Oracle 12c ilm_customer_experience

2013 © Trivadis
BASEL BERN BRUGG LAUSANNE ZUERICH DUESSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MUNICH STUTTGART VIENNA
2013 © Trivadis
Implementation of Oracle 12c ILM
Jacques Kostic Senior Consultant LS-IMS
Date 2014.09.12
1

2013 © Trivadis
AGENDA
1. Customer Overview
 Environment
 Requirements
 Phases of the project
2. Trivadis Activities
 Analysis of the Tools on the market
 The implemented solution
3. Live Demo
4. Q & A
Date 2014.09.12
2

2013 © Trivadis
Date 2014.09.12
Customer Overview
3

2013 © Trivadis
Customer Overview
The name will not be disclosed but the most relevant
characteristics to the project are reported below.
 Medium size customer of the Public sector.
 Several databases involved on the data archiving project with more than
15 years of online data.
 Complex business rules which define the data archiving and purging.
 Expired information should be deleted from the database (law obligation).
Date 2014.09.12
4
Customer
Environment

2013 © Trivadis
Customer Overview
Description of the customer requirements to implement on
the database with no application change.
 Data should be organized within the following categories:
Date 2014.09.12
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Customer
Requirements
1 of 2
 Active  data younger than 3 fiscal years.
 Archived  data older than 3 fiscal years but younger than the limit defined by
the associated business rule (different retentions between 10, 15 or 25 years).
 To purge  expired data should be consistently deleted from the database.

2013 © Trivadis
Customer Overview
 Storage tiering should be possible between Active and Archived data.
 The automated database refresh procedure which clone Production
databases to Test environment, should be capable to replicate all data or
the Active data only.
 The initial database version is 11gR2 but the decision to upgrade to 12c
was taken before starting this project.
Date 2014.09.12
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Customer
Requirements
2 of 2

2013 © Trivadis
Customer Overview
Due to the complexity and the risks associated to the
purge of the data, the project has been divided in three
distinct phases:
 Identification of the most appropriate data lifecycle method.
 Validation of the technical solution by a PoC.
 Implementation of the data lifecycle on all databases.
Date 2014.09.12
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Phases of the
Project

2013 © Trivadis
Date 2014.09.12
Trivadis Activities
8

2013 © Trivadis
Trivadis Activities
With the aim of being customer oriented and not
technology oriented Trivadis has used the S.W.O.T.
analysis to identify the most suitable data lifecycle
technology.
 The following options have been retained for the S.W.O.T. analysis:
 Home made archiving/purging solution.
 Pre-12c features (Partitioning, Compression, Total Recall).
 Oracle 12c ILM.
Date 2014.09.12
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Analysis of
the Tools on
the market
The S.W.O.T. analysis has shown that none of the retained options
was able to satisfy all requirements. But the adoption of Oracle 12c
Information Lifecycle Managements could guarantee solid foundation
to the project.

2013 © Trivadis
Trivadis Activities
Verified that ILM alone was not enough we have
combined the following functionalities to engineer and
automate a robust Lifecycle solution.
 Oracle 12c ILM the cornerstone of the project. Designed to optimize
storage tiering and data compression, guaranteeing the maximum
performance and cost saving. This technology relies on two main
components:
Date 2014.09.12
10
The
Implemented
Solution
1 of 4
 Heat Map  provides a detailed view of how the data is being accessed and
modified. The fine-grained statistics generated at row and segment level are
differentiated by access (e.g. full table scan and index lookup). Other
administrative tasks like Stats Gathering, DDLs or Table Redefinitions are
automatically excluded.

2013 © Trivadis
Trivadis Activities
 Automatic Data Optimization (ADO)  allows to create policies for storage
tiering, data compression and data movement. ADO uses Heat Map
information to determine when enforcing a rule at row or segment level.
Complex business rules can be translated in ADO actions using PL/SQL
functions.
Date 2014.09.12
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The
Implemented
Solution
2 of 4
-- ILM Partition compression
ALTER TABLE Sales modify partition p2009 ILM ADD POLICY ROW STORE COMPRESS
ADVANCED SEGMENT AFTER 30 DAYS OF NO MODIFICATION;
-- ILM Partition tiering
ALTER TABLE Sales modify partition p2007 ILM ADD POLICY TIER TO TS_ARCHIVE;

2013 © Trivadis
Trivadis Activities
To cover the missing functionalities the following options
have been integrated on the project.
 In-Database Row Archiving permits to archive rows within a table by
marking them as invisible. Added value for the customer:
Date 2014.09.12
12
The
Implemented
Solution
3 of 4
 Safely hide expired rows to the users with no need of application changes.
 Development of a module for validating the rows marked as expired before
definitive deletion.

2013 © Trivadis
Trivadis Activities
 Ad hoc PL/SQL procedures in support of the validation and purging of the
expired data.
Date 2014.09.12
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The
Implemented
Solution
4 of 4
 Automated RMAN replication of the test databases with the possibility to
replicate all data or the Active data only.

2013 © Trivadis
Questions and answers ...
2013 © Trivadis
BASEL BERN BRUGG LAUSANNE ZUERICH DUESSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MUNICH STUTTGART VIENNA
Jacques Kostic Senior Consultant LS-IMS
Date 2014.09.12

Oracle 12c ilm_customer_experience

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