ENHANCING DATABASE PERFORMANCE

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1 ENHANCING DATABASE PERFORMANCE Performance Topics Monitoring Load Balancing Defragmenting Free Space Striping Tables Using Clusters Using Efficient Table Structures Using Indexing Optimizing Queries Supplying Hints to the Qptimizer. Monitoring Performance through Enterprise Manger. 1

2 Monitoring Load Balancing Monitoring Load Balancing and I/O Contention Examine the physical reads and writes on each physical devise. Move files to different physical devises to better balance the reads and writes. 2

3 Monitoring Load Balancing and I/O Contention (cont.) SQL> select d.name, f.phyrds, f.phywrts 2 from v$datafile d, v$filestat f 3 where d.file# = f.file#; NAME PHYRDS PHYWRTS /oraclec/data/db08/disk1/system01.dbf /oraclec/data/db08/disk1/tools01.dbf 5 3 /oraclec/data/db08/disk1/rbs01.dbf 8 50 /oraclec/data/db08/disk1/temp01.dbf 5 3 /oraclec/data/db08/disk1/users01.dbf 5 3 /oraclec/data/db08/disk1/indx01.dbf 5 3 /oraclec/data/dbins/disk1/data01.dbf /oraclec/data/dbins/disk1/indexes01.dbf 7 7 Moving a Data File 1. Take the tablespace offline using: ALTER TABLESPACE tablespace_name OFFLINE; 2. Shutdown the database 3. Use the unix mv command to move the file to the new location. 4. Use the following command to rename the file in Oracle. ALTER TABLESPACE RENAME DATAFILE full specification of old file including location TO full specification of new file including location 5. Bring the tablespace online using ALTER TABLESPACE tablespace_name ONLINE; 3

4 Monitoring Free Space Fragmentation Prior to Oracle version 9, the dictionary managed extents could be of different sizes. As data were deleted and added, fragments of unused free space would develop. To examine and minimize this free space: Query dba_free_space for the number of free space segments. Defragment the free space. Querying for Free Space Segments SQL> select tablespace_name, 2 sum(bytes), max(bytes), 3 count(tablespace_name) 4 as Fragments 5 from dba_free_space 6 group by tablespace_name; TABLESPACE_NAME SUM(BYTES) MAX(BYTES) FRAGMENTS AUDIT_ RBS SYSTEM TEMP TOOLS USERS

5 Coalescing Free Space Enter the following SQL statement for each tablespace that has significant fragmentation substituting a tablespace name for TBSNAME. :SQL> Alter Tablespace TBSNAME Coalesce; Contiguous segments of free space will be merged into one large segment of free space. Extents allocated to Segments will not be coalesced or moved. Striping If multiple I/O devices are available, you may increase performance when retrieving data from large tables by striping the table across multiple devises. An extent acquired by a table must fit entirely on a single disk. However, different extents of the same table may exist on different disks as shown below. Disk 1 Disk 2 Disk 3 Extent 1 Extent 2 Extent 3 5

6 Striping Example 1. Estimate the total size of the table. Suppose the table will have a size of 72K. 2. Decide how many striped segments you want to create. In this example, there will be three striped segments 3. Divide the size of the table by the number of striped segment. (72K / 3 = 24K in the example). This provides the size of each extent. 4. Create a tablespace placing the following conditions on the data files. Create a data file for each striped segment. Locate each data file on a separate disk. Size each data file one database block size larger than the extent that will be placed in it. (24K + 8K = 32K in the example). 5. Create the table assigning it to the tablespace you created above. Make the Initial and Next extents the size of the striped segment (24K in the example). Set the PctIncrease to zero. Set both the Minextents and Maxextents to the value of the number of striped segments (three in the example). Creating the Stripe Tablespace The statement below will create the Stripe tablespace with three data files. Each data file is located on a different disk. SQL> Create Tablespace Stripe 2 Datafile '/oraclec/data/db08/disk2/stripe02.dbf' 3 Size 32K, 4 '/oraclec/data/db08/disk3/stripe03.dbf' 5 Size 32K, 6 '/oraclec/data/db08/disk4/striped04.dbf' 7 Size 32K 8 Default Storage ( 9 Initial 32K Next 32K 10 Minextents 1 Maxextents PctIncrease 0); 6

7 Creating the TEST Table The TEST table below is created with three extents all of size 24K. Each extent must be located on a different disk since two 24K extents will not fit on one 32K disk. This technique works with Dictionary Managed Extents and must be slightly modified for Locally Managed Extents. SQL> Create Table TEST 2 (x1 char(10), x2 char(10)) 3 Tablespace STRIPE -- Place in Stripe 4 Storage (Initial 24K Next 24K 5 Minextents 3 Maxextents 3); USING CLUSTERS 7

