Similar documents
DB2 SQL for the 21 st Century: Overlooked Enhancements. David Simpson

Lab 15: EXL3 Microsoft Excel s AutoFill Tool, Multiple Worksheets, Charts and Conditional Formatting

Introduction to tablebase and tablebase Family. William Weber. Market Experts Distribution, SL

<Insert Picture Here> Using ERPi for EBS/FDM Data Loads into HFM

A Memory-Efficient Method for Fast Computation of Short 15-Puzzle Solutions

Compressing Pattern Databases

Principles of Ad Hoc Networking

Place value disks activity: learn addition and subtraction with large numbers

MonetDB & R. amst-r-dam meet-up, Hannes Mühleisen

Census Data and UK Data Service Census Support.

Organized Play Database. Anders Lykkehoy

Previous Lecture. How can computation sort data faster for you? Sorting Algorithms: Speed Comparison. Recursive Algorithms 10/31/11

CSC 343 Inverted course material: SQL subqueries

Increasing Buffer-Locality for Multiple Index Based Scans through Intelligent Placement and Index Scan Speed Control

an Introduction ETD Preparation and Submission Marshall University Graduate College July 6, 2011

How to write a scholarship rejection letter

NetApp Sizing Guidelines for MEDITECH Environments

Model Number: OmniBER 718 User Guide Date Printed: September 2000 Part Number:

Similarity & Link Analysis. Stony Brook University CSE545, Fall 2016

Relational Algebra Symbols

ID Card Production Software

CHAPTER 1 INTRODUCTION. Infineon consists of two main companies which are:

IBM PowerVM Express Edition and IBM Management Edition for AIX offerings help allocate systems resources to where they are needed

GD&T Administrator Manual v 1.0

Working Sample... Service For Life!

Schedule K Classification of Foreign Ports by Geographic Trade Area and Country

Towards Real-Time Volunteer Distributed Computing

Windows INSTRUCTION MANUAL

NIKON D7100 GUIDES PDF

The Editor GT ink jet controller

Managing Microservices Using Terraform, Docker, and the Cloud

Managing Complex Land Mobile Radio Systems

Development of Innovation Strategy and Patent Systems. Paik Saber Assistant General Counsel, IP Law IBM Asia Pacific

6. Games. COMP9414/ 9814/ 3411: Artificial Intelligence. Outline. Mechanical Turk. Origins. origins. motivation. minimax search

GigaPX Tools 2.0. Solutions for oversized images

Link State Routing. Brad Karp UCL Computer Science. CS 3035/GZ01 3 rd December 2013

Implementing VID Function with Platform Manager 2

APPLICATION NOTE. Computer Controlled Variable Attenuator for Lasers. Technology and Applications Center Newport Corporation

< The Family Demographics table contains the family demographic data, including home address and phone number

Ringgold External Identify Database Schema

Multiple Downstream Profile Implications. Ed Boyd, Broadcom

Back up your data regularly to protect against loss due to power failure, disk damage, or other mishaps. This is very important!

Final Report: DBmbench

RMF Post Processor Report JCL Samples for Use with RMF Spreadsheet Reporter

APPLICATION NOTE. Computer Controlled Variable Attenuator for Tunable Lasers. Technology and Applications Center Newport Corporation

User requirements for remote accessed instruments in material science

COMPUTER AIDED DESIGNING OF THE CABINET FURNITURE. Teofil MIHAILESCU, Wilhelm LAURENZI, Viorel POPA. Universitatea "Transilvania" din Brasov

Info theory and big data

Balance. Sketchbook Pages

The Senses model was developed for indoors use (museum, shopping, restaurants, coffes, offices, etc.) and can be wall mounted or placed on a table.

FAST TRACK READ ME FIRST! FAST TRACK E300 A Quick-Start Guide to Installing and Using Your COOLPIX 300. Contents. Nikon View... 25

Writing a Research Paper with Ease

Transaction Log Fundamentals for the DBA

MITOCW watch?v=zkcj6jrhgy8

Case Study. British Library 19th Century Book Digitisation Project

Byte = More common: 8 bits = 1 byte Abbreviation:

File Specification for the Exact Change Import file

Chapter 4 Heuristics & Local Search

Implementation and Analysis of Iterative MapReduce Based Heuristic Algorithm for Solving N-Puzzle

Legal Information System: A Model Framework for Indian High Courts

Communications Planner for Operational and Simulation Effects With Realism (COMPOSER)

CSE6488: Mobile Computing Systems

DCN Z44035C30DES00R02. Advanced Traffic Management System (ATMS) Release 2. Code Specifications (540) - SWARM

Hello and welcome to the CPA Australia podcast. Your weekly source of business, leadership, and public practice accounting information.

