11  · Time Complexity = O(n log n + m + m log n) = O(m log n) COP 3530: DATA STRUCTURES 10/12/16 Kruskal’s Algorithm 11/17/2016

Data Structuresgiri/teach/3530/f16/Lectures/...2004/03/11  · Time Complexity = O(n log n + m + m log n) = O(m log n) COP 3530: DATA STRUCTURES 10/12/16 Kruskal’s Algorithm 11/17/2016

An n log n Algorithm for Online BDD Refinement

An n log n Algorithm for Online BDD Refinement

An optimal O(log log n) time parallel string matching ...

An optimal O(log log n) time parallel string matching ...

Updated from: Algorithms in Java, Chapter 2 Intro to … · 2008-02-06 · Running Linux on Sun-Fire-X4100 14 Log-log plot. Plot running time vs. input size N on log-log scale . Regression.

Updated from: Algorithms in Java, Chapter 2 Intro to … · 2008-02-06 · Running Linux on Sun-Fire-X4100 14 Log-log plot. Plot running time vs. input size N on log-log scale . Regression.

distance, m (log scale)

distance, m (log scale)

Large scale Click-streaming and tranaction log mining

Large scale Click-streaming and tranaction log mining

An O(n log n) Cutting Plane Algorithm for Structured ...

An O(n log n) Cutting Plane Algorithm for Structured ...

Integer multiplication in time O(n log n)

Integer multiplication in time O(n log n)

Properties of Logarithms log b (MN)= log b M + log b N Ex: log 4 (15)= log 4 5 + log 4 3 log b (M/N)= log b M – log b N Ex: log 3 (50/2)= log 3 50 – log.

Properties of Logarithms log b (MN)= log b M + log b N Ex: log 4 (15)= log 4 5 + log 4 3 log b (M/N)= log b M – log b N Ex: log 3 (50/2)= log 3 50 – log.