8 Clusters Clusters are database objects that will cause data from the related tables to be stored in close proximity for more efficient data retrieval. Tables in the cluster must have a common column (up to 16 tables). Tables are normally selected using a join condition. Types of Clusters Index Clusters Have a single B-tree index storing the cluster key that is used to access all of the tables in the cluster. Hash Clusters stores pointers to specific rows within the tables. The pointers are created based upon a formula. Cluster Key based upon a common column contained by all of the tables in the cluster. All the columns must be of the same data type and length. 8

9 Advantages Of Clusters Reduce Disk I/O. Improve Access Time. Reduce Space Required for Indexes. Selects, Updates, and Deletes are Faster. Disadvantages Of Clusters More Rollback Data and Redo Log Data Generated. Inserts are Slower. Loading of Tables is Much Slower. Selecting From Individual Tables is Slower. 9

10 Attributes Of Good Cluster Table Candidates Table is Frequently Queried But Not Often Updated. Key Columns Contain Redundancy. Tables Usually Joined. Attributes Of Good Cluster Key Candidates Low Degree of Cardinality. Used to Join Multiple Tables. Cannot Be of LONG or LONG RAW Datatypes. 10

11 Use Hashing When: Tables Do Not Vary in Size. Optimizing Query Performance is the Only Objective. Key Columns are Numeric. Queries are Equality Queries on the Hashed Columns. The Hash Key is Well Distributed. Creating The Index Cluster SQL> connect jerry/welcome Connected. SQL> CREATE CLUSTER Emp_Cluster(Dept Varchar2(4)) 2 Size 75 3 TABLESPACE Data; SQL> CREATE INDEX Emp_Clu_Indx 2 ON CLUSTER Emp_Cluster 3 TABLESPACE INDEXES; Index created. 11

12 Adding Tables to the Index Cluster SQL> CREATE TABLE Dept_Table 2 (Dept Varchar2(4) Primary Key, 3 DName Varchar2(20)) 4 CLUSTER Emp_Cluster (Dept); Table created. SQL> CREATE TABLE Emp_Table 2 (ID Varchar2(4), 3 Name Varchar2(20), 4 Salary Number(6), 5 Dept Varchar2(4) References Dept_Table) 6 CLUSTER Emp_Cluster (Dept); Table created. Creating the Hash Cluster SQL> CREATE CLUSTER Emp_Hash_Cluster (Dept Number(4)) 2 Hashkeys TABLESPACE Data; Cluster created. SQL> CREATE TABLE Dept_HTable 2 (Dept Number(4) Primary Key, 3 DName Varchar2(20)) 4 CLUSTER Emp_Hash_Cluster (Dept); Table created. SQL> CREATE TABLE Emp_HTable 2 (ID Char(4) Primary Key, 3 Name Varchar2(20), 4 Dept Number(4) References Dept_HTable) 5 CLUSTER Emp_Hash_Cluster (Dept); Table created. 12

13 Viewing Clusters and Tables SQL> connect system/change_on_install Connected. SQL> Select Owner, Table_Name, 2 Cluster_Name, Cluster_Owner 3 From DBA_Tables 4 Where Owner = 'JERRY' 5 And Cluster_Name Is Not Null 6 Order By Cluster_Name; OWNER TABLE_NAME CLUSTER_NAME CLUSTER_OWNER JERRY DEPT_TABLE EMP_CLUSTER JERRY JERRY EMP_TABLE EMP_CLUSTER JERRY JERRY DEPT_HTABLE EMP_HASH_CLUSTER JERRY JERRY EMP_HTABLE EMP_HASH_CLUSTER JERRY Removing Clusters The following statement removes the cluster but the tables and constraints remain. SQL> DROP CLUSTER Emp_Cluster; The following statement removes the cluster and the tables. SQL> DROP CLUSTER Emp_Cluster 2 INCLUDING TABLES; The following statement removes the cluster and tables. It also removes all constraints that had been written on tables in the cluster. SQL> DROP CLUSTER Emp_Cluster 2 INCLUDING TABLES 3 CASCADE CONSTRAINTS; 13

14 EFFICIENT TABLES Partitioned Tables Partitioning tables allows you to store a single table in two or more separate partitions. This allows you to store a table on more than one tablespace and on more than one disk file. To create the partitioned table: Create the new tablespaces placing them on different disks, if possible. Create the table, partitioning the data based upon some criterion (name ranges, salary ranges, etc. 14

