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1 Practical Space Management in Data Warehouse Environments Hamid Minoui Database Specialists, Inc.

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1 1 Practical Space Management in Data Warehouse Environments Hamid Minoui Database Specialists, Inc.

2 2 Objectives 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

3 3 Characteristics 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

4 4 Characteristics 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

5 5 Characteristics of a Data Warehouse (continued) Typical issues: –Data integrity issues –Data security issues –Space issues –Query performance issues –Duplicate rows

6 6 Characteristics 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

7 7 Other 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

8 8 Performance Tuning and Resolutions Frequent query tuning Star transformation De-normalization Pre-aggregations via materialized views B*Tree, IOT, function based, bitmap, bitmap- join indexes Use of database resource management

9 9 Why 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)

10 10 Why 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

11 11 Reacting 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

12 12 Issues 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

13 13 A 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

14 14 Avoiding 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: SQL*Loader 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 select * from source_table ; create table transient_table as select * from source_table ;

15 15 Speeding 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

16 16 Speeding 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

17 17 Space Issues in Data Warehouses Permanent tablespaces (data, indexes) Temporary tablespaces (temp segments) UNDO segments and tablespace

18 18 Space Issues with Permanent Tablespaces Caused by: –Poor extent sizing –Setting maxextents –PCT_INCREASE > 0 –Small data files (tablespaces) –User quota on tablespace

19 19 Space 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

20 20 Space Issues with Temporary Tablespace Partially resolved by: –Oracle 9i - Dynamic PGA memory allocation PGA_AGGREGATE_TARGET= WORKAREA_SIZE_POLICY=AUTO –Oracle 10g - Tablespace Group assignment

21 21 Space Issues Associated with Undo Segments Long running queries causing ORA-1555 (snapshot too old) Small UNDO tablespace Small rollback segments

22 22 Database 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

23 23 Appropriate 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.

24 24 Benefits 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

25 25 Benefits 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

26 26 Disks, 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

27 27 Disks, I/O and Database Files Configuration Stripe and Mirror or Mirror and Stripe the disks –RAID-1+0 or RAID-0+1 Evenly spread your data and Stripe And Mirror Everything (SAME) on many disks Reserve room on file systems for auto extendable files

28 28 Managing the UNDO Segments Manual undo (rollback segments) management –Pre Oracle 9i practices –Too many manual interventions by DBA

29 29 Managing 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

30 30 UNDO_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

31 31 Undo Reuse and Undo Stealing Undo Reuse: Unexpired undo of the same segment will be reused Undo Stealing: Unexpired 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

32 32 Monitoring the UNDO Segments Statistics Statistics are gathered in V$UNDOSTAT every 10 minutes Helps sizing UNDO tablespaces and tune UNDO_RETENTION Statistics are retained for 7 days

33 33 V$UNDOSTAT BEGIN_TIMEBeginning time for this interval END_TIMEEnding time for this interval UNDOTSNTablespace ID of the last active undo within the interval UNDOBLKSNumber of consumed undo blocks within the period MAXQUERYLENThe longest length of time (in seconds) a query took to complete within this period TXNCOUNTTotal number of transactions executed with the period

34 34 V$UNDOSTAT (continued) UNXPSTEALCNTNumber of attempts to obtain undo space by stealing unexpired extents from other undo segments UNXPBLKRELCNTNumber of unexpired blocks released from undo segments to be used by other transactions SSOLDERRNTNumber of times ORA-1555 occurred with the period NOSPACERRCNTNumber of times space was unavailable in the undo tablespace when requested and failed

35 35 Tuning UNDO_RETENTION Oracle 9i: –Manually adjust to the time taken by the longest query SELECT MAX (MAXQUERYLEN) FROM V$UNDOSTAT; Oracle 10g: –Automatically tracked and tuned by RDBMS

36 36 The UNDO Tablespace Created at DB creation or with CREATE UNDO TABLESPACE Use V$UNDOSTAT for sizing and monitoring Space issues if UNDO_RETENTION is too large Use AUTOEXTEND RETENTION_GUARANTEE clause Sizing formula: Undo Segment Space Required (MB) = (undo_retention * undo_blcks/secs * DB_BLOCK_Size)/1024

37 37 Database 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

38 38 Tablespace 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

39 39 Segment 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

40 40 Block 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

41 41 Tablespace 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

42 42 Tablespace 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

43 43 Benefits 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

44 44 LMT Considerations The bitmap is 64K –Make the size of each file a multiple of UNIFORM extent+64K Storage parameters –Avoid setting them –If already defined on segments reorganize, or rebuild with storage parameters matching tablespace

45 45 Multiple 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 SizeExtent SizeSize Model < 128 M128 KBSmall >= 128 M & < 4 GB4 MBMedium >= 4 GB128 MBLarge

