Title: Practical Space Management in Data Warehouse Environments
1Practical Space Management in Data Warehouse
Environments
Hamid Minoui Database Specialists,
Inc. www.dbspecialists.com hminoui_at_dbspecialists.
com
2Objectives
- To point out data warehouse space management
issues - Suggest resolutions
- Recommend space management methodologies
- Provide proactive prevention strategies
- Cover both Oracle 9i and Oracle 10g space
management features
3Characteristics of a Data Warehouse
- The data
- Large amount of data loads and ETL operations
- Very large size (Terabytes)
- Change in structure of source data
- Contains lots of historical data
- Data massaging and aggregations
- Multiple sources of data
- Dynamic nature of data
4Characteristics of a Data Warehouse (continued)
- Maintenance activities
- Space management
- Table re-organizations
- Index rebuilds
- Partition maintenance
- Refresh maintenance on materialized views
- Job and scheduling management
5Characteristics of a Data Warehouse (continued)
- Typical issues
- Data integrity issues
- Data security issues
- Space issues
- Query performance issues
- Duplicate rows
6Characteristics of a Data Warehouse (continued)
- Database features frequently used
- Materialized views (MV)
- Bitmap indexes and bitmap-join indexes
- Index organized tables (IOT)
- Parallel execution
- Table and index partitioning
- Table and index compression
- Load utilities and facilities
7Other Characteristics
- Star schemas, snow flakes or 3rd Normal Form
- Have dimensions and hierarchy
- Frequent need to collect statistics
- Use of bulk and parallel loads
- Variety in the generated queries
- Dynamic nature of queries
- Divided into areas (staging, ODS, and target
area) - Often associated with smaller data marts
8Performance Tuning and Resolutions
- Frequent query tuning
- Star transformation
- De-normalization
- Pre-aggregations via materialized views
- BTree, IOT, function based, bitmap, bitmap-join
indexes - Use of database resource management
9Why is Space a Coveted Resource in a Data
Warehouse?
- Lots of disk space is consumed
- Stores all enterprise data
- Segments are mostly large
- Many indexes
- Years of historical data kept online
- Many versions of the same data
- Duplicated and de-normalized data
- Various levels and dimensions of data (monthly,
weekly, daily)
10Why is Space a Coveted Resource in a Data
Warehouse?
- Enough reserve space needed
- For daily/weekly/monthly growth
- Recall offline old data when needed
- Data correction
- Materialized views and their growth
- Emergency needs
- Data files and tablespace growth
- Temporary tablespaces
11Reacting to Space Issues
- Down sides
- Often, not enough time to react
- Delay in the load
- Wasted resources to reload
- Up sides
- Loads are usually scheduled
- Once data is loaded, most of it wont change
12Issues with Database Backups in a Data Warehouse
- Too many files to backup every night
- Backup takes a long time to complete
- System resources busy during backup
- Possible licensing issues with third-party backup
software - Restoring and recovery after a failure can take a
long time
13A Typical Backup Strategy
- Make non-current table spaces READONLY every
month - Perform a special backup of READONLY tablespaces
- Exclude the READONLY table spaces from regular
hot backups - Never backup temporary tablespaces
- Caveat You must wait until all transactions are
committed
14Avoiding Unnecessary Redo Log Generation
- Create some tables and all indexes with NOLOGGING
for any segment that can be re-generated without
doing a database recovery - SQLLoader with direct path load
- CREATE TABLE AS SELECT from external or transient
tables - INSERT using append hint
- Use global temporary tables
-
- insert / append / into transiant_table selec
t from source_table - create table transient_table as select from
source_table
15Speeding Up Bulk Load Operations
- Before the load
- Make all non-unique indexes unusable
- Disable the primary and unique constraints if the
source data is trusted - Disable all triggers on the table
- Set the session to skip unusable indexes
16Speeding Up Bulk Load Operations
- Implement the load
- Use append and parallel hints with insert
- Commit the transaction
- After the load
- Rebuild indexes
- Enable triggers and constraints
17Space Issues in Data Warehouses
- Permanent tablespaces (data, indexes)
- Temporary tablespaces (temp segments)
- UNDO segments and tablespace
18Space Issues with Permanent Tablespaces
- Caused by
- Poor extent sizing
- Setting maxextents
- PCT_INCREASE gt 0
- Small data files (tablespaces)
- User quota on tablespace
19Space Issues with Temporary Tablespace
- Caused by
- Not enough space for the sort segments
- Other temp segments such as global temporary
tables - Multiple users sharing the same temporary space
- Multiple queries with sort requirements running
at any time
20Space Issues with Temporary Tablespace
- Partially resolved by
- Oracle 9i - Dynamic PGA memory allocation
- PGA_AGGREGATE_TARGETltinteger valuegt
- WORKAREA_SIZE_POLICYAUTO
- Oracle 10g - Tablespace Group assignment
21Space Issues Associated with Undo Segments
- Long running queries causing ORA-1555 (snapshot
too old) - Small UNDO tablespace
- Small rollback segments
22Database Block Size (DB_BLOCK_SIZE)
- Should seriously be considered
- An important decision with new data warehouse
projects - Inappropriate value can be disastrous and
detrimental - Small value can
- Impact I/O efficiency for majority of queries
- Negatively influence overall database performance
23Appropriate DB_BLOCK_SIZE Value
- Multiple of the OS block size
- As large as your I/O subsystem can handle in a
single read - As large as supported by Oracle
- Best benefit from larger block size if
- Database is configured on raw devices, or
- Direct I/O is available to you.
