High Availability Flashback Archive Data Guard Streams Online

High Availability • Flashback Archive • Data Guard • Streams • Online Maintenance • Data Recovery Advisor

<Insert Picture Here> Flashback Data Archive

Data History and Retention • Data retention and change control requirements are growing • Regulatory oversight and Compliance • Sarbanes-Oxley, HIPAA, Basel-II, Internal Audit • Business needs • Extract “temporal” dimension of data • Understand past behavior and manage customer relationships profitably • Failure to maintain appropriate history & retention is expensive • Legal risks • Loss of Reputation • Current approaches to manage historical data are inefficient and often ineffective

Data History and Retention - Requirements • Historical data needs to be secure and tamper proof • Unauthorized users should not be able to access historical data • No one should be able to update historical data • Easily accessible from existing applications • Seamless access • Should not require special interfaces or application changes • Minimal performance overhead • Optimal Storage footprint • Historical data volume can easily grow into hundreds of terabytes • Easy to set up historical data capture and configure retention policies

Managing Data History – Current Approaches • Application or mid-tier level • Combines business logic and archive policies • Increases complexity • No centralized management • Data integrity issues if underlying data is updated directly • Database level • Enabled using Triggers • Significant performance and maintenance overhead • External or Third-party • Mine redo logs • History stored in separate database • Cannot seamlessly query OLTP and history data • None of the above approaches meet all customer requirements • Customers are therefore forced to make significant compromises

Introducing Flashback Data Archive • Transparently tracks historical changes to all Oracle data in a highly secure and efficient manner • Historical data is stored in the database and can be retained for as long as you want • Special kernel optimizations to minimize performance overhead of capturing historical data • Historical data is stored in compressed form to minimize storage requirements • Automatically prevents end users from changing historical data • Seamless access to archived historical data • Using “AS OF” SQL construct select * from product_information AS OF TIMESTAMP '02 -MAY-05 12. 00 AM‘ where product_id = 3060

Introducing Flashback Data Archive • Extremely easy to set up • enable history capture in minutes! • Completely transparent to Automatically Purge Data based on Retention policy applications • Centralized and automatic management • policy-based • multiple tables can share same Retention and Purge policies • automatic purge of aged history Retention Period

How Does Flashback Data Archive Work? • Primary source for history is the undo data • History is stored in automatically created history tables inside the archive • Transactions and its undo records on tracked tables marked for archival • undo records not recycled until history is archived • History is captured asynchronously by new background process (fbda) • default capture interval is 5 minutes • capture interval is self-tuned based on system activities • process tries to maximize undo data reads from buffer cache for better performance • INSERTs do not generate history records

Flashback Data Archive And DDLs • Possible to add columns to tracked tables • Automatically disallows any other DDL that invalidates history • Dropping and truncating a tables • Dropping or modifying a column • Must disable archiving before performing any major changes • Disabling archiving discards already collected history • Flashback Data Archive guarantees historical data capture and maintenance • Any operations that invalidates history or prevents historical capture will be disallowed

Creating Flashback Data Archive & Enable History Tracking 1. Create tablespace (Automatic Segment Space Management is required) 2. Create a flashback data archive Ø Set the retention period CREATE FLASHBACK ARCHIVE fda 1 TABLESPACE tbs 1 RETENTION 5 YEAR; 3. Enable archiving on desired tables ALTER TABLE EMPLOYEES FLASHBACK ARCHIVE fda 1;

Managing Flashback Data Archive SYS_FBA_HIST_* - Internal History Table • • replica of tracked table with additional timestamp columns partitioned for faster performance no modifications allowed to internal partitions compression reduces disk space required no out-of-box indexes support for copying primary key indexes from tracked table in later releases (TBD) Applications don’t need to access internal tables directly • • use ‘AS OF’ to seamlessly query history Alerts generated when flashback data archive is 90% full Automatically purges historical data after expiration of specified retention period • • • supports ad-hoc purge by administrators (privileged operation

Summary • Managing historical data should no longer be a onerous task • Flashback Data Archive provides a secure, efficient, easy to use and applicant transparent solution • • Easy to implement Centralized, Integrated and query-able Highly storage and performance efficient Automatic, Policy-based management • Reduce costs of compliance • Can be used for variety of other purposes • Auditing, Human error correction, etc.