15 Partition by Range and List Partition By Range if you have continuous values such as a Salary. Partition By List if you have discrete values such as a list of Departments. Tablespaces for Partitioned Table SQL> Create Tablespace Emp_TS1 2 Datafile '/oraclec/data/db08/disk1/emp_ts101.dbf' 3 Size 10M 4 Uniform size 100K; Tablespace created. SQL> Create Tablespace Emp_TS1 2 Datafile '/oraclec/data/db08/disk2/emp_ts201.dbf' 3 Size 10M 4 Uniform size 100K; Tablespace Created. 15

16 Creating the Partitioned Table (Partition By Range) SQL> Create Table EMP 2 (ID Number(9) primary key, 3 Name Varchar2(20), 4 Salary Number(10,2), 5 Dept Varchar2(4)) 6 Partition by Range (Name) 7 (Partition EMP1 values less than ('N') 8 tablespace EMP_TS1, 9 Partition EMP2 values less than (maxvalue) 10 tablespace EMP_TS2); Table created. Creating the Partitioned Table (Partition By List) SQL> Create Table EMP 2 (ID Number(9) primary key, 3 Name Varchar2(20), 4 Salary Number(10,2), 5 Dept Varchar2(4)) 6 Partition by List (Dept) 7 (Partition EMP1 values ( MIS, ACC ) 8 tablespace EMP_TS1, 9 Partition EMP2 values ( MGT, FIN ) 10 tablespace EMP_TS2); Table created. 16

17 Indexed Organization Tables An Indexed Organization table (IOT) maintains the data sorted by the primary key of the table. Data may be entered in any order and the IOT will save the rows sorted according to the primary key values. An IOT should be used when: The table is a smaller lookup table. The table is frequently referenced as a foreign key in other tables. Creating the IOT SQL> CREATE TABLE Dept_IO (DeptNO Char(3) Primary Key, 2 DName Varchar2(30)) 3 ORGANIZATION INDEX; Table created. SQL> INSERT INTO Dept_IO VALUES 2 ('MIS', 'Management Info Systems'); 1 row created. SQL> INSERT INTO Dept_IO VALUES ('ACC', 'Accounting'); 1 row created. SQL> Select * From Dept_IO; DEP DNAME ACC Accounting MIS Management Info Systems Rows are ordered in the table even though the data were not entered in order. 17

18 INDEXING METHODS Index Row ID SQL> select id,name,salary,dept,rowid from emp; ID NAME SALARY DEPT ROWID Joe MIS AAAAwLAAHAAAAAKAAA 2 John ACC AAAAwLAAHAAAAAKAAB ROWID VALUE AAAAwL AAH AAAAAK AAA CODING Segment Identifier Data File Identifier. Data Block Identifier Row Identifier 18

19 Simple B-Tree Indexes Simple index on the Salary column. Unique index indicates no SSN values may be duplicated. Index on concatenated columns. SQL> Create Index emp_salary_index 2 on EMP(Salary) 3 tablespace Indexes; Index created. SQL> Create Unique Index emp_ssn_idx 2 on EMP(SSN) 3 tablespace Indexes; Index created. SQL> Create index emp_name_idx 2 on EMP(first last) 3 tablespace Indexes; Index created. Composite B-Tree Indexes Salary is indexed in descending order. Probably to sort data for a report. SQL> Create Index emp_salary_idx 2 on EMP(Salary DESC) 3 tablespace Indexes; Index created. Composite index indicates the presentation of Dept values in ascending order and Salary values in descending order. SQL> Create Index emp_report_idx 2 on EMP(Dept ASC, Salary DESC) 3 tablespace Indexes; Index created. 19

20 Reverse Indexes Use a Reverse Index if the column being indexed contains values that don t vary for the first several characters. For example, a company has employee id s that all be begin with the number 900). SQL> Create Index Emp_Dept_Idx 2 on EMP(Dept) Reverse 3 tablespace Indexes; Index created. Function Based Indexes The data are frequently queried as shown with the retrieval condition based upon a formula. SQL> Select Name, Salary * From EMP 3 Where Salary * 1.08 > 45000; An index on the Salary column will not be used against the query shown above. The index shown on the right is required. SQL> Create Index emp_raises_idx 2 on EMP(Salary * 1.08) 3 tablespace indexes; Index created. 20

21 Bitmap Indexes The data on the right reside in the EMP table. There will be a Bitmap Index created on the Dept column. ID NAME SALARY DEPT Joe MIS 2 John ACC 3 John MIS 4 John MGT 5 John ACC The Unique values of the Dept column become the rows of the Index. The columns of the Index are the rows of the table data. DEPT MIS ACC MGT SQL> Create Bitmap Index emp_dept_idx on EMP (Dept) 2 tablespace Indexes; Maintaining Indexes Whenever many inserts, updates, and deletes have occurred against an indexed table, the table s index should be rebuild periodically. The following query will rebuild the index and place it in the appropriate tablespace if the index has not been properly located. SQL> ALTER INDEX Emp_Dept_Idx 2 REBUILD 3 TABLESPACE Indexes; 21