24Benefits of Larger DB_BLOCK_SIZE Value
- Efficiency with index scan
- A larger block size reduces the number of reads
required to probe an index and scan a range of
values from its leaf blocks - Less memory requirement for buffer cache
- Fewer buffers needed for index branch blocks
- Better compression ratio for tables, indexes
- Improvement in block density
- Amount of space used by fixed portion
- of bock header is reduced
25Benefits of Larger DB_BLOCK_SIZE Value
- Blocks can accommodate longer rows less chance
for row chaining - Less occurrence of ORA-1555
- Increase in size of the transaction table in undo
segments header blocks - Fewer writes required for data loads
- Because of the reduced block level overhead, less
redo logs are generated when blocks are modified
sequentially
26Disks, I/O and Database Files Configuration
- A poorly configured I/O subsystem can badly
impact I/O performance - Poor I/O performance can impair a data warehouse
- Configure disk and distribute data for read and
write efficiency - Use raw I/O if possible, otherwise use direct I/O
- Make use of asynchronous I/O, parallel read and
parallel writes
27Disks, I/O and Database Files Configuration
- Stripe and Mirror or Mirror and Stripe the disks
- RAID-10 or RAID-01
- Evenly spread your data and Stripe And Mirror
Everything (SAME) on many disks - Reserve room on file systems for auto extendable
files
28Managing the UNDO Segments
- Manual undo (rollback segments) management
- Pre Oracle 9i practices
- Too many manual interventions by DBA
29Managing UNDO (continued)
- Automatic Undo Management (AUM)
- Much better Highly recommended
- Allows controlling retention of committed
transactions undo information (UNDO_RETENTION) - Better monitoring statistics
- Infrequent occurrence of ORA-1555
- SMON periodically manage space and shrinks undo
segments
30UNDO_RETENTION Parameter Setting
- Set to a value equal to the time used by the
longest running query - Undo is expired when retention time is reached
- Expired undo will be de-allocated if needed by
new transactions - Unexpired undo are re-used if space is needed
(undo reuse) - Default value is 300 seconds
31Undo Reuse and Undo Stealing
- Undo ReuseUnexpired undo of the same segment
will be reused - Undo StealingUnexpired undo of another segment
is used - Undo reuse is more common. Occurs when
- UNDO tablespace is too small, or
- UNDO_RETENTION value is too large
32Monitoring the UNDO Segments Statistics
- Statistics are gathered in VUNDOSTAT every 10
minutes - Helps sizing UNDO tablespaces and tune
UNDO_RETENTION - Statistics are retained for 7 days
33VUNDOSTAT
BEGIN_TIME Beginning time for this interval
END_TIME Ending time for this interval
UNDOTSN Tablespace ID of the last active undo within the interval
UNDOBLKS Number of consumed undo blocks within the period
MAXQUERYLEN The longest length of time (in seconds) a query took to complete within this period
TXNCOUNT Total number of transactions executed with the period
34VUNDOSTAT (continued)
UNXPSTEALCNT Number of attempts to obtain undo space by stealing unexpired extents from other undo segments
UNXPBLKRELCNT Number of unexpired blocks released from undo segments to be used by other transactions
SSOLDERRNT Number of times ORA-1555 occurred with the period
NOSPACERRCNT Number of times space was unavailable in the undo tablespace when requested and failed
35Tuning UNDO_RETENTION
- Oracle 9i
- Manually adjust to the time taken by the longest
query - SELECT MAX (MAXQUERYLEN) FROM VUNDOSTAT
- Oracle 10g
- Automatically tracked and tuned by RDBMS
36The UNDO Tablespace
- Created at DB creation or with CREATE UNDO
TABLESPACE - Use VUNDOSTAT for sizing and monitoring
- Space issues if UNDO_RETENTION is too large
- Use AUTOEXTEND
- RETENTION_GUARANTEE clause
- Sizing formulaUndo Segment Space Required (MB)
