語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Dynamic Oracle Performance Analytics...
~
SpringerLink (Online service)
Dynamic Oracle Performance Analytics = Using Normalized Metrics to Improve Database Speed /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Dynamic Oracle Performance Analytics/ by Roger Cornejo.
其他題名:
Using Normalized Metrics to Improve Database Speed /
作者:
Cornejo, Roger.
面頁冊數:
XXI, 224 p. 83 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Database management. -
電子資源:
https://doi.org/10.1007/978-1-4842-4137-0
ISBN:
9781484241370
Dynamic Oracle Performance Analytics = Using Normalized Metrics to Improve Database Speed /
Cornejo, Roger.
Dynamic Oracle Performance Analytics
Using Normalized Metrics to Improve Database Speed /[electronic resource] :by Roger Cornejo. - 1st ed. 2018. - XXI, 224 p. 83 illus.online resource.
Part I. Performance Tuning Basics -- 1. Traditional Approaches -- Part II. The Dynamic Oracle Performance Analytics (DOPA) Process -- 2. Gathering Problem Information -- 3. Data Preparation -- 4. Statistical Analysis -- 5. Feature Selection -- 6. Taxonomy -- 7. Building the Model and Reporting -- Part III. Case Studies and Further Applications -- 8. Case Studies -- 9. Monitoring -- 10. Further Enhancements.
Use an innovative approach that relies on big data and advanced analytical techniques to analyze and improve Oracle Database performance. The approach in this book is a step-change away from traditional methods. Instead of relying on a few hand-picked, favorite metrics, or wading through multiple specialized tables of information such as those found in an automatic workload repository (AWR) report, you will draw on all available data, applying big data methods and analytical techniques to draw impactful, focused performance improvement conclusions. This book reviews past and present practices, along with available tools, to help you pinpoint areas for improvement. The book then guides you through a step-by-step method that can be used to take advantage of all available metrics to identify problem areas and work toward improving them. The method presented simplifies the tuning process and solves the problem of metric overload. You will learn how to: collect and normalize data, generate deltas that are useful in performing statistical analysis, create and use a taxonomy to enhance your understanding of problem performance areas in your database and its applications, and create a root cause analysis report that enables understanding of a specific performance problem and its likely solutions. What You'll Learn: Collect and prepare metrics for analysis from a wide array of sources Apply statistical techniques to select relevant metrics Create a taxonomy to provide additional insight into problem areas Provide a metrics-based root cause analysis regarding the performance issue Generate an actionable tuning plan prioritized according to problem areas Monitor performance using database-specific normal ranges.
ISBN: 9781484241370
Standard No.: 10.1007/978-1-4842-4137-0doiSubjects--Topical Terms:
557799
Database management.
LC Class. No.: QA76.9.D3
Dewey Class. No.: 005.74
Dynamic Oracle Performance Analytics = Using Normalized Metrics to Improve Database Speed /
LDR
:03537nam a22004095i 4500
001
989193
003
DE-He213
005
20200629144236.0
007
cr nn 008mamaa
008
201225s2018 xxu| s |||| 0|eng d
020
$a
9781484241370
$9
978-1-4842-4137-0
024
7
$a
10.1007/978-1-4842-4137-0
$2
doi
035
$a
978-1-4842-4137-0
050
4
$a
QA76.9.D3
072
7
$a
UN
$2
bicssc
072
7
$a
COM021000
$2
bisacsh
072
7
$a
UN
$2
thema
072
7
$a
UMT
$2
thema
082
0 4
$a
005.74
$2
23
100
1
$a
Cornejo, Roger.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1211946
245
1 0
$a
Dynamic Oracle Performance Analytics
$h
[electronic resource] :
$b
Using Normalized Metrics to Improve Database Speed /
$c
by Roger Cornejo.
250
$a
1st ed. 2018.
264
1
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2018.
300
$a
XXI, 224 p. 83 illus.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
Part I. Performance Tuning Basics -- 1. Traditional Approaches -- Part II. The Dynamic Oracle Performance Analytics (DOPA) Process -- 2. Gathering Problem Information -- 3. Data Preparation -- 4. Statistical Analysis -- 5. Feature Selection -- 6. Taxonomy -- 7. Building the Model and Reporting -- Part III. Case Studies and Further Applications -- 8. Case Studies -- 9. Monitoring -- 10. Further Enhancements.
520
$a
Use an innovative approach that relies on big data and advanced analytical techniques to analyze and improve Oracle Database performance. The approach in this book is a step-change away from traditional methods. Instead of relying on a few hand-picked, favorite metrics, or wading through multiple specialized tables of information such as those found in an automatic workload repository (AWR) report, you will draw on all available data, applying big data methods and analytical techniques to draw impactful, focused performance improvement conclusions. This book reviews past and present practices, along with available tools, to help you pinpoint areas for improvement. The book then guides you through a step-by-step method that can be used to take advantage of all available metrics to identify problem areas and work toward improving them. The method presented simplifies the tuning process and solves the problem of metric overload. You will learn how to: collect and normalize data, generate deltas that are useful in performing statistical analysis, create and use a taxonomy to enhance your understanding of problem performance areas in your database and its applications, and create a root cause analysis report that enables understanding of a specific performance problem and its likely solutions. What You'll Learn: Collect and prepare metrics for analysis from a wide array of sources Apply statistical techniques to select relevant metrics Create a taxonomy to provide additional insight into problem areas Provide a metrics-based root cause analysis regarding the performance issue Generate an actionable tuning plan prioritized according to problem areas Monitor performance using database-specific normal ranges.
650
0
$a
Database management.
$3
557799
650
1 4
$a
Database Management.
$3
669820
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9781484241363
776
0 8
$i
Printed edition:
$z
9781484241387
776
0 8
$i
Printed edition:
$z
9781484245910
856
4 0
$u
https://doi.org/10.1007/978-1-4842-4137-0
912
$a
ZDB-2-CWD
912
$a
ZDB-2-SXPC
950
$a
Professional and Applied Computing (SpringerNature-12059)
950
$a
Professional and Applied Computing (R0) (SpringerNature-43716)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入