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• SQL Constraints &ndash; CHECK and NOCHECK

  - by David Turner

  One performance issue i faced at a recent project was with the way that our constraints were being managed, we were using Subsonic as our ORM, and it has a useful tool for generating your ORM code called SubStage – once configured, you can regenerate your DAL code easily based on your database schema, and it can even be integrated into your build as a pre-build event if you want to do this.  SubStage also offers the useful feature of being able to generate DDL scripts for your entire database, and can script your data for you too. The problem came when we decided to use the generate scripts feature to migrate the database onto a test database instance – it turns out that the DDL scripts that it generates include the WITH NOCHECK option, so when we executed them on the test instance, and performed some testing, we found that performance wasn’t as expected. A constraint can be disabled, enabled but not trusted, or enabled and trusted.  When it is disabled, data can be inserted that violates the constraint because it is not being enforced, this is useful for bulk load scenarios where performance is important.  So what does it mean to say that a constraint is trusted or not trusted?  Well this refers to the SQL Server Query Optimizer, and whether it trusts that the constraint is valid.  If it trusts the constraint then it doesn’t check it is valid when executing a query, so the query can be executed much faster. Here is an example base in this article on TechNet, here we create two tables with a Foreign Key constraint between them, and add a single row to each.  We then query the tables: 1 DROP TABLE t2 2 DROP TABLE t1 3 GO 4 5 CREATE TABLE t1(col1 int NOT NULL PRIMARY KEY) 6 CREATE TABLE t2(col1 int NOT NULL) 7 8 ALTER TABLE t2 WITH CHECK ADD CONSTRAINT fk_t2_t1 FOREIGN KEY(col1) 9 REFERENCES t1(col1) 10 11 INSERT INTO t1 VALUES(1) 12 INSERT INTO t2 VALUES(1) 13 GO14 15 SELECT COUNT(*) FROM t2 16 WHERE EXISTS17 (SELECT *18 FROM t1 19 WHERE t1.col1 = t2.col1) This all works fine, and in this scenario the constraint is enabled and trusted.  We can verify this by executing the following SQL to query the ‘is_disabled’ and ‘is_not_trusted’ properties: 1 select name, is_disabled, is_not_trusted from sys.foreign_keys This gives the following result: We can disable the constraint using this SQL: 1 alter table t2 NOCHECK CONSTRAINT fk_t2_t1 And when we query the constraints again, we see that the constraint is disabled and not trusted: So the constraint won’t be enforced and we can insert data into the table t2 that doesn’t match the data in t1, but we don’t want to do this, so we can enable the constraint again using this SQL: 1 alter table t2 CHECK CONSTRAINT fk_t2_t1 But when we query the constraints again, we see that the constraint is enabled, but it is still not trusted: This means that the optimizer will check the constraint each time a query is executed over it, which will impact the performance of the query, and this is definitely not what we want, so we need to make the constraint trusted by the optimizer again.  First we should check that our constraints haven’t been violated, which we can do by running DBCC: 1 DBCC CHECKCONSTRAINTS (t2) Hopefully you see the following message indicating that DBCC completed without finding any violations of your constraint: Having verified that the constraint was not violated while it was disabled, we can simply execute the following SQL:   1 alter table t2 WITH CHECK CHECK CONSTRAINT fk_t2_t1 At first glance this looks like it must be a typo to have the keyword CHECK repeated twice in succession, but it is the correct syntax and when we query the constraints properties, we find that it is now trusted again: To fix our specific problem, we created a script that checked all constraints on our tables, using the following syntax: 1 ALTER TABLE t2 WITH CHECK CHECK CONSTRAINT ALL

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• Non use of persisted data

  - by Dave Ballantyne

  Working at a client site, that in itself is good to say, I ran into a set of circumstances that made me ponder, and appreciate, the optimizer engine a bit more. Working on optimizing a stored procedure, I found a piece of code similar to : select BillToAddressID, Rowguid, dbo.udfCleanGuid(rowguid) from sales.salesorderheaderwhere BillToAddressID = 985 A lovely scalar UDF was being used,  in actuality it was used as part of the WHERE clause but simplified here.  Normally I would use an inline table valued function here, but in this case it wasn't a good option. So this seemed like a pretty good case to use a persisted column to improve performance. The supporting index was already defined as create index idxBill on sales.salesorderheader(BillToAddressID) include (rowguid) and the function code is Create Function udfCleanGuid(@GUID uniqueidentifier)returns varchar(255)with schemabindingasbegin Declare @RetStr varchar(255) Select @RetStr=CAST(@Guid as varchar(255)) Select @RetStr=REPLACE(@Retstr,'-','') return @RetStrend Executing the Select statement produced a plan of : Nothing surprising, a seek to find the data and compute scalar to execute the UDF. Lets get optimizing and remove the UDF with a persisted column Alter table sales.salesorderheaderadd CleanedGuid as dbo.udfCleanGuid(rowguid)PERSISTED A subtle change to the SELECT statement… select BillToAddressID,CleanedGuid from sales.salesorderheaderwhere BillToAddressID = 985 and our new optimized plan looks like… Not a lot different from before!  We are using persisted data on our table, where is the lookup to fetch it ?  It didnt happen,  it was recalculated.  Looking at the properties of the relevant Compute Scalar would confirm this ,  but a more graphic example would be shown in the profiler SP:StatementCompleted event. Why did the lookup happen ? Remember the index definition,  it has included the original guid to avoid the lookup.  The optimizer knows this column will be passed into the UDF, run through its logic and decided that to recalculate is cheaper than the lookup.  That may or may not be the case in actuality,  the optimizer has no idea of the real cost of a scalar udf.  IMO the default cost of a scalar UDF should be seen as a lot higher than it is, since they are invariably higher. Knowing this, how do we avoid the function call?  Dropping the guid from the index is not an option, there may be other code reliant on it.   We are left with only one real option,  add the persisted column into the index. drop index Sales.SalesOrderHeader.idxBillgocreate index idxBill on sales.salesorderheader(BillToAddressID) include (rowguid,cleanedguid) Now if we repeat the statement select BillToAddressID,CleanedGuid from sales.salesorderheaderwhere BillToAddressID = 985 We still have a compute scalar operator, but this time it wasnt used to recalculate the persisted data.  This can be confirmed with profiler again. The takeaway here is,  just because you have persisted data dont automatically assumed that it is being used.

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• ?12c database ????Adaptive Execution Plans ????????

  - by Liu Maclean(???)

