Partition, Compress, Archive and Purge
Keep Your System on the Road
David Kurtz
Go-Faster Consultancy Ltd.
david.kurtz@go-faster.co.uk
www.go-faster.co.uk
Who Am I?
• Oracle Database Specialist
– Independent consultant
• Performance tuning
– PeopleSoft ERP
– Oracle RDBMS
• Book
– www.psftdba.com
•
•
OakTable
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This happens to be a story about...
• An ERP System
– But it could be about any on-line transaction
processing system.
• A PeopleSoft system
– But it could be about any ERP
• PeopleSoft HR/Time & Labor/Payroll
– But it could be about any product
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PeopleSoft HR, T&L, GP
@ Morrisons
• 130,000 employees
– 100,000 in stores
• Scheduled hours
– Clock in/out
– T&L matches reported hours with schedules to
determine payable time
– Legacy T&L feed from Manufacturing and
Distribution.
– Payable time passed to Global Payroll.
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Two Challenges
• Performance
– Big Tables
• (for OLTP)
• Eg payroll accumulator
table 2.4 billion rows!
– Poor/Variable
Performance
• Various processes and
reports suffering
• Critical Processes
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• Database Size
– >4TB
– Growth ≈ 1TB/year
– Backup
• Size/Contention
– Cloning
• Dev/Test environments
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0.91Tb/yr
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Throw Away
• When we say the ‘database is slow’, often:
– It is fetching data from disk, reading it, and
deciding it isn’t something it wants and throwing it
away.
– It would be better if we had not spent time and
resource fetching it in the first place
• The fastest way to do anything is not to do it at
all.
–
Cary Millsap
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4 Techniques
• Partition
– Breaking tables and indexes into manageable
pieces
• Compress
– Squeezing more data into the same space
• Archive
– Get the data out of the live application tables and
put it somewhere else.
• Purge
– Expunge the data from the database
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PARTITIONING
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Partitioning
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Can I Partition Application
tables?
• Support implication?
• We could only use partitioning because the
application and the business data was
suitable.
– You need to understand
• the application
• the data (which reflects the business)
• partitioning
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Partitioning decisions
driven by Application
• Global Payroll
– ‘streamed’ processing
• RANGE on EMPLID to match concurrent processing no good for archiving
– ‘Calendar Group ID’ (effectively a payroll period
ID) corresponds to a period of time
• LIST sub-partition on payroll period - archive by
partition
• Scheduling, Time & Labor
– Weekly range partitions on ‘Date under reporting’
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Partitioning in Other PeopleSoft
Financials Modules?
• General Ledger
– FISCAL_YEAR & ACCOUNTING_PERIOD
– Monthly/Quarterly/Annual partitions.
• Many tables keyed by
– Set ID (legal entity/legislature)
– Business Unit
• No use for archiving, but good for separating concurrent
processes.
• I have another customer with 99% of the business in one
BUSINESS_UNIT.
– Partitioning is not an option for them.
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Partitioning helps archiving
• Links logical data value to physical location of data
in the database.
• Time-based partitioning
– Future / Current / Historical
• Partition-wise operations
–
–
–
–
–
Compress historical partitions
Archive by partition exchange
Purge by dropping whole partitions.
Less Redo. Faster.
Better chance of reclaiming free space
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Delete rows –v- Drop Partition?
• Free space is left in
data block.
• High Water Mark
unchanged
– Data block remain part
of table/index
– Still scanned by
queries.
• Still backed up by
RMAN
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• No longer in a database
object. So not
referenced.
• Free space is available
in tablespace.
– Still backed up
• If the space is at end of
the datafile it can be
trimmed off by resize.
– No longer backed up
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Partitioning PeopleSoft
at Morrisons
• Global Payroll
– 46 tables range on EMPLID, matching 32 streams
– List sub-partition largest tables by pay period (CAL_RUN_ID).
– 24 archive tables, range partitioned on pay period into tax-year
partitions.
– 2 custom GP reporting tables
• Schedules & Time and Labor
– 10 tables in weekly range partitions
– of which Reported Time table hash sub-partitioned
• Audit Tables
– 28 monthly range partitions on audit timestamp
• Security Tables
– Separate partitions for different business units
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Managing Partitioning and
Partition DDL
• How are you going to generate partition
DDL?
– Manual scripting?
– Who is going to write them?
– On going maintenance?
• Add new partitions over time?