<Insert Picture Here> Data Guard

Data Guard Enhancements • Better standby resource utilization • Enhanced HA / DR functionality • Improved performance Data Guard becomes an integral part of IT operations

Physical Standby with Real-Time Query Concurrent Real-Time Query Continuous Redo Shipment and Apply Primary Database Physical Standby Database • Read-only queries on physical standby concurrent with redo apply • Supports RAC on primary and/or standby • Queries see transactionally consistent results • Handles all data types, but not as flexible as logical standby

Real-time Query – Benefits • Immediate appeal to a large installed customer base for physical standby • Allows leveraging existing physical standby assets for excellent business use • Satisfies several customers with specific requirements • Telecom – service schedules for technicians • Medical – access patient medical reports • Finance – provide management-level reports • Transportation – provide responses to package tracking queries • Web-business – scale-out read access for catalog browsing • Significant differentiator compared to storage mirroring • Mirror volumes are offline during mirroring

Snapshot Standby Leverage Standby Database for Testing Updates Primary Database Queries Updates Physical Standby Snapshot Database • Preserves zero data loss, although no real time query or fast failover • Truly leverages DR hardware for multiple purposes • Similar to storage snapshots, but provides DR at the same time anduses single copy of storage

Snapshot Standby Easier than manual steps in 10. 2 Standby > alter database recover managed standby database cancel; > create restore point before_lt guarantee flashback database; Primary > alter system archive log current; > alter system set log_archive_dest_state_2=defer; Standby > alter database activate standby database; > startup mount force; > alter database set standby database to maximize performance; > alter system set log_archive_dest_state_2=defer; > alter database open; PERFORM TESTING, ARCHIVE LOGS NOT SHIPPED > startup mount force; > flashback database to restore point before_lt; > alter database convert to physical standby; > startup mount force; > alter database recover managed standby database disconnect from session; Primary > Alter system set log_archive_dest_state_2=enable 11. 1 Standby > alter database convert to snapshot standby; PERFORM TESTING, ARCHIVE LOGS CONTINUE TO BE SHIPPED > alter database convert to physical standby;

Use Physical Standby to Detect Lost Writes • Use new initialization parameter db_lost_write_protect • Compare versions of blocks on the standby with that in the incoming redo stream • Version discrepancy implies lost writes • Can use the standby to failover and restore data consistency

Enhanced SQL Apply • Support • XMLType data type (CLOB) • Transparent Data Encryption (TDE) • DBMS_FGA (Fine Grained Auditing) • DBMS_RLS (Virtual Private Database) • Role-specific DBMS_SCHEDULER jobs • (PRIMARY, LOGICAL STANDBY, BOTH) • Dynamic SQL Apply parameter changes • Support for Parallel DDL execution on the standby database

Enhanced Fast-Start Failover • Supports Maximum Performance (ASYNC) Mode • Automatic failover for long distance standby • Data loss exposure limited using Broker property (default=30 seconds, min=6 seconds) Fast. Start. Failover. Lag. Limit • Immediate fast-start failover for user-configurable health conditions ENABLE FAST_START FAILOVER [CONDITION <value>]; • Condition examples: • Datafile Offline • Corrupted Controlfile • Corrupted Dictionary • Inaccessible Logfile • Stuck Archiver • Any explicit ORA-xyz error • Apps can request fast-start failover using api DBMS_DG. INITIATE_FS_FAILOVER

Data Guard Performance Improvements • Faster Failover • Failover in seconds with Fast-Start Failover • Faster Redo Transport • Optimized async transport for Maximum Performance Mode • Redo Transport Compression for gap fetching: new compression attribute for log_archive_dest_n • Faster Redo Apply • Parallel media recovery optimization • Faster SQL Apply • Internal optimizations • Fast incremental backup on physical standby database • Support for block change tracking

Rolling Database Upgrades Using Transient Logical Standby Physical Logical • Start rolling database upgrades with physical standbys • Temporarily convert physical standby to logical to perform the upgrade • Data type restrictions are limited to short upgrade window Upgrade • No need for separate logical standby for upgrade Physical • Also possible in 10. 2 (more manual steps) Leverage your physical standbys!