  12c R1 ????SQL??????- Adaptive Execution Plans ????????,???????optimizer ??????(runtime)???????????????, ????????????????????? SQL???????? ????????????, ?????????????????????????????????????????????????????????????adaptive plan ????????????????????????????????????,?????subplan???????????????????? ??????, ???????? ???????????????,?????????, ?????? ???????????????”???”????, ???????????????????buffer ???????  ????????????,?????,??????????????????? ???optimizer ?????????????????????????,?????????????????????????????????????????plan???? ??12C?????????????, ???????????????????,?????? ???????????? ????????????2???: Dynamic Plans????: ???????????????????????;??????,???optimizer??????????subplans??????????????, ???????????????????,?????????????? Reoptimization????: ?Dynamic Plans????,Reoptimization??????????????????????Reoptimization??,?????????????????????????,??reoptimization????? OPTIMIZER_ADAPTIVE_REPORTING_ONLY ???? report-only????????????????TRUE,?????????report-only????,???????????????,??????????????? Dynamic Plans ??????????????,????????????????????????, ?????????????,???????????,????????????????????????????????????????? ?????????????final plan??????????????default plan, ??final plan?default plan???????,????????????? subplan ???????????????,???????????????????????? ??????,???????statistics collector ?buffer???????????statistics collector?????????????????,???????????????????????????? ?????????????????????????????????????????,??????????,?????????????? ???????????,???????buffer???? ???????????????,?????????????????????????????,??????buffer,??????final plan? ????????,???????????????????????,????????????????? ?V$SQL??????IS_RESOLVED_DYNAMIC_PLAN??????????final plan???default plan? ??????dynamic plan ???????SQL PLAN directives?????? declare cursor PLAN_DIRECTIVE_IDS is select directive_id from DBA_SQL_PLAN_DIRECTIVES; begin for z in PLAN_DIRECTIVE_IDS loop DBMS_SPD.DROP_SQL_PLAN_DIRECTIVE(z.directive_id); end loop; end; / explain plan for select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; select * from table(dbms_xplan.display()); Plan hash value: 1255158658 www.askmaclean.com ------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 4 | 128 | 7 (0)| 00:00:01 | | 1 | NESTED LOOPS | | | | | | | 2 | NESTED LOOPS | | 4 | 128 | 7 (0)| 00:00:01 | |* 3 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 (0)| 00:00:01 | |* 4 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK | 1 | | 0 (0)| 00:00:01 | | 5 | TABLE ACCESS BY INDEX ROWID| PRODUCT_INFORMATION | 1 | 20 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("O"."UNIT_PRICE"=15 AND "QUANTITY">1) 4 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") alter session set events '10053 trace name context forever,level 1'; OR alter session set events 'trace[SQL_Plan_Directive] disk highest'; select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; ---------------------------------------------------------------+-----------------------------------+ | Id | Operation | Name | Rows | Bytes | Cost | Time | ---------------------------------------------------------------+-----------------------------------+ | 0 | SELECT STATEMENT | | | | 7 | | | 1 | HASH JOIN | | 4 | 128 | 7 | 00:00:01 | | 2 | NESTED LOOPS | | | | | | | 3 | NESTED LOOPS | | 4 | 128 | 7 | 00:00:01 | | 4 | STATISTICS COLLECTOR | | | | | | | 5 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 | 00:00:01 | | 6 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK| 1 | | 0 | | | 7 | TABLE ACCESS BY INDEX ROWID | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | | 8 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | ---------------------------------------------------------------+-----------------------------------+ Predicate Information: ---------------------- 1 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") 5 - filter(("O"."UNIT_PRICE"=15 AND "QUANTITY">1)) 6 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") ===================================== SPD: BEGIN context at statement level ===================================== Stmt: ******* UNPARSED QUERY IS ******* SELECT /*+ OPT_ESTIMATE (@"SEL$1" JOIN ("P"@"SEL$1" "O"@"SEL$1") ROWS=13.000000 ) OPT_ESTIMATE (@"SEL$1" TABLE "O"@"SEL$1" ROWS=13.000000 ) */ "P"."PRODUCT_NAME" "PRODUCT_NAME" FROM "OE"."ORDER_ITEMS" "O","OE"."PRODUCT_INFORMATION" "P" WHERE "O"."UNIT_PRICE"=15 AND "O"."QUANTITY">1 AND "P"."PRODUCT_ID"="O"."PRODUCT_ID" Objects referenced in the statement PRODUCT_INFORMATION[P] 92194, type = 1 ORDER_ITEMS[O] 92197, type = 1 Objects in the hash table Hash table Object 92197, type = 1, ownerid = 6573730143572393221: No Dynamic Sampling Directives for the object Hash table Object 92194, type = 1, ownerid = 17822962561575639002: No Dynamic Sampling Directives for the object Return code in qosdInitDirCtx: ENBLD =================================== SPD: END context at statement level =================================== ======================================= SPD: BEGIN context at query block level ======================================= Query Block SEL$1 (#0) Return code in qosdSetupDirCtx4QB: NOCTX ===================================== SPD: END context at query block level ===================================== SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Inserted felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: qosdCreateFindingSingTab retCode = CREATED, fid = 2896834833840853267 SPD: qosdCreateDirCmp retCode = CREATED, fid = 2896834833840853267 SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SKIP_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Modified felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 5618517328604016300 SPD: Modified felem, fid=5618517328604016300, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 1142802697078608149 SPD: Modified felem, fid=1142802697078608149, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 2, objcnt = 2, obItr = 0, objid = 92194, objtyp = 1, vecsize = 0, obItr = 1, objid = 92197, objtyp = 1, vecsize = 0, fid = 1437680122701058051 SPD: Modified felem, fid=1437680122701058051, ftype = 1, freason = 2, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO select * from table(dbms_xplan.display_cursor(format=>'report')) ; ????report????adaptive plan Adaptive plan: ------------- This cursor has an adaptive plan, but adaptive plans are enabled for reporting mode only.  The plan that would be executed if adaptive plans were enabled is displayed below. ------------------------------------------------------------------------------------------ | Id  | Operation          | Name                | Rows  | Bytes | Cost (%CPU)| Time     | ------------------------------------------------------------------------------------------ |   0 | SELECT STATEMENT   |                     |       |       |     7 (100)|          | |*  1 |  HASH JOIN         |                     |     4 |   128 |     7   (0)| 00:00:01 | |*  2 |   TABLE ACCESS FULL| ORDER_ITEMS         |     4 |    48 |     3   (0)| 00:00:01 | |   3 |   TABLE ACCESS FULL| PRODUCT_INFORMATION |     1 |    20 |     1   (0)| 00:00:01 | ------------------------------------------------------------------------------------------ SQL> select SQL_ID,IS_RESOLVED_DYNAMIC_PLAN,sql_text from v$SQL WHERE SQL_TEXT like '%MALCEAN%' and sql_text not like '%like%'; SQL_ID IS -------------------------- -- SQL_TEXT -------------------------------------------------------------------------------- 6ydj1bn1bng17 Y select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id ???? explain plan for ????default plan, ??????optimizer???final plan,??V$SQL.IS_RESOLVED_DYNAMIC_PLAN???Y,????????????? DBA_SQL_PLAN_DIRECTIVES?????????????SQL PLAN DIRECTIVES, ???12c? ???MMON?????DML ???column usage??????????,????SMON??? MMON????SGA??PLAN DIRECTIVES??? ?????DBMS_SPD.flush_sql_plan_directive???? select directive_id,type,reason from DBA_SQL_PLAN_DIRECTIVES / DIRECTIVE_ID TYPE REASON ----------------------------------- -------------------------------- ----------------------------- 10321283028317893030 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 4757086536465754886 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 16085268038103121260 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE SQL> set pages 9999 SQL> set lines 300 SQL> col state format a5 SQL> col subobject_name format a11 SQL> col col_name format a11 SQL> col object_name format a13 SQL> select d.directive_id, o.object_type, o.object_name, o.subobject_name col_name, d.type, d.state, d.reason 2 from dba_sql_plan_directives d, dba_sql_plan_dir_objects o 3 where d.DIRECTIVE_ID=o.DIRECTIVE_ID 4 and o.object_name in ('ORDER_ITEMS') 5 order by d.directive_id; DIRECTIVE_ID OBJECT_TYPE OBJECT_NAME COL_NAME TYPE STATE REASON ------------ ------------ ------------- ----------- -------------------------------- ----- ------------------------------------- --- 1.8156E+19 COLUMN ORDER_ITEMS UNIT_PRICE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 TABLE ORDER_ITEMS DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 COLUMN ORDER_ITEMS QUANTITY DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE DBA_SQL_PLAN_DIRECTIVES????? _BASE_OPT_DIRECTIVE ? _BASE_OPT_FINDING SELECT d.dir_own#, d.dir_id, d.f_id, decode(type, 1, 'DYNAMIC_SAMPLING', 'UNKNOWN'), decode(state, 1, 'NEW', 2, 'MISSING_STATS', 3, 'HAS_STATS', 4, 'CANDIDATE', 5, 'PERMANENT', 6, 'DISABLED', 'UNKNOWN'), decode(bitand(flags, 1), 1, 'YES', 'NO'), cast(d.created as timestamp), cast(d.last_modified as timestamp), -- Please see QOSD_DAYS_TO_UPDATE and QOSD_PLUS_SECONDS for more details -- about 6.5 cast(d.last_used as timestamp) - NUMTODSINTERVAL(6.5, 'day') FROM sys.opt_directive$ d ??dbms_spd??? SQL PLAN DIRECTIVES, SQL PLAN DIRECTIVES???retention ???53?: Package: DBMS_SPD This package provides subprograms for managing Sql Plan Directives(SPD). SPD are objects generated automatically by Oracle server. For example, if server detects that the single table cardinality estimated by optimizer is off from the actual number of rows returned when accessing the table, it will automatically create a directive to do dynamic sampling for the table. When any Sql statement referencing the table is compiled, optimizer will perform dynamic sampling for the table to get more accurate estimate. Notes: DBMSL_SPD is a invoker-rights package. The invoker requires ADMINISTER SQL MANAGEMENT OBJECT privilege for executing most of the subprograms of this package. Also the subprograms commit the current transaction (if any), perform the operation and commit it again. DBA view dba_sql_plan_directives shows all the directives created in the system and the view dba_sql_plan_dir_objects displays the objects that are included in the directives. -- Default value for SPD_RETENTION_WEEKS SPD_RETENTION_WEEKS_DEFAULT CONSTANT varchar2(4) := '53'; | STATE : NEW : Newly created directive. | : MISSING_STATS : The directive objects do not | have relevant stats. | : HAS_STATS : The objects have stats. | : PERMANENT : A permanent directive. Server | evaluated effectiveness and these | directives are useful. | | AUTO_DROP : YES : Directive will be dropped | automatically if not | used for SPD_RETENTION_WEEKS. | This is the default behavior. | NO : Directive will not be dropped | automatically. Procedure: flush_sql_plan_directive This procedure allows manually flushing the Sql Plan directives that are automatically recorded in SGA memory while executing sql statements. The information recorded in SGA are periodically flushed by oracle background processes. This procedure just provides a way to flush the information manually. ????”_optimizer_dynamic_plans”(enable dynamic plans)????????,???TRUE??DYNAMIC PLAN? ???FALSE???????????? ????,Dynamic Plan????????????Nested Loop?Hash Join???case ,????????Nested loop???????????HASH JOIN,?HASH JOIN????????????????? ????????subplan?????,???? pass?? ?join method???,?????STATISTICS COLLECTOR???cardinality?,???????HASH JOIN?????Nested Loop,????????????subplan?????access path; ???????Sales??????????????????,????HASH JOIN,??SUBPLAN??customers?????????;?????Nested Loop,???????cust_id?????Range Scan+Access by Rowid? Cardinality feedback Cardinality feedback????????11.2????,????????re-optimization???;  ???????????,Cardinality feedback?????????????????????????? ???????????????????,?????????????????,??????????Cardinality feedback????????????? ????????????????????????? ??????????????Cardinality feedback ??: ????????,???????????,??????????,????????????????selectivity ??? ????????????: ??????,?????????????????????????????????,??????????????????? ????????????????????????????????????????,?????????????????????????? ?????????,???????????????,?????????? ??????????Cardinality ????,??????join Cardinality ????????? Cardinality feedback???????cursor?,?Cursor???aged out????? SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ---------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | ---------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | 20 | | | | |* 1 | HASH JOIN | | 1 | 4 | 13 |00:00:00.01 | 24 | 20 | 2061K| 2061K| 429K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 4 | 13 |00:00:00.01 | 7 | 6 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 1 | 288 |00:00:00.01 | 17 | 14 | | | | ---------------------------------------------------------------------------------------------------------------------------------------- SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | | | | |* 1 | HASH JOIN | | 1 | 13 | 13 |00:00:00.01 | 24 | 2061K| 2061K| 413K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 13 | 13 |00:00:00.01 | 7 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 288 | 288 |00:00:00.01 | 17 | | | | ------------------------------------------------------------------------------------------------------------------------------- Note ----- - statistics feedback used for this statement SQL> select count(*) from v$SQL where SQL_ID='cz0hg2zkvd10y'; COUNT(*) ---------- 2 SQL>select sql_ID,USE_FEEDBACK_STATS FROM V$SQL_SHARED_CURSOR where USE_FEEDBACK_STATS ='Y'; SQL_ID U ------------- - cz0hg2zkvd10y Y ????????Cardinality feedback????,???????????????????????????,????????????order_items???????? ????2??????plan hash value??(??????????),?????2????child cursor??????gather_plan_statistics???actual : A-ROWS  estimate :E-ROWS????????? Automatic Re-optimization ???dynamic plan, Re-optimization???????????????  ?  ??????????????? ????????????????????????????????  ???????????,??????????????, ???????????????????? ???????????  Re-optimization??, ????????????????????? Re-optimization????dynamic plan??????????  dynamic plan????????????????????, ???????????????????? ????,??????????join order ??????????????,?????????????join order????? ??????,????????Re-optimization, ??Re-optimization ??????????????????? ?Oracle database 12c?,join statistics?????????????????????,??????????????????????Re-optimization???????????adaptive cursor sharing????? ????????????????,???????????? ????? ???????statistics collectors ????????????????????Re-optimization??????2?????????????,???????????????? ??????????????Re-optimization?????,?????????????????????? ???v$SQL??????IS_REOPTIMIZABLE?????????????????????Re-optimization,??????????Re-optimization???,?????Re-optimization ,???????reporting????? IS_REOPTIMIZABLE VARCHAR2(1) This columns shows whether the next execution matching this child cursor will trigger a reoptimization. The values are:   Y: If the next execution will trigger a reoptimization R: If the child cursor contains reoptimization information, but will not trigger reoptimization because the cursor was compiled in reporting mode N: If the child cursor has no reoptimization information ??1: select plan_table_output from table (dbms_xplan.display_cursor('gwf99gfnm0t7g',NULL,'ALLSTATS LAST')); SQL_ID  gwf99gfnm0t7g, child number 0 