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Managing Partitioning
in PeopleSoft
• Partitioning strategies
– Described own meta-data tables
• PL/SQL Utility package
– generate DDL scripts.
– Driven by PeopleTools tables and our own meta-data
• Application Designer from PT8.51 will preserve some existing
partitioning
– See Managing Oracle Table Partitioning in PeopleSoft
Applications with GFC_PSPART Package
• http://www.go-faster.co.uk/gfc_pspart.manual.pdf
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Licencing of Partitioning
• Oracle RDBMS Enterprise Edition only
– And then separately licenced
• Application Support Policies Vary
– Partitioning does not invalidate any aspect of
PeopleSoft support.
– My understanding is that the policy for EBusiness suite is not the same.
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COMPRESSION
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Oracle RDBMS Compression
• Basic Compression
– Not separately licenced
– Only option in 10g
• Advanced Compression
• Out of scope of this presentation
– Licenced option
– Available in 11g
• Hybrid Columnar Compression (HCC)
• Also out of scope of this presentation.
– Exadata and ZFS filesystem only.
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Simple Compression
• Block Dictionary Encoding
– Data values stored only stored once in array in
data block.
– Pointer from row of data to array of values.
• Shorter Rows, more rows per block, fewer
Blocks, less I/O
• More CPU to read row.
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Simple Table Compression
• Specified at table or partition level with DDL
– Sub-partition level inherits from partition level
• Compression only occurs
– On creation of the object
• ALTER TABLE … COMPRESS
– Direct path insert into object
– CPU overhead during compression and read
• Row decompressed on update
– Likely to be migrated
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Advanced Table Compression
• 11g Licenced Option
–
–
–
–
Same Compression Algorithm
Same Performance Benefits/Overheads
Data compressed after DML
Tables remain on-line during compress
operations.
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When can I compress my data?
• When it is no longer updated by application.
– Because DML uncompresses rows
– But that may be well before you can
archive/purge.
– Needs knowledge of business/application.
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What tables do I compress?
• Depends on application, business, and
partitioning strategy.
– Audit data partitions: as soon as month ends
– Payroll result data: when pay period is closed
for 1 month
– T&L: after 6 months
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Compression Gotcha!
• During
– ALTER TABLE PARTITION … MOVE …
COMPRESS.
• Local index partitions momentarily become
unusable before they go back to being usable.
• This can cause application errors
–
–
–
–
Choose carefully when to compress,
or ignore unusable indexes,
or do it in an outage
or use on-line reredefinition
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Custom PL/SQL Utility Package
• DBA run management utility
• Meta-data rules to determine when partition no
longer updated.
– Moves partitions to correct tablespace
– Incrementally compress static partitions.
– Dynamically generates DDL statements and
executes them.
– Added some logging which appears trace files and
alert log.
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How much table compression?
• It depends on your data!
• We have see a factor 2x – 5x on tables
– (50%-80% reduction in size)
• Indexes are less compressible
– Up to 50% reduction
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Index Compression
• Applies to whole of index
– Can choose to enable/disable for each partition
• Useful for DEFAULT or MAXVALUE partition
• Index remains compressed
– DML does not decompress
– CPU Performance overhead
• Table compression does not affect index size.
– But can affect clustering factor and hence cost
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Index Compression Prefix Length
• Choose how many columns of index to
compress
– Too much compression can be worse than no
compression at all
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ANALYZE INDEX VALIDATE
• Examines physical index segments
– OPT_CMPR_COUNT = optimal compression
– OPT_CMPR_PCTSAVE = size saving relative
to current index size
– 1 result row in INDEX_STATS
• Result is for last partition if partitioned index
• MAXVALUE / DEFAULT partition may produce
unusual results.
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Index Compression
• Not limited to static data
• Increased CPU overhead on DML
– Offset by lower I/O overhead
• We found that it has been worth
compressing largest indexes on live tables.
– Space Saving
– Net performance gain
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ARCHIVE & PURGE
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Archive & Purge
• Archive:
– Move data from live
application table to
another table.
– In this case another to
table in the same
database.
– Read-only access
provided to archive
tables.
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• Purge:
– Expunge data from the
database.
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Archive/Purge
• For each table or set of tables
– Define a policy that specifies when data is
archived or purged.
• Compression too, but that has no functional impact.
• Discuss with business
– Check legal requirements
• PAYE 3 years, Company Accounts 6 years
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‘But my data will disappear’
• That may be a good thing
– If you keep data you have to look after it
responsibly.
