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Oracle 12c ilm_customer_experience

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Engineering an archiving solution for a set of databases using Oracle 12c ILM and In Database Archiving features.
Done in collaboration with my colleague Emiliano Fusaglia.

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Oracle 12c ilm_customer_experience

  1. 1. 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 Implementation of Oracle 12c ILM 1
  2. 2. 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 Implementation of Oracle 12c ILM 2
  3. 3. 2013 © Trivadis Date 2014.09.12 Implementation of Oracle 12c ILM Customer Overview 3
  4. 4. 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 Implementation of Oracle 12c ILM 4 Customer Environment
  5. 5. 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 Implementation of Oracle 12c ILM 5 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.
  6. 6. 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 Implementation of Oracle 12c ILM 6 Customer Requirements 2 of 2
  7. 7. 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 Implementation of Oracle 12c ILM 7 Phases of the Project
  8. 8. 2013 © Trivadis Date 2014.09.12 Implementation of Oracle 12c ILM Trivadis Activities 8
  9. 9. 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 Implementation of Oracle 12c ILM 9 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.
  10. 10. 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 Implementation of Oracle 12c ILM 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.
  11. 11. 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 Implementation of Oracle 12c ILM 11 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;
  12. 12. 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 Implementation of Oracle 12c ILM 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.
  13. 13. 2013 © Trivadis Trivadis Activities  Ad hoc PL/SQL procedures in support of the validation and purging of the expired data. Date 2014.09.12 Implementation of Oracle 12c ILM 13 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.
  14. 14. 2013 © Trivadis Date 2014.09.12 Implementation of Oracle 12c ILM Live Demo 14
  15. 15. 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 Implementation of Oracle 12c ILM

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