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 1906736282 ------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation             | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT      |                     |      1 |        |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   1 |  NESTED LOOPS         |                     |      1 |      1 |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   2 |   MERGE JOIN CARTESIAN|                     |      1 |      4 |   9135 |00:00:00.02 |      34 |     15 |       |       |          | |*  3 |    TABLE ACCESS FULL  | PRODUCT_INFORMATION |      1 |      1 |     87 |00:00:00.01 |      33 |     14 |       |       |          | |   4 |    BUFFER SORT        |                     |     87 |    105 |   9135 |00:00:00.01 |       1 |      1 |  4096 |  4096 | 4096  (0)| |   5 |     INDEX FULL SCAN   | ORDER_PK            |      1 |    105 |    105 |00:00:00.01 |       1 |      1 |       |       |          | |*  6 |   INDEX UNIQUE SCAN   | ORDER_ITEMS_UK      |   9135 |      1 |    269 |00:00:00.01 |    1302 |      3 |       |       |          | ------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    6 - access("O"."ORDER_ID"="ORDER_ID" AND "P"."PRODUCT_ID"="O"."PRODUCT_ID") SQL_ID  gwf99gfnm0t7g, child number 1 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 35479787 -------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation              | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | -------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT       |                     |      1 |        |    269 |00:00:00.01 |      63 |      3 |       |       |          | |   1 |  NESTED LOOPS          |                     |      1 |    269 |    269 |00:00:00.01 |      63 |      3 |       |       |          | |*  2 |   HASH JOIN            |                     |      1 |    313 |    269 |00:00:00.01 |      42 |      3 |  1321K|  1321K| 1234K (0)| |*  3 |    TABLE ACCESS FULL   | PRODUCT_INFORMATION |      1 |     87 |     87 |00:00:00.01 |      16 |      0 |       |       |          | |   4 |    INDEX FAST FULL SCAN| ORDER_ITEMS_UK      |      1 |    665 |    665 |00:00:00.01 |      26 |      3 |       |       |          | |*  5 |   INDEX UNIQUE SCAN    | ORDER_PK            |    269 |      1 |    269 |00:00:00.01 |      21 |      0 |       |       |          | -------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    2 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID")    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    5 - access("O"."ORDER_ID"="ORDER_ID") Note -----    - statistics feedback used for this statement    SQL> select IS_REOPTIMIZABLE,child_number FROM V$SQL  A where A.SQL_ID='gwf99gfnm0t7g'; IS CHILD_NUMBER -- ------------ Y             0 N             1    1* select child_number,other_xml From v$SQL_PLAN  where SQL_ID='gwf99gfnm0t7g' and other_xml is not nul SQL> / CHILD_NUMBER OTHER_XML ------------ --------------------------------------------------------------------------------            1 <other_xml><info type="cardinality_feedback">yes</info><info type="db_version">1              2.1.0.1</info><info type="parse_schema"><![CDATA["OE"]]></info><info type="plan_              hash">35479787</info><info type="plan_hash_2">3382491761</info><outline_data><hi              nt><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]></hint><hint><![CDATA[OPTIMIZER_FEATUR              ES_ENABLE('12.1.0.1')]]></hint><hint><![CDATA[DB_VERSION('12.1.0.1')]]></hint><h              int><![CDATA[ALL_ROWS]]></hint><hint><![CDATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></              hint><hint><![CDATA[MERGE(@"SEL$2")]]></hint><hint><![CDATA[OUTLINE(@"SEL$1")]]>              </hint><hint><![CDATA[OUTLINE(@"SEL$2")]]></hint><hint><![CDATA[FULL(@"SEL$F5BB7              4E1" "P"@"SEL$2")]]></hint><hint><![CDATA[INDEX_FFS(@"SEL$F5BB74E1" "O"@"SEL$2"              ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PRODUCT_ID"))]]></hint><hint><![CDATA[I              NDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA[              LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$2" "O"@"SEL$1")]]></hint><hint><![C              DATA[USE_HASH(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint><hint><![CDATA[USE_NL(@"SEL$              F5BB74E1" "O"@"SEL$1")]]></hint></outline_data></other_xml>            0 <other_xml><info type="db_version">12.1.0.1</info><info type="parse_schema"><![C              DATA["OE"]]></info><info type="plan_hash">1906736282</info><info type="plan_hash              _2">2579473118</info><outline_data><hint><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]>              </hint><hint><![CDATA[OPTIMIZER_FEATURES_ENABLE('12.1.0.1')]]></hint><hint><![CD              ATA[DB_VERSION('12.1.0.1')]]></hint><hint><![CDATA[ALL_ROWS]]></hint><hint><![CD              ATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></hint><hint><![CDATA[MERGE(@"SEL$2")]]></hi              nt><hint><![CDATA[OUTLINE(@"SEL$1")]]></hint><hint><![CDATA[OUTLINE(@"SEL$2")]]>              </hint><hint><![CDATA[FULL(@"SEL$F5BB74E1" "P"@"SEL$2")]]></hint><hint><![CDATA[              INDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA              [INDEX(@"SEL$F5BB74E1" "O"@"SEL$2" ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PROD              UCT_ID"))]]></hint><hint><![CDATA[LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$1              " "O"@"SEL$2")]]></hint><hint><![CDATA[USE_MERGE_CARTESIAN(@"SEL$F5BB74E1" "O"@"              SEL$1")]]></hint><hint><![CDATA[USE_NL(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint></o              utline_data></other_xml> ??2: SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 0 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 -------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | -------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | 14 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 8 | 29 |00:00:00.01 | 17 | 14 | -------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OWNER OBJECT_NAME COL_NAME OBJECT TYPE STATE REASON ----------------------- ----- ------------- ----------- ------ ---------------- ----- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; ELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 1 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 ----------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | ----------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 29 | 29 |00:00:00.01 | 17 | ----------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) Note ----- - cardinality feedback used for this statement SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' b74nw722wjvy3 1 select /*+g N ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' SELECT /*+gather_plan_statistics*/ CUST_EMAIL FROM CUSTOMERS WHERE CUST_STATE_PROVINCE='MA' AND COUNTRY_ID='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID 3tk6hj3nkcs2u, child number 0 ------------------------------------- Select /*+gather_plan_statistics*/ cust_email From customers Where cust_state_province='MA' And country_id='US' Plan hash value: 1683234692 ------------------------------------------------------------------------------- |Id | Operation | Name | Starts|E-Rows|A-Rows| A-Time |Buffers| ------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 2 |00:00:00.01| 16 | |*1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 2| 2 |00:00:00.01| 16 | ----------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='MA' AND "COUNTRY_ID"='US')) Note ----- - dynamic sampling used for this statement (level=2) - 1 Sql Plan Directive used for this statement EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OW OBJECT_NA COL_NAME OBJECT TYPE STATE REASON ------------------- -- --------- ---------- ------- --------------- ------------- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE

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• SQL SERVER – SQL in Sixty Seconds – 5 Videos from Joes 2 Pros Series – SQL Exam Prep Series 70-433

  - by pinaldave

  Joes 2 Pros SQL Server Learning series is indeed fun. Joes 2 Pros series is written for beginners and who wants to build expertise for SQL Server programming and development from fundamental. In the beginning of the series author Rick Morelan is not shy to explain the simplest concept of how to open SQL Server Management Studio. Honestly the book starts with that much basic but as it progresses further Rick discussing about various advanced concepts from query tuning to Core Architecture. This five part series is written with keeping SQL Server Exam 70-433. Instead of just focusing on what will be there in exam, this series is focusing on learning the important concepts thoroughly. This book no way take short cut to explain any concepts and at times, will go beyond the topic at length. The best part is that all the books has many companion videos explaining the concepts and videos. Every Wednesday I like to post a video which explains something in quick few seconds. Today we will go over five videos which I posted in my earlier posts related to Joes 2 Pros series. Introduction to XML Data Type Methods – SQL in Sixty Seconds #015 The XML data type was first introduced with SQL Server 2005. This data type continues with SQL Server 2008 where expanded XML features are available, most notably is the power of the XQuery language to analyze and query the values contained in your XML instance. There are five XML data type methods available in SQL Server 2008: query() – Used to extract XML fragments from an XML data type. value() – Used to extract a single value from an XML document. exist() – Used to determine if a specified node exists. Returns 1 if yes and 0 if no. modify() – Updates XML data in an XML data type. node() – Shreds XML data into multiple rows (not covered in this blog post). [Detailed Blog Post] | [Quiz with Answer] Introduction to SQL Error Actions – SQL in Sixty Seconds #014 Most people believe that when SQL Server encounters an error severity level 11 or higher the remaining SQL statements will not get executed. In addition, people also believe that if any error severity level of 11 or higher is hit inside an explicit transaction, then the whole statement will fail as a unit. While both of these beliefs are true 99% of the time, they are not true in all cases. It is these outlying cases that frequently cause unexpected results in your SQL code. To understand how to achieve consistent results you need to know the four ways SQL Error Actions can react to error severity levels 11-16: Statement Termination – The statement with the procedure fails but the code keeps on running to the next statement. Transactions are not affected. Scope Abortion – The current procedure, function or batch is aborted and the next calling scope keeps running. That is, if Stored Procedure A calls B and C, and B fails, then nothing in B runs but A continues to call C. @@Error is set but the procedure does not have a return value. Batch Termination – The entire client call is terminated. XACT_ABORT – (ON = The entire client call is terminated.) or (OFF = SQL Server will choose how to handle all errors.) [Detailed Blog Post] | [Quiz with Answer] Introduction to Basics of a Query Hint – SQL in Sixty Seconds #013 Query hints specify that the indicated hints should be used throughout the query. Query hints affect all operators in the statement and are implemented using the OPTION clause. Cautionary Note: Because the SQL Server Query Optimizer typically selects the best execution plan for a query, it is highly recommended that hints be used as a last resort for experienced developers and database administrators to achieve the desired results. [Detailed Blog Post] | [Quiz with Answer] Introduction to Hierarchical Query – SQL in Sixty Seconds #012 A CTE can be thought of as a temporary result set and are similar to a derived table in that it is not stored as an object and lasts only for the duration of the query. A CTE is generally considered to be more readable than a derived table and does not require the extra effort of declaring a Temp Table while providing the same benefits to the user. However; a CTE is more powerful than a derived table as it can also be self-referencing, or even referenced multiple times in the same query. A recursive CTE requires four elements in order to work properly: Anchor query (runs once and the results ‘seed’ the Recursive query) Recursive query (runs multiple times and is the criteria for the remaining results) UNION ALL statement to bind the Anchor and Recursive queries together. INNER JOIN statement to bind the Recursive query to the results of the CTE. [Detailed Blog Post] | [Quiz with Answer] Introduction to SQL Server Security – SQL in Sixty Seconds #011 Let’s get some basic definitions down first. Take the workplace example where “Tom” needs “Read” access to the “Financial Folder”. What are the Securable, Principal, and Permissions from that last sentence? A Securable is a resource that someone might want to access (like the Financial Folder). A Principal is anything that might want to gain access to the securable (like Tom). A Permission is the level of access a principal has to a securable (like Read). [Detailed Blog Post] | [Quiz with Answer] Please leave a comment explain which one was your favorite video as that will help me understand what works and what needs improvement. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video

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• How to display a dependent list box disabled if no child data exist

  - by frank.nimphius

  A requirement on OTN was to disable the dependent list box of a model driven list of value configuration whenever the list is empty. To disable the dependent list, the af:selectOneChoice component needs to be refreshed with every value change of the parent list, which however already is the case as the list boxes are already dependent. When you create model driven list of values as choice lists in an ADF Faces page, two ADF list bindings are implicitly created in the PageDef file of the page that hosts the input form. At runtime, a list binding is an instance of FacesCtrlListBinding, which exposes getItems() as a method to access a list of available child data (java.util.List). Using Expression Language, the list is accessible with #{bindings.list_attribute_name.items} To dynamically set the disabled property on the dependent af:selectOneChoice component, however, you need a managed bean that exposes the following two methods //empty – but required – setter method public void setIsEmpty(boolean isEmpty) {} //the method that returns true/false when the list is empty or //has values public boolean isIsEmpty() {   FacesContext fctx = FacesContext.getCurrentInstance();   ELContext elctx = fctx.getELContext();   ExpressionFactory exprFactory =                          fctx.getApplication().getExpressionFactory();   ValueExpression vexpr =                       exprFactory.createValueExpression(elctx,                         "#{bindings.EmployeeId.items}",                       Object.class);   List employeesList = (List) vexpr.getValue(elctx);                        return employeesList.isEmpty()? true : false;      } If referenced from the dependent choice list, as shown below, the list is disabled whenever it contains no list data <! --  master list --> <af:selectOneChoice value="#{bindings.DepartmentId.inputValue}"                                  label="#{bindings.DepartmentId.label}"                                  required="#{bindings.DepartmentId.hints.mandatory}"                                   shortDesc="#{bindings.DepartmentId.hints.tooltip}"                                   id="soc1" autoSubmit="true">      <f:selectItems value="#{bindings.DepartmentId.items}" id="si1"/> </af:selectOneChoice> <! --  dependent  list --> <af:selectOneChoice value="#{bindings.EmployeeId.inputValue}"                                   label="#{bindings.EmployeeId.label}"                                      required="#{bindings.EmployeeId.hints.mandatory}"                                   shortDesc="#{bindings.EmployeeId.hints.tooltip}"                                   id="soc2" disabled="#{lovTestbean.isEmpty}"                                   partialTriggers="soc1">     <f:selectItems value="#{bindings.EmployeeId.items}" id="si2"/> </af:selectOneChoice>