46 46 Tablespaces for Different Types of Segments Separate indexes and tables –Better manageability –Different type of usage –Reduces wastage (indexes are rebuilt often in data warehouses)

47 47 Adjust Settings of PCTFREE and PCTUSED Parameters Avoid using default values Set according to usage Most of the times PCTFREE=0 and PCTFREE=99 should be enough If ASSM, no need for PCTUSED More compact data in blocks reduces waste and improves I/O

48 48 Use 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

49 49 Table 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

50 50 Table Compression To compress a table use: ALTER TABLE t1 MOVE compress; To compress a table partition use: ALTER TABLE T1 MOVE PARTTION P1 compress; Alternative way CTAS compress: CREATE TABLE T1 compress AS SELECT * FROM T1_UNCOMPRESSED; Table or partition not available (locked) during move Use DBMS_REDEFINITION for online move

51 51 To Get the Best Results To achieve the best compression ratio: 1.Analyze the table to get column statistics SELECT COLUMN_NAME, NUM_DISTINCT, NUM_NULLS, AVG_COL_LEN FROM DBA_TAB_COLUMNS ; 2.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) 3.CTAS compress and use order by candidate_column

52 52 Table 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

53 53 Index 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

54 54 Index Key Compression Example Current years Car Inventory table, index CAR_IND indexes columns are: Type, Color, Model Before compression: ….…

55 55 Index Key Compression Example (continued) ALTER INDEX CAR_IND compress 3; After compression: ….

56 56 Index 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

57 57 Identifying Keys to Compress 1.Validate or analyze the index VALIDATE INDEX INDX1; 2.Query the index_stats view SELECT NAME, OPT_CMPR_COUNT, OPT_CMPR_PCTSAVE FROM index_stats; 3.Examine output NAME OPT_CMPR_COUNTOPT_CMPR_PCTSAVE INDX1 2 57

58 58 De-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)

59 59 Identify 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

60 60 De-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

61 61 Two-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

62 62 One-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

63 63 One-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

64 64 De-allocating Space at the Tablespace Level Caused by tablespace fragmentation –Index rebuilds, table moves, partition move, etc. –Not having UNIFORM size extents

65 65 De-allocating Space at the Data File Level File size larger than the last block used in the file Size over-estimated Auto extended

66 66 Shrinking 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.

67 67 Steps to Shrink Data Files to High Water Mark Position 1)Create a temporary table preferably a GTT CREATE global temporary table SPACE_ADMIN_GTT ON COMMIT PRESERVE ROWS AS SELECT FILE_NAME, TABLESPACE_NAME, BYTES, BYTES, BYTES FROM DBA_DATAFILES WHERE 1=0; 2)Create another table with name of tablespace to shrink CREATE GLOBAL TEMPORAY TABLE SHRINKING_TBS_GTT ON COMMIT PRESERVE ROWS AS SELECT TABLESPACE_NAME FROM DBA_TABLESPACES WHERE TABLESPACE_NAME in (TBS1,TBS2,TBS3); COMMIT;

68 68 Steps to Shrink Data Files to High Water Mark Position (continued) 3) Get DB_BLOCK_SIZE column value new_val blksize select value from v$parameter where name = 'db_block_size' ;

69 69 Steps to Shrink Data Files to High Water Mark Position (continued) 4) Calculate the files high water mark and save INSERT INTO SPACE_ADMIN_GTT SELECT file_name, tablespace_name, ceil( (nvl(hwm,1)*&&blksize)/1024/1024 ) smallest, ceil( blocks*&&blksize/1024/1024) currsize, ceil( blocks*&&blksize/1024/1024) - ceil( (nvl(hwm,1)*&&blksize)/1024/1024 ) savings FROM DBA_DATA_FILES a, ( SELECT file_id, max(block_id+blocks-1) hwm FROM DBA_EXTENTS GROUP BY file_id ) b WHERE a.file_id = b.file_id(+) AND a.tablespace_name IN (SELECT tablespace_name FROM SHRINKING_TBS_GTT) ; COMMIT;

70 70 Steps to Shrink Data Files to High Water Mark Position (continued) 5) Generate ALTER DATABASE commands column cmd format a95 word_wrapped set trimspool on SPOOL c:\TMP\dbf_resize.sql SELECT 'alter database datafile '''||file_name||''' resize ' || smallest || 'm;' cmd FROM SPACE_ADMIN_GTT WHERE savings >= 5 ; SPOOL OFF

71 71 Automatically 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

72 72 Steps for Resumable Space Allocation 1.DBA grants RESUMABLE privilege to user 2.User makes session resumable with ALTER SESSION ENABLE RESUMABLE ; 3.If session encounters space problem, it is suspended

73 73 Steps 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

74 74 Other 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

75 75 Conclusion 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

76 76 Contact Information Hamid Minoui Database Specialists, Inc. 388 Market Street, Suite 400 San Francisco, CA Tel: 415/ Web:


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