<Insert Picture Here> Streams

Streams Overview Source Database Target Database Propagate Redo Logs Capture Apply 1 Apply 2 Transparent Gateway • All sites active and updateable • Automatic conflict detection & optional resolution Non-Oracle • Supports data transformations Database • Flexible configurations – n-way, hub & spoke, … • Database platform / release / schema structure can differ • Provides HA for applications where update conflicts can be avoided or managed

Streams Enhancements in Oracle Database 11 g • Additional Data Type Support • Table data comparison • Synchronous capture • Manageability & Diagnosibility improvements • Performance improvements • Streams AQ Enhancements

Newly Supported Datatypes • XMLType • Storage CLOB • Transparent Data Encryption (TDE) • Default: Capture TDE=> Apply TDE • PRESERVE_ENCRYPTION apply parameter controls behaviour when destination columns are not encrypted

Table Data Comparison • Compare data between live sources • Compare 11. 1 with 10. 1, 10. 2 or 11. 1 Compare • Recheck • In-flight data • Rows that are different • Converge feature • Identify “truth” database (local or remote) for row diffs DBMS_COMPARISON

Synchronous Capture • Available in all editions of Oracle Database 11 g • Efficient internal mechanism to immediately capture change • Changes captured as part of the user transaction • DML only • LCRs enqueued persistently to disk • When to use: • Replicate a few low activity tables of highly active source database • Capture from redo logs cannot be implemented DBMS_CAPTURE_ADM. CREATE_SYNC_CAPTURE

Streams Performance Advisor • Auto-discovery of streams topology on Capture Changes 10110 00011 10101 multiple databases • Automatic performance analysis across all databases • Per-Stream Analysis: • Time-based analysis of each component (waits, CPU, etc. ) using ASH • Bottleneck components • Top wait events of bottleneck Change Apply • Per-Component Analysis: • Throughput and latency • Aborted or Enabled • Integrated with ADDM • Stream errors are integrated with Server-generated Alerts

Split and Merge of Streams Challenge • With hub&spoke configurations, when one destination is unavailable, all destinations are hit with a performance impact because capture queue spills to disk after 5 minutes Solution • • Split the queue between live and down destinations Merge queues after recovery Ø Maintains high performance for all replicas Ø Automated, fast “catch-up” for unavailable replica

Streams: Hub with 3 Spokes Destination Database A Dequeue LCRs Propagation A Queue Apply Process Source Database Enqueue LCRs Destination Database B Dequeue LCRs Propagation B Queue Capture Process Apply Process Destination Database C Dequeue Apply LCRs Process Queue Propagation C

Split Streams: Site A Unavailable Source Database CLONED Propagation A X Destination Database A Dequeue LCRs Queue Apply Process Queue CLONED Capture Process (Disabled) Enqueue LCRs Destination Database B Dequeue LCRs Propagation B Queue Capture Process Apply Process Destination Database C Apply Dequeue Process LCRs Queue Propagation C

Split Streams: Site A Available Source Database CLONED Propagation A Destination Database A Dequeue LCRs Queue Enqueue LCRs Apply Process Queue CLONED Capture Process (Enabled) Enqueue LCRs Destination Database B Dequeue LCRs Propagation B Queue Capture Process Apply Process Destination Database C Apply Dequeue Process LCRs Queue Propagation C

Merge Streams: Original Configuration Destination Database A Dequeue LCRs Propagation A Queue Apply Process Source Database Enqueue LCRs Destination Database B Dequeue LCRs Propagation B Queue Capture Process Apply Process Destination Database C Apply Dequeue Process LCRs Queue Propagation C

Streams …. more manageability improvements • Automated Alerts • abort of capture, propagation, or apply • 1 st error in DBA_APPLY_ERROR • Propagation uses scheduler • Improved error messages • • • ORA-1403 -> ORA-26786 or ORA-26787 customer DML Handlers need to handle these new exceptions more detail added to many error messages • Cross-database LCR tracking • trace Streams messages from start to finish DBMS_CAPTURE_ADM. SET_MESSAGE_TRACKING(‘mylabel’) V$STREAMS_MESSAGE_TRACKING