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• How much help should I give during technical interviews?

  - by kojiro

  I'm asked to perform or sit in during many technical interviews. We ask logic questions and simple programming problems that the interviewee is expected to be able to solve on paper. (I would rather they have access to a keyboard, but that is a problem for another time.) Sometimes I sense that people do know how to approach a problem, but they are hung up by nervousness or some second-guessing of the question (they aren't intended to be trick questions). I've never heard my boss give any help or hints. He just thanks the interviewee for the response (no matter how good or bad it is) and moves on to the next question or problem. But I know something about the rabbit hole that defeat and nerves can lead you down, and how it disables your mind, and I can't help wondering if providing a little help now and then would ultimately help us end up with more capable programmers instead of more failed interviews. Should I provide hints and assistance for befuddled interviewees (and if so, how far should I go while still being fair to the more prepared candidates)?

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• Established coding standards for pl/pgsql code

  - by jb01

  I need to standardize coding practises for project that compromises, among others has pl/pgsql database, that has some amount of nontrivial code. I look for: Code formatting guidelines, especially inside procedures. Guidelines on what constructs are consigered unsafe (if any) Naming coventions. Code documentation conventions (if this is pracicised) Any hints to documets that define good practises in pl/pgsql code? If not i'm looking for hints to practices that you consider good. There is related question regarding TSQL: Can anyone recommend coding standards for TSQL?, which is relevant to psql as well, but I need more information on stored procedures. Other related questions: http://stackoverflow.com/questions/1070275/what-indenting-style-do-you-use-in-sql-server-stored-procedures

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• NetBeans IDE 7.3 Knows Null

  - by Geertjan

  What's the difference between these two methods, "test1" and "test2"? public int test1(String str) {     return str.length(); } public int test2(String str) {     if (str == null) {         System.err.println("Passed null!.");         //forgotten return;     }     return str.length(); } The difference, or at least, the difference that is relevant for this blog entry, is that whoever wrote "test2" apparently thinks that the variable "str" may be null, though did not provide a null check. In NetBeans IDE 7.3, you see this hint for "test2", but no hint for "test1", since in that case we don't know anything about the developer's intention for the variable and providing a hint in that case would flood the source code with too many false positives:  Annotations are supported in understanding how a piece of code is intended to be used. If method return types use @Nullable, @NullAllowed, @CheckForNull, the value is considered to be "strongly possible to be null", as well as if the variable is tested to be null, as shown above. When using @NotNull, @NonNull, @Nonnull, the value is considered to be non-null. (The exact FQNs of the annotations are ignored, only simple names are checked.) Here are examples showing where the hints are displayed for the non-null hints (the "strongly possible to be null" hints are not shown below, though you can see one of them in the screenshot above), together with a comment showing what is shown when you hover over the hint: There isn't a "one size fits all" refactoring for these various instances relating to null checks, hence you can't do an automated refactoring across your code base via tools in NetBeans IDE, as shown yesterday for class member reordering across code bases. However, you can, instead, go to Source | Inspect and then do a scan throughout a scope (e.g., current file/package/project or combinations of these or all open projects) for class elements that the IDE identifies as potentially having a problem in this area: Thanks to Jan Lahoda, who reports that this currently also works in NetBeans IDE 7.3 dev builds for fields but that may need to be disabled since right now too many false positives are returned, for help with the info above and any misunderstandings are my own fault!

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• Software Architecture

  - by Roger

  I have a question about Software Architecture, anyone can help me or give me some hints currently, I have a J2EE project which deploys in a server, I should a Java Standard project(J2SE) should run 24 hours x 7 days to monitor something it could not run separately, because the Java Project shared the some same classes such as Java Bean classes with the J2EE project maybe my design is not correct, can anyone suggest me what should I do? Using SOA? is this correct? my current solution is run this java project using a bash, but I dont think it is then best idea. I list my class packages com.company.alteck com.company.altronics com.company.gamming com.company.jaycar com.company.jup com.company.rpg com.company.sansai com.company.wiretech com.company.yatsal com.ebay.api com.ebay.bean com.ebay.credential com.ozsstock.finals com.ozstock.adapter com.ozstock.aspectj com.ozstock.model com.ozstock.persistence com.ozstock.service com.ozstock.suppliers my structure likes this, all the packages contains "company" should run separately, but depends on the model bean class. can anyone give me some hints to redesign?

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• PHP ZendOptimizer on Red Hat Enterprise Linux

  - by Jacob Kristensen

  I would like to install FlashMoto and the requirements are not unreasonable: PHP 5.2.1 or higher, Zend Optimizer 3.3 or higher. However my RHEL 5.4 provides me with PHP 5.1.6. So I tried the remi repository http://rpms.famillecollet.com/ but it gave me PHP 5.3.1 and Zend Optimizer from zend.com does not support anything higher than 5.2.x. I also tried the dag repo but it does not have PHP in any version. I also tried some RPMs that Oracle provides on their homepage but they don't provide php-mbstring that I also need. Does anyone know how to get PHP 5.2.1 installed on a RHEL 5.4? Then I can probably fix install the Zend thing. Thanks in advance.

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• How do I create statistics to make ‘small’ objects appear ‘large’ to the Optmizer?