Enhanced Storage and Network Function Innovation to Quality Management

Towards 100G over Copper

Class XII A. Mock Pre Board Exam - Syllabus ( ) English. Maths. Economics. History. Geography. Home Science. Psychology

SOME MORE DECREASE AND CONQUER ALGORITHMS

Supplementary Materials for

OmniBevel 2017 Best-in-class technology for bevel cutting

The Quake-Catcher Network: A Volunteer Distributed Computing Seismic Network

Metadata for Photographs SHN Post-Conference Workshop - ATALM 2016 Part 2: Image Digitization

Q A bitmap file contains the binary on the left below. 1 is white and 0 is black. Colour in each of the squares. What is the letter that is reve

CS 758/858: Algorithms

Autonomous Face Recognition

Media & Entertainment Venture Capital In The US - Industry Market Research Report [Download: PDF] [Digital] By IBISWorld READ ONLINE

M F TYPE S R-SETUP. Setup Software

Section SN [SOCIAL NETWORK] Sequence: 8

A Quick Introduction to Modular Arithmetic

Computing Permutations with Stacks and Deques

Legal challenges 3D Printing A business perspective

Baltic Marine Environment Protection Commission

Database Operations at Groupon using Ansible. Mani Subramanian Sr. Manager Global Database Services Groupon

Introduction to. Algorithms. Lecture 10. Prof. Piotr Indyk

Arrays. Independent Part. Contents. Programming with Java Module 3. 1 Bowling Introduction Task Intermediate steps...

Homework 2 Solutions. Perform.op analysis, the small-signal parameters of M1 and M2 are shown below.

Radivoje Đurić, 2015, Analogna Integrisana Kola 1

BACnet Protocol Implementation Conformance Statement

Nova Full-Screen Calibration System

Wireless systems. how radio works radio spectrum allocation examples. tradeoffs. non-technical issues

Intel's 65 nm Logic Technology Demonstrated on 0.57 µm 2 SRAM Cells

Managing Microservices using Terraform, Docker, and the Cloud

Skylanders Swap Force Wii Graphics

Analogue Signals. M J Brockway. February 5, 2018

Heuristic Search with Pre-Computed Databases

GWiQ-P: : An Efficient, Decentralized Quota Enforcement Protocol

Heuristics & Pattern Databases for Search Dan Weld

Programming an Othello AI Michael An (man4), Evan Liang (liange)

The lump sum amount that a series of future payments is worth now; used to calculate loan payments; also known as present value function Module 3

Galera Replicator IRL Art van Scheppingen Head of Database Engineering

Transcription:

o o o

o o TOS 2.4.1 PDI 3.0.0 IBM DS 7.5 IBM DS PX 7.5 INFA PWC 8.1.1 Test1 13 7 19 8 16 Test2 0 0 0 0 0 Test3 13 3 7 9 11 Test4 8 7 12 5 13 Test5 15 4 13 12 18 Test6 15 4 10 5 12 Test7 11 3 7 8 15 Test8 13 12 5 14 16 Test8.2 12 13 4 15 18 Test8.3 12 12 4 15 17 Test9 12 6 15 12 17 Test9.2 16 5 12 9 19 Test9.3 12 8 13 11 16 Test10 20 7 12 10 13 Test10.2 20 6 6 13 16 Test10.3 16 6 6 14 18 Test10.4 12 4 8 17 19 Test11 20 7 10 8 16 Test11.2 20 6 6 12 16 Test11.3 16 6 6 13 19 Test12 20 8 13 6 13 Test12.2 20 7 6 11 16 Test12.3 17 7 5 12 19 Total 333 148 199 239 353

Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,00 7,80 39,10 162,09 PDI 3.0.0 2,00 15,50 83,80 417,80 IBM DS 7.5 2,00 4,00 12,50 66,00 IBM DS PX 7.5 3,40 12,00 40,00 150,00 INFA PWC 8.1.1 2,00 7,00 18,00 74,00

Lines 100 000 1 000 000 5 000 000 TOS 2.4.1 15,26 144,50 731,78 PDI 3.0.0 14,90 151,80 843,90 TOS 2.4.1 with Extended Insert 2,60 25,00 129,00

Lines 100 000 500 000 1 000 000 TOS 2.4.1 2,25 6,26 14,25 PDI 3.0.0 4,78 21,20 37,40 IBM DS 7.5 4,00 11,00 19,00 IBM DS PX 7.5 4,00 8,00 15,00 INFA PWC 8.1.1 5 6 9