(undo_retention undo_blcks/secs
DB_BLOCK_Size)/1024
37Database Fragmentation Issues
- Best to reduce or eliminate fragmentation to
avoid wastage and improve performance - Tablespace level (or file level) fragmentation
- Segment level fragmentation
- Block level fragmentation
38Tablespace Level Fragmentation
- Bubble Fragmentation
- Free block of space not large enough for another
extent - Honeycomb Fragmentation
- Free un-coalesced space next to each other but
considered separate
39Segment Level Fragmentation
- Space allocated to segment is not fully utilized
(wasted) - Space above the high water mark (unused blocks)
- Free segment blocks below the high water mark
40Block Level Fragmentation
- Blocks are not empty but there is space within a
block that is not used - Caused by
- Setting of PCTFREE and PCTUSED
- Deletions
- Row migrations
41Tablespace Planning
- Use locally managed tablespaces (LMTs) with
UNIFORM size extents - 64K bitmaps on file header are used to manage
extents - Improves performance and significantly reduces
overhead associated with updating dictionary
tables (recursive SQL) - No need to use ST enqueue
- No more tablespace fragmentation
42Tablespace Planning
- Use Automatic Segment Space Management (ASSM)
- Set at the tablespace level
- Tablespace must be locally managed
- Uses bitmap instead of freelist to manage space
within segments
43Benefits of ASSM
- No more need for FREELISTS, FREELIST GROUPS and
PCTUSED - Reduces segment level and block level
fragmentations - Reduces the number of buffer free waits
- Adds efficiency to space usage
- Provides better use of space within the blocks
44LMT Considerations
- The bitmap is 64K
- Make the size of each file a multiple of UNIFORM
extent64K - Storage parameters
- Avoid setting them
- If already defined on segments reorganize, or
rebuild with storage parameters matching
tablespace
45Multiple Tablespace Size Models
- SAFE (methodology)
- Group segments according to size (3 groups)
- Use 3 tablespace model having different UNIFORM
extents - Assign each group to one of the size model
- Develop a naming convention
Segment Size Extent Size Size Model
lt 128 M 128 KB Small
gt 128 M lt 4 GB 4 MB Medium
gt 4 GB 128 MB Large
46Tablespaces for Different Types of Segments
- Separate indexes and tables
- Better manageability
- Different type of usage
- Reduces wastage (indexes are rebuilt often in
data warehouses)
47Adjust Settings of PCTFREE and PCTUSED Parameters
- Avoid using default values
- Set according to usage
- Most of the times PCTFREE0 and PCTFREE99 should
be enough - If ASSM, no need for PCTUSED
- More compact data in blocks reduces waste and
improves I/O
48Use Index Organized Tables (IOTs)
- When most of the columns are indexed
- When associated tables are used
- Columns are pre-sorted
- Makes better use of space and improve performance
- Good for certain data warehouse tables
49Table Compression
- Introduced in Oracle 9i R2
- Improves read only operations and factors out
repetitive values within a block - Replaces duplicate values in a block with a
reference to a symbol table in the block - Very low CPU overhead to reconstruct the block
- Significantly fewer blocks, leading to better I/O
- Very flexible (not all blocks are compressed)
- Associated with bulk load operations
50Table Compression
- To compress a table useALTER TABLE t1 MOVE
compress - To compress a table partition useALTER TABLE T1
MOVE PARTTION P1 compress - Alternative way CTAS compressCREATE TABLE T1
compressAS SELECT FROM T1_UNCOMPRESSED - Table or partition not available (locked) during
move - Use DBMS_REDEFINITION for online move
51To Get the Best Results
- To achieve the best compression ratio
- Analyze the table to get column statistics
SELECT COLUMN_NAME, NUM_DISTINCT, NUM_NULLS,
