Peter Ramm's Oracle performance analysis stuff

Since release 18c there's an undocumented feature Parallel Shared Hash Join which introduces sharing memory between parallel query slaves. The required memory for these shared hash tables is allocated in a new memory region known as the Managed Global Area (MGA). See also doc. ID 2638904.1. This feature is particularly beneficial for costly HASH JOIN BUFFERED operations that spill large amounts of data into the temporary tablespace. These operations may benefit from transformation into HASH JOIN SHARED operations. By sharing hash tables between parallel query (PQ) processes, instead of each PQ server maintaining its own, runtime can be significantly reduced. This reduces overall memory requirements, enabling more data to be processed before spilling to disk in the temporary tablespace. There are several ways to activate the Parallel Shared Hash Join: set '_px_shared_hash_join'=true; at system or session level define the PQ distribution strategy for a particular

Recently a problem occured using function based indexes: The optimizer switched to full table scan on a table with 3.2 billion rows although the used function expression is covered by a function based index. The expression often evaluates to NULL ond so this index has only 4.9 million rows ( < 1% of the table rows ) and a low selectivity of approx. 4 rows per key. Let's consider the simple case. The table INVOICE has two interesting columns: - CUSTOMER_ID 38 mio distinct values, not null, avg. 84 rows/key - OPEN_AMOUNT not null, 4,8 mio. records > 0 A function based index was created to quickly identify the small portion of rows of a certain customer where the OPEN_AMOUNT is > 0 CREATE INDEX IX_OPENAMOUNT ON INVOICE(CASE WHEN Open_Amount > 0 THEN Customer_ID END); This SQL is used to select the rows of a certain customer where the OPEN_AMOUNT is > 0 SELECT ID FROM Invoice WHERE CASE WHEN Open_Amount > 0 THEN Customer_ID END = :B1 ; The executi

As of Oracle DB release 19.12 it is possible to use the new and the previous password for user logon simultaneously for a limited period. For details see New features guide . This is a great and long-awaited feature that lowers the barriers to changing passwords with less operational risk. But there's an obstacle for practical use: You must be able to monitor the users who are within this rollover period and are still using the old password. The only way of monitoring the use of old passwords known to me so far is to: Use Unified Auditing Create a policy for the LOGON action Check for the keyword "VERIFIER=12C-OLD" in the column AUTHENTICATION_TYPE of the logon records in unified audit trail. The following SQL provides an overview over all the users who are currently within a password rollover period, combined with info about old password usage: SELECT u.Account_Status, u.Password_Change_Date, u.Profile, u.UserName, u.Last_Login, a.DBUserName, a.

If you try to use parallel DML or direct load in SQL statements by placing the appropiate optimizer hints (PARALLEL, APPEND etc.), there might be several reasons why the DB ignores them. For example, if you want to execute DML in parallel you need to enable the session to do this before by executing ALTER SESSION ENABLE PARALLEL DML; . There are lots of similar pitfalls that may prevent the DB from using the expected execution path. The free performance analysis tool Panorama offers a way to scan your entire database for SQLs where parallel DML or direct load should have been used but in reality is not. Use the shown selection from menu "Dragnet investigation" (point 2.2.12) to execute this check and find SQLs that are not executed as expected. The result is sorted by the time this SQLs took to execute. The link in column "sql id" allows you to dig deeper in the details of the found SQL statement. Precondition is licensing of Oracle Diagnostics Pack or the u

The release 19.19 of the Oracle DB got the long awaited populating of Access_Predicates and Filter_Predicates in DBA_Hist_SQL_Plan (as backport from 21c). So far so good, after decades of complaints. But as the execution plans already stored in the AWR before 19.19 are without a time reference, Access_Predicates and Filter_Predicates for SQLs are not filled, as long as the plans from before 19.19 still exist. These plans are independent of the AWR retention time and therefore remain in the old state without Access_Predicates and Filter_Predicates forever as long as the SQLs are still contained in upcoming AWR snapshots. A solution for that behaviour is, to manually remove the old plans to trigger storage of current plans from SGA again. If executed once as SYSDBA, this script deletes all the execution plans saved in the AWR for which the Access_Predicates and Filter_Predicates columns are not filled. These plans will be saved again from SGA with the next AWR snapshots, but then