  - by Maria Colgan

  I recently spoke with a customer who has a development environment that is a tiny fraction of the size of their production environment. His team has been tasked with identifying problem SQL statements in this development environment before new code is released into production. The problem is the objects in the development environment are so small, the execution plans selected in the development environment rarely reflects what actually happens in production. To ensure the development environment accurately reflects production, in the eyes of the Optimizer, the statistics used in the development environment must be the same as the statistics used in production. This can be achieved by exporting the statistics from production and import them into the development environment. Even though the underlying objects are a fraction of the size of production, the Optimizer will see them as the same size and treat them the same way as it would in production. Below are the necessary steps to achieve this in their environment. I am using the SH sample schema as the application schema who's statistics we want to move from production to development. Step 1. Create a staging table, in the production environment, where the statistics can be stored Step 2. Export the statistics for the application schema, from the data dictionary in production, into the staging table Step 3. Create an Oracle directory on the production system where the export of the staging table will reside and grant the SH user the necessary privileges on it. Step 4. Export the staging table from production using data pump export Step 5. Copy the dump file containing the stating table from production to development Step 6. Create an Oracle directory on the development system where the export of the staging table resides and grant the SH user the necessary privileges on it.  Step 7. Import the staging table into the development environment using data pump import Step 8. Import the statistics from the staging table into the dictionary in the development environment. You can get a copy of the script I used to generate this post here. +Maria Colgan

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• Hello Operator, My Switch Is Bored

  - by Paul White

  This is a post for T-SQL Tuesday #43 hosted by my good friend Rob Farley. The topic this month is Plan Operators. I haven’t taken part in T-SQL Tuesday before, but I do like to write about execution plans, so this seemed like a good time to start. This post is in two parts. The first part is primarily an excuse to use a pretty bad play on words in the title of this blog post (if you’re too young to know what a telephone operator or a switchboard is, I hate you). The second part of the post looks at an invisible query plan operator (so to speak). 1. My Switch Is Bored Allow me to present the rare and interesting execution plan operator, Switch: Books Online has this to say about Switch: Following that description, I had a go at producing a Fast Forward Cursor plan that used the TOP operator, but had no luck. That may be due to my lack of skill with cursors, I’m not too sure. The only application of Switch in SQL Server 2012 that I am familiar with requires a local partitioned view: CREATE TABLE dbo.T1 (c1 int NOT NULL CHECK (c1 BETWEEN 00 AND 24)); CREATE TABLE dbo.T2 (c1 int NOT NULL CHECK (c1 BETWEEN 25 AND 49)); CREATE TABLE dbo.T3 (c1 int NOT NULL CHECK (c1 BETWEEN 50 AND 74)); CREATE TABLE dbo.T4 (c1 int NOT NULL CHECK (c1 BETWEEN 75 AND 99)); GO CREATE VIEW V1 AS SELECT c1 FROM dbo.T1 UNION ALL SELECT c1 FROM dbo.T2 UNION ALL SELECT c1 FROM dbo.T3 UNION ALL SELECT c1 FROM dbo.T4; Not only that, but it needs an updatable local partitioned view. We’ll need some primary keys to meet that requirement: ALTER TABLE dbo.T1 ADD CONSTRAINT PK_T1 PRIMARY KEY (c1);   ALTER TABLE dbo.T2 ADD CONSTRAINT PK_T2 PRIMARY KEY (c1);   ALTER TABLE dbo.T3 ADD CONSTRAINT PK_T3 PRIMARY KEY (c1);   ALTER TABLE dbo.T4 ADD CONSTRAINT PK_T4 PRIMARY KEY (c1); We also need an INSERT statement that references the view. Even more specifically, to see a Switch operator, we need to perform a single-row insert (multi-row inserts use a different plan shape): INSERT dbo.V1 (c1) VALUES (1); And now…the execution plan: The Constant Scan manufactures a single row with no columns. The Compute Scalar works out which partition of the view the new value should go in. The Assert checks that the computed partition number is not null (if it is, an error is returned). The Nested Loops Join executes exactly once, with the partition id as an outer reference (correlated parameter). The Switch operator checks the value of the parameter and executes the corresponding input only. If the partition id is 0, the uppermost Clustered Index Insert is executed, adding a row to table T1. If the partition id is 1, the next lower Clustered Index Insert is executed, adding a row to table T2…and so on. In case you were wondering, here’s a query and execution plan for a multi-row insert to the view: INSERT dbo.V1 (c1) VALUES (1), (2); Yuck! An Eager Table Spool and four Filters! I prefer the Switch plan. My guess is that almost all the old strategies that used a Switch operator have been replaced over time, using things like a regular Concatenation Union All combined with Start-Up Filters on its inputs. Other new (relative to the Switch operator) features like table partitioning have specific execution plan support that doesn’t need the Switch operator either. This feels like a bit of a shame, but perhaps it is just nostalgia on my part, it’s hard to know. Please do let me know if you encounter a query that can still use the Switch operator in 2012 – it must be very bored if this is the only possible modern usage! 2. Invisible Plan Operators The second part of this post uses an example based on a question Dave Ballantyne asked using the SQL Sentry Plan Explorer plan upload facility. If you haven’t tried that yet, make sure you’re on the latest version of the (free) Plan Explorer software, and then click the Post to SQLPerformance.com button. That will create a site question with the query plan attached (which can be anonymized if the plan contains sensitive information). Aaron Bertrand and I keep a close eye on questions there, so if you have ever wanted to ask a query plan question of either of us, that’s a good way to do it. The problem The issue I want to talk about revolves around a query issued against a calendar table. The script below creates a simplified version and adds 100 years of per-day information to it: USE tempdb; GO CREATE TABLE dbo.Calendar ( dt date NOT NULL, isWeekday bit NOT NULL, theYear smallint NOT NULL,   CONSTRAINT PK__dbo_Calendar_dt PRIMARY KEY CLUSTERED (dt) ); GO -- Monday is the first day of the week for me SET DATEFIRST 1;   -- Add 100 years of data INSERT dbo.Calendar WITH (TABLOCKX) (dt, isWeekday, theYear) SELECT CA.dt, isWeekday = CASE WHEN DATEPART(WEEKDAY, CA.dt) IN (6, 7) THEN 0 ELSE 1 END, theYear = YEAR(CA.dt) FROM Sandpit.dbo.Numbers AS N CROSS APPLY ( VALUES (DATEADD(DAY, N.n - 1, CONVERT(date, '01 Jan 2000', 113))) ) AS CA (dt) WHERE N.n BETWEEN 1 AND 36525; The following query counts the number of weekend days in 2013: SELECT Days = COUNT_BIG(*) FROM dbo.Calendar AS C WHERE theYear = 2013 AND isWeekday = 0; It returns the correct result (104) using the following execution plan: The query optimizer has managed to estimate the number of rows returned from the table exactly, based purely on the default statistics created separately on the two columns referenced in the query’s WHERE clause. (Well, almost exactly, the unrounded estimate is 104.289 rows.) There is already an invisible operator in this query plan – a Filter operator used to apply the WHERE clause predicates. We can see it by re-running the query with the enormously useful (but undocumented) trace flag 9130 enabled: Now we can see the full picture. The whole table is scanned, returning all 36,525 rows, before the Filter narrows that down to just the 104 we want. Without the trace flag, the Filter is incorporated in the Clustered Index Scan as a residual predicate. It is a little bit more efficient than using a separate operator, but residual predicates are still something you will want to avoid where possible. The estimates are still spot on though: Anyway, looking to improve the performance of this query, Dave added the following filtered index to the Calendar table: CREATE NONCLUSTERED INDEX Weekends ON dbo.Calendar(theYear) WHERE isWeekday = 0; The original query now produces a much more efficient plan: Unfortunately, the estimated number of rows produced by the seek is now wrong (365 instead of 104): What’s going on? The estimate was spot on before we added the index! Explanation You might want to grab a coffee for this bit. Using another trace flag or two (8606 and 8612) we can see that the cardinality estimates were exactly right initially: The highlighted information shows the initial cardinality estimates for the base table (36,525 rows), the result of applying the two relational selects in our WHERE clause (104 rows), and after performing the COUNT_BIG(*) group by aggregate (1 row). All of these are correct, but that was before cost-based optimization got involved :) Cost-based optimization When cost-based optimization starts up, the logical tree above is copied into a structure (the ‘memo’) that has one group per logical operation (roughly speaking). The logical read of the base table (LogOp_Get) ends up in group 7; the two predicates (LogOp_Select) end up in group 8 (with the details of the selections in subgroups 0-6). These two groups still have the correct cardinalities as trace flag 8608 output (initial memo contents) shows: During cost-based optimization, a rule called SelToIdxStrategy runs on group 8. It’s job is to match logical selections to indexable expressions (SARGs). It successfully matches the selections (theYear = 2013, is Weekday = 0) to the filtered index, and writes a new alternative into the memo structure. The new alternative is entered into group 8 as option 1 (option 0 was the original LogOp_Select): The new alternative is to do nothing (PhyOp_NOP = no operation), but to instead follow the new logical instructions listed below the NOP. The LogOp_GetIdx (full read of an index) goes into group 21, and the LogOp_SelectIdx (selection on an index) is placed in group 22, operating on the result of group 21. The definition of the comparison ‘the Year = 2013’ (ScaOp_Comp downwards) was already present in the memo starting at group 2, so no new memo groups are created for that. New Cardinality Estimates The new memo groups require two new cardinality estimates to be derived. First, LogOp_Idx (full read of the index) gets a predicted cardinality of 10,436. This number comes from the filtered index statistics: DBCC SHOW_STATISTICS (Calendar, Weekends) WITH STAT_HEADER; The second new cardinality derivation is for the LogOp_SelectIdx applying the predicate (theYear = 2013). To get a number for this, the cardinality estimator uses statistics for the column ‘theYear’, producing an estimate of 365 rows (there are 365 days in 2013!): DBCC SHOW_STATISTICS (Calendar, theYear) WITH HISTOGRAM; This is where the mistake happens. Cardinality estimation should have used the filtered index statistics here, to get an estimate of 104 rows: DBCC SHOW_STATISTICS (Calendar, Weekends) WITH HISTOGRAM; Unfortunately, the logic has lost sight of the link between the read of the filtered index (LogOp_GetIdx) in group 22, and the selection on that index (LogOp_SelectIdx) that it is deriving a cardinality estimate for, in group 21. The correct cardinality estimate (104 rows) is still present in the memo, attached to group 8, but that group now has a PhyOp_NOP implementation. Skipping over the rest of cost-based optimization (in a belated attempt at brevity) we can see the optimizer’s final output using trace flag 8607: This output shows the (incorrect, but understandable) 365 row estimate for the index range operation, and the correct 104 estimate still attached to its PhyOp_NOP. This tree still has to go through a few post-optimizer rewrites and ‘copy out’ from the memo structure into a tree suitable for the execution engine. One step in this process removes PhyOp_NOP, discarding its 104-row cardinality estimate as it does so. To finish this section on a more positive note, consider what happens if we add an OVER clause to the query aggregate. This isn’t intended to be a ‘fix’ of any sort, I just want to show you that the 104 estimate can survive and be used if later cardinality estimation needs it: SELECT Days = COUNT_BIG(*) OVER () FROM dbo.Calendar AS C WHERE theYear = 2013 AND isWeekday = 0; The estimated execution plan is: Note the 365 estimate at the Index Seek, but the 104 lives again at the Segment! We can imagine the lost predicate ‘isWeekday = 0’ as sitting between the seek and the segment in an invisible Filter operator that drops the estimate from 365 to 104. Even though the NOP group is removed after optimization (so we don’t see it in the execution plan) bear in mind that all cost-based choices were made with the 104-row memo group present, so although things look a bit odd, it shouldn’t affect the optimizer’s plan selection. I should also mention that we can work around the estimation issue by including the index’s filtering columns in the index key: CREATE NONCLUSTERED INDEX Weekends ON dbo.Calendar(theYear, isWeekday) WHERE isWeekday = 0 WITH (DROP_EXISTING = ON); There are some downsides to doing this, including that changes to the isWeekday column may now require Halloween Protection, but that is unlikely to be a big problem for a static calendar table ;)  With the updated index in place, the original query produces an execution plan with the correct cardinality estimation showing at the Index Seek: That’s all for today, remember to let me know about any Switch plans you come across on a modern instance of SQL Server! Finally, here are some other posts of mine that cover other plan operators: Segment and Sequence Project Common Subexpression Spools Why Plan Operators Run Backwards Row Goals and the Top Operator Hash Match Flow Distinct Top N Sort Index Spools and Page Splits Singleton and Range Seeks Bitmaps Hash Join Performance Compute Scalar © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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• Unused Indexes Gotcha