– Pay for the disk to store it/back it up.
• Read-only access via PS/Query tool to archive
data.
– No access via SQL Developer
• A very few components and reports access
archive tables
– Development cost of customisation
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Example Archive/Purge Policies
– GP: archive 2 rolling years, purge after 8 tax
years
– Schedules, purge at 56 weeks
– T&L, purge at 108 weeks
– Audit: various:
• Archive after 3 months, 1, 3 year
• Purge 6 months, 1 year, 2 years, never
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Archive Method
• Partition Management
– Exchange/Drop whole
Partitions
• Time based partitioning
– Faster
• Avoid rewriting data
• Avoid redo
– Global Indexes
maintenance overhead
• Don’t build on archive table
– Compression must match
• Archive table indexes not
compressed.
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• Row-by-Row
– Non-time based
partitioning
• Some GP tables
– Can be done on-line
– Can compress data
during rewrite
– Different partitioning
strategy in archive and
live.
– Move archive to lower
storage tier.
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PL/SQL Archive/Purge Utility
• Custom PL/SQL Package
–
–
–
–
Driven by same meta-data as partitioning utility
Archive by partition exchange
Purge by dropping partition.
Called from custom Application Engine
• So archiving can be done via application.
– Writes
• To PeopleSoft Message Log
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Custom Archive Utility
• Based on delivered PeopleSoft Archive
Utility
• We only use it for GP archiving
• Copies data in direct path
– Faster
– Can compress during copy
• Calls PL/SQL utility to drop partitions to
save deleting data.
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‘PSARCH’ Schema Design
• 2nd schema to hold archive tables
– Only tables archived by partition exchange
– Same name as live tables
– Same local indexes as live
• Benefits
– Application cannot update/delete from these tables.
• Drawbacks
– Views to make them accessible to PS/Query.
– Can’t manage indexes with Application Designer.
– Only Owner can alter index
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Tablespace Design
• No impact on performance
– Because all on same tier of disk
• Do not keep objects with dissimilar purge policies in
same tablespaces
– You can drop empty tablespaces and recover space.
• Periodic tablespaces make sense without purge
policy
• With a purge policy might just have one tablespace.
– Unless you have tiered storage available.
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Wrong Tablespace Design
• Before archive policy
– Weekly T&L and Schedule partitions in same
monthly tablespaces
• Archive Policy
– T&L: 108 weeks
– Schedules: 56 weeks
• Schedules populated first, T&L later.
– Schedules tend to be nearer start of tablespace
– Schedules purged first leaving holes than cannot be
trimmed off.
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Free Space Fragmentation
• Free Space left in middle of tablespace
– Dropping objects
– Compressing objects can leave holes
• Less Severe since Oracle 9i
– Uniform extent sizes
– Bitmap space map
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Oracle RMAN Backup
• Backs up block with SCN
– If an object is dropped, blocks still have SCN
– These empty blocks are still backed up.
• Can only reduce full backup size by
trimming free space from end of data files.
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Defragmentation of Free Space
• PL/SQL utility to rebuild objects nearest
end of data file into spaces in the middle of
the tables
– Needs to be done during an application outage.
• Frees space at end of data file that can be
trimmed off.
– Thus reducing size of database and backup.
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Oracle Flashback Database
• SQL Rollback
– We are used to the idea of rolling back transaction
that have not been committed.
• Flashback database
– Generates additional flashback logging
– Rollback committed transaction and DDL
• but not through a drop/resize data file (smaller)
– Whole database option
• Highly effective in testing archive/purge
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Future: Oracle >= 11g
• Automatic Partition Creation
• Range-Range partitioning
• Advanced Compression
– Licenced Option
– Supports DML
• Possible row-migration threats.
• Active Data-Guard
– Off-load query activity to standby database
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PROGRESS
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0.91Tb/yr
0.56Tb/yr
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Achievements
• Database Size
– 4.5TB => <2TB
– No Growth (apart from GP archive tablespace)
• Performance Improvements
– GP calculation and other processing
– T&L processing
– Financial Reports
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Caveat
• I/O has reduced, but not as much as the size
of the database
• IOPs/Gb of data file has gone up!
– Cheaper to use SSD rather than stripe over
more spindles but leaving empty disk space to
supply more IOPs?
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Conclusion
• It depends…
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Nullius in verba
QUESTIONS?
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