Lines 100 000 1 000 000 2 000 000 TOS 2.4.1 4,36 22,12 49,66 PDI 3.0.0 2,60 30,60 72,70 IBM DS 7.5 3,00 18,00 40,00 IBM DS PX 7.5 6,00 27,00 55,00 INFA PWC 8.1.1 4 7 11

Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,30 8,50 43,10 183,13 PDI 3.0.0 5,30 51,00 259,40 1126,10 IBM DS 7.5 2,00 10,00 56,00 178,00 IBM DS PX 7.5 4,75 11,33 41,00 155,00 INFA PWC 8.1.1 3,00 6,00 17,00 74,00

Lines 100 000 500 000 1 000 000 TOS 2.4.1 1,24 1,4 1,69 PDI 3.0.0 4,26 22,26 47,80 IBM DS 7.5 2,40 8,00 13,67 IBM DS PX 7.5 8,00 12,00 17,50 INFA PWC 8.1.1 4 3 4

Lines 100 000 500 000 1 000 000 TOS 2.4.1 5,99 23,26 52,72 PDI 3.0.0 38,35 201,60 382,60 IBM DS 7.5 12,70 65,00 116,00 IBM DS PX 7.5 15,00 30,50 47,50 INFA PWC 8.1.1 5 9 14

Sorted by age Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,44 15,73 188,21 1016,03 PDI 3.0.0 3,63 32,85 155,95 668,20 IBM DS 7.5 4,20 60,70 267,70 IBM DS PX 7.5 4,00 16,25 64,50 492,67 INFA PWC 8.1.1 5,00 13,00 50,00 201,00

Sorted by firstname Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,69 18,05 168,46 1071,20 PDI 3.0.0 3,40 31,20 157,15 739,20 IBM DS 7.5 6,00 58,00 426,00 IBM DS PX 7.5 4,00 16,00 57,00 624,00 INFA PWC 8.1.1 4,00 13,00 51,00 223,00

Sorted by age & firstname Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,33 17,40 225,03 1007,00 PDI 3.0.0 3,22 29,27 159,10 842,20 IBM DS 7.5 7,33 60,00 360,00 IBM DS PX 7.5 4,50 16,33 59,00 582,50 INFA PWC 8.1.1 5,00 13,00 49,00 211,00

Group by Age (Count) Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 0,62 6,99 30,05 124,16 PDI 3.0.0 2,70 26,53 134,30 466,50 IBM DS 7.5 2,00 6,00 21,00 128,00 IBM DS PX 7.5 4,00 6,50 21,33 78,00 INFA PWC 8.1.1 3,00 5,00 8,00 27,00

Group by Age (Count, Sum(Rate), Avg(Rate), Min(Rate), Max(Rate)) Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 0,84 7,44 37,61 139,12 PDI 3.0.0 2,60 25,20 138,30 426,00 IBM DS 7.5 2,00 11,00 50,00 184,00 IBM DS PX 7.5 11,25 15,33 33,50 254,33 INFA PWC 8.1.1 2,00 6,00 12,00 38,00

Group by FirstName (Count) Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 0,86 7,89 198,79 928,08 PDI 3.0.0 2,70 29,70 162,30 544,00 IBM DS 7.5 2,00 14,00 68,00 424,00 IBM DS PX 7.5 4,50 11,00 40,00 505,00 INFA PWC 8.1.1 4 9 23 85

Lookup 100 000 rows ~7MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,45 6,39 28,72 108,37 PDI 3.0.0 4,14 21,40 87,60 288,90 IBM DS 7.5 5,00 10,60 33,00 139,00 IBM DS PX 7.5 5,00 12,20 40,00 122,00 INFA PWC 8.1.1 5,00 11,00 32,00 116,00

Lookup 500 000 rows ~34MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 3,9 8,89 32,36 115,67 PDI 3.0.0 7,90 24,50 97,40 291,10 IBM DS 7.5 28,00 33,00 56,00 195,00 IBM DS PX 7.5 7,00 13,00 40,00 122,00 INFA PWC 8.1.1 4,00 11,00 33,00 122,00

Lookup 1 000 000 rows ~68MB Lookup 1 000 000 rows ~68MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 9,86 14,26 38,6 121,44 PDI 3.0.0 14,50 32,20 116,60 487,25 IBM DS 7.5 68,30 80,00 102,00 203,00 IBM DS PX 7.5 9,25 15,00 40,00 123,00 INFA PWC 8.1.1 5,00 12,00 35,00 142,00