Some times a SQL execution includes all partitions of a partitioned table or index into processing, although there are filter conditions used that contain also the partition key of that partitoned table or index. There are several possible reasons why the optimizer does not recognize that access could be reduced to one or less partitions (a.k.a. partition pruning): The partition key can be obfuscated behind a conversion function The partition key can be compared to a function result that is known only at execution time Being able to use partition pruning can make a huge difference for execution time of the SQL. Imagine you only need to scan one partition of a table instead of several thousands. Often only a small change in the SQL statement can drive the optimizer to use partition pruning. A small example where all partitions are scanned due to comparison of the partition key with a function result: Get the sum of order value for a table interval partitioned by day. SELE

What does the database really do with your optimizer hints in SQL statements? Starting with Oracle 19c the column 'OTHER_XML' of V$SQL_Plan rsp. DBA_Hist_SQL_Plan or Plan_Table was extended by a section 'hint_usage'. This gives information about the state of optimizer hint usage correlated with the line in the execution plan. Example for section 'hint_usage' of OTHER_XML Lets take this simple but useless SQL as example: SELECT /*+ FULL(c) QB_NAME(Outer) NONSENS(c) */ * FROM cust.Customer c WHERE ID_Company IN ( SELECT /*+ USE_NL(cp) QB_NAME(Inner) */ 12 FROM sysp.Company cp WHERE RowNum < 5 ) AND RowNum < 20; The section 'hint_usage' in PLAN_TABLE.OTHER_XML looks like for this example: <hint_usage> <q> <n><![CDATA[INNER]]></n> <h o="EM"> <x><![CDATA[QB_NAME(Inner)]]></x> </h> <

The performance analysis tool Panorama for Oracle now supports both evaluation of standard audit trail as well as evaluation of unified audit trail. The menu item "DBA General" / "Audit Trail" / "Auditing rules" shows the current configuration of the DB audit trail as well as several auditing rules for standard, fine grained and unified audit trail. With menu item "DBA General" / "Audit Trail" / "Standard audit trail" you open a dialog for evaluation of standard audit trail including find grained audit trail. Depending on the choosen value for "Grouping" single audit records are show for the selected period or the result is grouped by time with record counts for the top x OS and DB users, machines and actions. By clicking at the links in the columns for "Action", "Machine", "User" etc. you can refine the grouped result. Clicking at the column "Audits total" shows the s

Consider the following requirement: There are two tables. Table MASTER is referenced from table DETAIL. CREATE TABLE Master ( ID NUMBER PRIMARY KEY , Company_ID NUMBER ); CREATE TABLE Detail ( ID NUMBER GENERATED BY DEFAULT ON NULL AS IDENTITY PRIMARY KEY, Master_ID NUMBER REFERENCES Master(ID), Value NUMBER ); The content of the table DETAIL should be unique in a combination of two values: the column DETAIL.VALUE and the column MASTER.COMPANY_ID from a directly referenced table. Each column of this tables except the primary key columns can be changed. Limits of solution approach with function based index A first thought when securing uniqueness across table boundaries is often the use of function based indexes with a function that selects the second value from the referenced table. CREATE OR REPLACE FUNCTION Get_Company_ID(p_Master_ID IN NUMBER) RETURN NUMBER DETERMINISTIC IS v_Company_ID NUMBER; BEGIN SELECT Company_ID INTO v_Comp

The most efficient way of processing GROUP BY or SORT operations is often if they are executed only at the really necessary DB objects and the smallest number of rows and columns.  The optimizer itself tends to move GROUP BY and SORT operations out to the last operation of a SQL, thus executing these operations on larger data sets than necessary.  One way to improve that is to use the so called VIEW_PUSHED_PREDICATE feature forced by the NO_MERGE hint. Prepare example task You have two tables ORDER and POSITION. CREATE TABLE Orders ( ID NUMBER, Customer_ID NUMBER, CreationDate DATE ); INSERT INTO Orders SELECT Level, dbms_random.random, SYSDATE - Level/10000.0 FROM DUAL CONNECT BY Level <= 1000000 ; COMMIT; ALTER TABLE Orders ADD CONSTRAINT Orders_PK PRIMARY KEY (ID); CREATE INDEX Order_Customer ON Orders(Customer_ID); EXEC DBMS_Stats.Gather_Table_Stats(SYS_CONTEXT('USERENV', 'SESSION_USER'), 'ORDERS'); CREATE TABLE Positions ( Order_ID