AVG_COL_LENFROM DBA_TAB_COLUMNS - Identify best candidate columns for sorting as
columns with - Lowest number of distinct values (low
NUM_DISTINCT) - Least amount of null values (low NUM_NULLS)
- Longest average length (high AVG_COL_LEN)
- CTAS compress and use order by candidate_column
52Table Compression Limitations
- Can not be used on LOB field
- Can not be used for IOTs
- Can not compress tables with bitmap indexes
- With Oracle 9i, cannot drop or add columns to
compressed tables
53Index Key Compression
- Introduced in Oracle 8i
- Compression of leading index columns
- Indexes are grouped into a suffix and prefix
entry - Suffix entry made out of unique pieces
- Prefix entry consist of the grouping piece
- Can offer significant space savings and better
I/O performance
54Index Key Compression Example
- Current years Car Inventory table, index CAR_IND
indexes columns are Type, Color, Model - Before compression
ltSUVgtltBlackgtltRock Climbergt ltSedangtltBluegtltCharismagt
ltSUVgtltBlackgtltJungle Cruisergt ltSedangtltBluegtltFantasygt
ltSUVgtltBlackgtltMountaineergt ltSedangtltBluegtltStarletgt
.
55Index Key Compression Example (continued)
- ALTER INDEX CAR_IND compress 3
- After compression
ltSUVgtltBlackgt ltRock Climbergt ltJungle Cruisergt ltMountaineergt
ltSedangtltBluegt ltCharismagtltFantasygtltStarletgt
.
56Index Key Compression
- Partitioned indexes cannot be compressed
- Bitmap indexes cannot be compressed
- Can be defined on IOT
- Slight CPU overhead during index scan
- Consumes much less space
- Increases I/O throughput and buffer cache
efficiency - Ideal for data warehouses
57Identifying Keys to Compress
- Validate or analyze the indexVALIDATE INDEX
INDX1 - Query the index_stats viewSELECT NAME,
OPT_CMPR_COUNT, OPT_CMPR_PCTSAVEFROM
index_stats - Examine outputNAME OPT_CMPR_COUNT OPT_CMPR
_PCTSAVE------- -------------- ------------------
----INDX1 2
57
58De-Allocating Unused Space
- Segment Level
- Blocks above the segment high water mark (unused
blocks) - Space below the segment high water mark (free
blocks) - Tablespace Level
- Free space within tablespace
- Data file level
- Unallocated space above the highest allocated
extent (file high water mark)
59Identify Segment Space Usage
- DBMS_SPACE.UNUSED_SPACE
- Information about amount of unused space in
segment and position of high water mark - DBMS_SPACE.FREE_BLOCKS
- Information about the number of blocks on the
freelist groups - DBMS_SPACE.SPACE_USAGE
- Information about the space usage of blocks under
the high water mark
60De-Allocate Segment Free Space
- Unused blocks-
- ALTER TABLE INDEX CLUSTER segment_name
- DEALLOCATE UNUSED KEEP nK
- De-allocates only space above segment high water
mark, retaining space specified by KEEP - Other Unused space-
- Pre Oracle 10g Reorganize table, rebuild index
- Table move, export/import, DBMS_REDEFINITION
interface) - Oracle 10g Online segment shrink
61Two-Phase Online Segment Shrink
- ALTER TABLE table SHRINK SPACE
- Phase 1
- A series of DELETE and INSERT statements applied
to move data to the beginning of the segment - DML-compatible changes are held on rows and
blocks - Phase 2
- High water mark adjusted to the appropriate
location. - Exclusive lock is held
- Unused blocks (above high water mark) are
de-allocated
62One-Phase Online Segment Shrink
- ALTER TABLE table SHRINK SPACE COMPACT
- With COMPACT keyword only the first phase is
executed. - To implement phase 2, issue it without COMPACT
keyword at a later time
63One-Phase Online Segment Shrink (continued)
- Restrictions
- Row movement must be enabled
- Triggers based on ROWID of table must be disabled
- In data warehouses, locking might not be a
problem on some tables
64De-allocating Space at the Tablespace Level
- Caused by tablespace fragmentation
- Index rebuilds, table moves, partition move, etc.