Streams performance • CERN reporting >5000 txns/s in 10. 2. 03 • Open. LAB presentation http: //openlab-mu-internal. web. cern. ch/openlab-muinternal/Documents/3_Presentations/Slides/2007/DW_openlab_qr 1_2007. pdf • 11 g performance improvements • common case 10. 2 -> 11. 1 almost double

Streams Advanced Queuing (AQ) New Features • JMS/AQ performance improvements • Direct Streams AQ support in JDBC • Scalable event notification • Grouping notification by time • Multiple processes notification for scalability • Improved Manageability • Scheduler support • Performance views

Flashback Transaction

Flashback Transaction • Automatically finds and backs out a transaction and all its dependent transactions • Utilizes undo, archived redo logs, supplemental logging • Finalize changes with commit, or roll back • “Dependent” transactions include • Write after write • Primary Key insert after delete • Faster, Easier than laborious manual approach DBMS_FLASHBACK. TRANSACTION_BACKOUT

Flashback Transaction Enterprise Manager Support

Data Recovery Advisor

Data Recovery Advisor The Motivation Investigation & Planning • Oracle provides robust tools for data repair: ü RMAN – physical media loss or corruptions ü Flashback – logical errors ü Data Guard – physical or logical problems • However, problem diagnosis and Recovery choosing the right solution can be error prone and time consuming • Errors more likely during emergencies

Data Recovery Advisor • Oracle Database tool that automatically diagnoses data failures, presents repair options, and executes repairs at the user's request • Determines failures based on symptoms • E. g. an “open failed” because datafiles f 045. dbf and f 003. dbf are missing • Failure Information recorded in diagnostic repository (ADR) • Flags problems before user discovers them, via automated health monitoring • Intelligently determines recovery strategies • Aggregates failures for efficient recovery • Presents only feasible recovery options • Indicates any data loss for each option • Can automatically perform selected recovery steps Reduces downtime by eliminating confusion

Data Recovery Advisor Enterprise Manager Support

Data Recovery Advisor RMAN Command Line Interface RMAN> list failure • lists all previously detected failures RMAN> advise failure • presents recommended recovery options RMAN> repair failure • repair database failures (defaults to first repair option from most recent ADVISE FAILURE) RMAN> change failure 5 priority low • change failure priority (with exception of ‘critical’ priority failures, e. g. missing control file)

<Insert Picture Here> Recovery Manager, Ultra Safe Mode and Online Operations

RMAN Enhancements • Better performance • Intra-file parallel backup and restore of single data files (multi-section backup) • Faster backup compression (ZLIB, ~40% faster) • Better security • Virtual private catalog allows a consolidation of RMAN repositories and maintains a separation of responsibilities. • Lower space consumption • Duplicate database or create standby database over the network, avoiding intermediate staging areas • Integration with Windows Volume Shadow Copy Services (VSS) API • Allows database to participate in snapshots coordinated by VSS-compliant backup management tools and storage products • Database is automatically recovered upon snapshot restore via RMAN

Ultra-Safe Mode The DB_ULTRA_SAFE parameter provides an easy way to turn on the safest mode. It affects the default values of the following parameters • DB_BLOCK_CHECKING, which initiates checking of database blocks. This check can often prevent memory and data corruption. • DB_BLOCK_CHECKSUM, which initiates the calculation and storage of a checksum in the cache header of every data block when writing it to disk. Checksums assist in detecting corruption caused by underlying disks, storage systems or I/O systems. • DB_LOST_WRITE_PROTECT, which initiates checking for "lost writes". Data block lost writes occur on a physical standby database, when the I/O subsystem signals the completion of a block write, which has not yet been completely written in persistent storage. Of course, the write operation has been completed on the primary database.

Online Operations & Redefinition Improvements • Fast ‘add column’ with default value • Invisible indexes speed application migration and • • testing Online index build with NO pause to DML No recompilation of dependent objects when Online Redefinition does not logically affect objects More resilient execution of table DDL operations Support Online Redefinition for tables with Materialized View Logs

<Insert Picture Here> Q&A

High Availability • Flashback Archive • Data Guard • Streams • Online Maintenance • Data Recovery Advisor