Lookup 5 000 000 rows ~365MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 56,51 69,1 199,26 557,1 PDI 3.0.0 IBM DS 7.5 369,00 407,00 496,00 973,00 IBM DS PX 7.5 24,00 30,00 55,00 134,00 INFA PWC 8.1.1 11,00 14,00 42,00 141,00

Lookup 100 000 rows ~7MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,51 6,74 29,55 101,65 PDI 3.0.0 3,30 17,10 78,40 305,00 IBM DS 7.5 6,00 10,50 36,00 144,00 IBM DS PX 7.5 7,00 14,00 41,00 137,00 INFA PWC 8.1.1 5,00 10,00 33,00 120,00

Lookup 500 000 rows ~34MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 4,26 9,28 32,44 111,98 PDI 3.0.0 7,80 20,50 81,50 310,00 IBM DS 7.5 28,60 34,00 57,00 173,00 IBM DS PX 7.5 7,50 14,25 44,67 155,20 INFA PWC 8.1.1 5,00 10,00 34,00 126,00

Lookup 1 000 000 rows ~68MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 10,2 15,22 38,31 126,63 PDI 3.0.0 14,10 32,35 111,35 319,05 IBM DS 7.5 66,00 68,00 95,00 220,00 IBM DS PX 7.5 9,00 18,00 51,00 153,33 INFA PWC 8.1.1 6,00 14,00 34,00 130,00

Lookup 100 000 rows ~7MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 1,42 5,65 24,63 106,78 PDI 3.0.0 2,60 13,00 59,80 327,60 IBM DS 7.5 6,00 10,00 30,00 137,00 IBM DS PX 7.5 9,00 15,25 47,33 146,00 INFA PWC 8.1.1 4,00 12,00 33,00 121,00

Lookup 500 000 rows ~34MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 4,16 8,74 30,34 120,53 PDI 3.0.0 7,26 19,30 72,25 319,60 IBM DS 7.5 28,00 35,50 63,00 189,50 IBM DS PX 7.5 11,00 16,00 44,00 150,00 INFA PWC 8.1.1 5 11 33 127

Lookup 1 000 000 rows ~68MB Lines 100 000 1 000 000 5 000 000 20 000 000 TOS 2.4.1 10,98 15,18 38,49 126,57 PDI 3.0.0 13,30 27,35 79,00 413,45 IBM DS 7.5 38,49 90,40 108,00 231,00 IBM DS PX 7.5 13,00 19,00 49,00 134,00 INFA PWC 8.1.1 6 13 37 131

Test 1: File Input Delimited > File Output Delimited - dynamic partitioning at 2 with more than 5 millions rows This is a Disk Bounded test Test 2: File Input Delimited > Table MySQL Output Not Applicable Test 3: Table Oracle Input > File Output Delimited - no partitioning as it's too small in volume and short in time Test 4: File Input Delimited > Table Output Oracle BULK

- commit size at 100000 - dynamic partitioning at 2 with 2 millions rows This is a Disk Bounded test Test 5: File Input Delimited > Transform > File Output Delimited - function "CONCAT(CONCAT(firstname,' '),lastname)" is replaced by "firstname ' ' lastname" - dynamic partitioning at 2 with more than 5 millions rows This is a Disk Bounded test Test 6: Table Input Oracle > Aggregation > Table Output Oracle (ELT) - no partitioning as it's too small in volume and short in time Oracle database is not 'tuned' for ELT mode Test 7: Tables Input Oracle > Transformation > Tables Output Oracle (ELT) - commit size at 50000 - no partitioning as it's too small in volume and short in time Oracle database is not 'tuned' for ELT mode Test 8: File Input Delimited > Sort > File Output Delimited - sorter memory adjustment This is a memory limited test at 20 millions rows (2 pass sort are required) and also disk limited sometime Test 9: File Input Delimited > Aggregate > File Output Delimited - dynamic partitioning at 2 with more than 5 millions rows in source - aggregator memory adjustment This is a CPU bounded test Test 10: File Input Delimited > Lookup > File Output Delimited - dynamic partitioning at 2 with more than 5 millions rows in source or lookup - lookup memory adjustment - lookup in the flow with hash partitioning point This is a CPU bounded test Test 11: File Input Delimited > Lookup > File Output Delimited && rejects - use of router in place of filters - dynamic partitioning at 2 with more than 5 millions rows in source - lookup memory adjustment - lookup in the flow with hash partitioning point This is a CPU bounded test Test 12: file_input_delimited >_file_lookup_delimited > file_output_delimited rejects && innerjoin_rejects_file_output_delimited - use of router in place of filters - dynamic partitioning at 2 with more than 5 millions rows in source - lookup memory adjustment - lookup in the flow with hash partitioning point This is a CPU bounded test