22 Query Optimization Types of Query Optimization Rule Based the optimizer looks to an ordered set of rules and will use the method of highest priority to retrieve the data. Cost Based the optimizer evaluates the resource cost of extracting the data. A compute statistics or estimate statistics must have been run against all tables involved in the query to use this type of optimization. 22

23 Rule Based Optimization Rules indicate a set of precedence. The optimizer will use the access with the highest value, if found. Reading the results of Explain Plan is subjective. Order of Rules Order Type of Access. 1. Single Row by ROWID 2. Single row by cluster join 3. Single row by hash cluster key with unique or primary key. 4. Single row by unique or primary key. 5. Cluster join 6. Hash cluster key. 7. Indexed cluster key. 8. Composite index. 23

24 Order of Rules (cont.) Order Type of Access. 9. Single column index. 10. Bounded range search on indexed columns. 11. Unbounded range search on indexed columns. 12. Sort-merge join. 13. MAX() or MIN() of indexed column. 14. ORDER BY on indexed columns. 15. Full table scan. Using Explain Plan SQL> connect / as sysdba Connected. From SYS run the following script file. (Do this only once) Use the following statement to create an execution plan for a query. SQL> EXPLAIN PLAN 2 SET STATEMENT_ID = 'My_ID' FOR 3 SELECT...; The execution plan for your query will be in the SYS.PLAN_TABLE and identified with a Statement_ID = My_ID. 24

25 Cost Based Optimization Default optimization beginning with Oracle 8.0 Run Compute Statistics or Estimate Statistics on all tables used in the queries. Modify the initdb0x.ora to allow for cost based optimization. Use tkprof to read the resource cost statistics. Modifying The PFile. Edit the initdb0x.ora and add or change the following values. Save the file and shudown the database. Create the SPFile from the PFile and startup the database. MAX_DUMP_FILE_SIZE must be set to a value (in db blocks). TIMED_STATISTICS must be set to TRUE. USER_DUMP_DEST must contain a path/file name. If you want to generate Cost Statistics on all queries you enter, set the following value in the initdb0x.ora file. SQL_TRACE set to TRUE 25

26 Selective Cost Statistics If you want to generate cost statistics on only some queries, set SQL_TRACE = FALSE in the parameter file and turn SQL_TRACE on and off as shown below to generate the statistics. SQL> ALTER SESSION SET sql_trace = TRUE; Run the query (or queries) SQL> ALTER SESSION SET sql_trace = FALSE; Using tkprof Whenever you run a query with SQL_TRACE = TRUE, a trace file will be created with a name following the pattern ora_xxxx.trc. The tkprof utility program will convert the trace file to a file you can edit and read as show below. Note that tkprof is run from the O/S not SQL. [24]> tkprof ora_xxxx.trc ora_xxxx.log. 26

27 Supplying Hints to the Optimizer Using Hints Hints allow you to instruct the optimizer on how the query is to be executed. Hints may be used for INSERT, UPDATE, and DELETE statements and follow the structure below: SQL> Select /*+ hint */... The /* and */ represent the beginning and end of comments. The comment must be placed immediately after the SELECT, UPDATE or DELETE keyword. The + indicates a hint follows. The first character after the /* must be a +. Multiple hints may be placed in the comments. Syntax errors in a hint will cause the hint to be ignored. 27

28 Some Useful Hints Hint Description All_Rows First_Rows(n) Choose Rule INDEX (tname iname) NO_INDEX (tname iname) Ordered Retrieves all of the rows with the lowest possible resource cost. Retrieves the first n rows as quickly as possible. Requests Oracle to choose between Rule-Based or Cost-Based optimization. Requests Oracle to use Rule-Based optimization. Requests Oracle to use the iname index on the tname table. Requests that Oracle NOT use the iname index on the tname table. Requests Oracle to join the tables in the order in which they appear in the From clause Retrieve the first 6 rows from EMP as quickly as possible. Update all rows of EMP locating the rows using Rule- Based optimization Select all rows from EMP using the SAL_IDX index. Examples of Hints Select /*+ first_rows(6) */ * From EMP; UPDATE /*+ Rule */ EMP SET Salary = ; Select /*+ INDEX (EMP SAL_IDX) */ * From EMP; Join the Movie and Actor table in the order shown in the From statement. Select /*+ Ordered */ Mname,ActName From Movie a, Actor b,movact c Where a. MID = c.mid And b. AID = c.aic; 28

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