- Not having UNIFORM size extents
65De-allocating Space at the Data File Level
- File size larger than the last block used in the
file - Size over-estimated
- Auto extended
66Shrinking Data Files
- The statement
- ALTER DATABASE DATAFILE file_name resize n (K
M) - Attempts to size the data file to exactly n K (or
M) - It is safe. It will fail with ORA-03297, if there
are blocks of data beyond the requested resize
value - ORA-03297 File contains nnn blocks of data
beyond requested resize value.
67Steps to Shrink Data Files to High Water Mark
Position
- 1) Create a temporary table preferably a GTT
- CREATE global temporary table SPACE_ADMIN_GTTON
COMMIT PRESERVE ROWS ASSELECT FILE_NAME,
TABLESPACE_NAME, BYTES, BYTES, BYTESFROM
DBA_DATAFILES WHERE 10 - Create another table with name of tablespace to
shrink - CREATE GLOBAL TEMPORAY TABLE SHRINKING_TBS_GTTON
COMMIT PRESERVE ROWSASSELECT TABLESPACE_NAME
FROM DBA_TABLESPACESWHERE TABLESPACE_NAME in
(TBS1,TBS2,TBS3)COMMIT
68Steps to Shrink Data Files to High Water Mark
Position (continued)
- 3) Get DB_BLOCK_SIZE
- column value new_val blksizeselect value from
vparameterwhere name 'db_block_size'
69Steps to Shrink Data Files to High Water Mark
Position (continued)
- 4) Calculate the files high water mark and save
- INSERT INTO SPACE_ADMIN_GTTSELECT file_name,
tablespace_name, ceil( (nvl(hwm,1)blksiz
e)/1024/1024 ) smallest, ceil(
blocksblksize/1024/1024) currsize,
ceil( blocksblksize/1024/1024) - ceil(
(nvl(hwm,1)blksize)/1024/1024 ) savingsFROM
DBA_DATA_FILES a, ( SELECT file_id,
max(block_idblocks-1) hwm FROM
DBA_EXTENTS GROUP BY file_id ) bWHERE
a.file_id b.file_id()AND a.tablespace_name
IN (SELECT tablespace_name FROM
SHRINKING_TBS_GTT)COMMIT
70Steps to Shrink Data Files to High Water Mark
Position (continued)
- 5) Generate ALTER DATABASE commands
- column cmd format a95 word_wrappedset trimspool
onSPOOL c\TMP\dbf_resize.sqlSELECT 'alter
database datafile '''file_name''' resize '
smallest 'm' cmdFROM
SPACE_ADMIN_GTTWHERE savings gt 5SPOOL OFF
71Automatically Resolving Space Issues
- Oracle 9i Feature called RESUMABLE SPACE
ALLOCATION - Allows an active session to be suspended if a
space issue is encountered - The session resumes automatically when
- Space issue is fixed
- A timeout period (default 2 hours) is reached
- Beneficial for data warehouse environments
72Steps for Resumable Space Allocation
- DBA grants RESUMABLE privilege to user
- User makes session resumable with
- ALTER SESSION ENABLE RESUMABLE
- 3. If session encounters space problem, it is
suspended
73Steps for Resumable Space Allocation
- 4. If AFTER SUPSPEND TRIGGER exists, it gets
executed - 5. If trigger does not exit (or disabled) or if
the trigger does not fix the space problem,
session remains suspended - 6. Session resumes when space problem is fixed or
timeout value is reached
74Other Helpful Space-Related Features
- Oracle-Managed Datafiles (OMF)
- DBA_ADVISOR family of views
- Oracle10g Workload Repository (AWR) and segment
advisor - Oracle 10g Grid Control for monitoring
75Conclusion
- Oracle is consistent in offering new space
management related features in every release - Should be used by DBAs for best practices
- They enhance performance, reduce waste, improve
availability, reduce frequency of failures, and
provide better monitoring - Data warehouse operations that rely heavily on
space and I/O performance benefit the most from
these features
76Contact Information
- Hamid Minoui
- Database Specialists, Inc.
- 388 Market Street, Suite 400
- San Francisco, CA 94111
- Tel 415/344-0500
- Email hminoui_at_dbspecialists.com
- Web www.dbspecialists.com