  - by DavidWimbush

  I'm currently looking into dropping unused indexes to reduce unnecessary overhead and I came across a very good point in the excellent SQL Server MVP Deep Dives book that I haven't seen highlighted anywhere else. I was thinking it was simply a case of dropping indexes that didn't show as being used in DMV sys.dm_db_index_usage_stats (assuming a solid representative workload had been run since the last service start). But Rob Farley points out that the DMV only shows indexes whose pages have been read or updated. An index that isn't listed in the DMV might still be useful by providing metadata to the Query Optimizer and thus streamlining query plans. For example, if you have a query like this: select  au.author_name         , count(*) as books from    books b         inner join authors au on au.author_id = b.author_id group by au.author_name If you have a unique index on authors.author_name the Query Optimizer will realise that each author_id will have a different author_name so it can produce a plan that just counts the books by author_id and then adds the author name to each row in that small table. If you delete that index the query will have to join all the books with their authors and then apply the GROUP BY - a much more expensive query. So be cautious about dropping apparently unused unique indexes.

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• Column order can matter

  - by Dave Ballantyne

  Ordinarily, column order of a SQL statement does not matter. Select a,b,c from table will produce the same execution plan as   Select c,b,a from table However, sometimes it can make a difference.   Consider this statement (maxdop is used to make a simpler plan and has no impact to the main point):   select SalesOrderID, CustomerID, OrderDate, ROW_NUMBER() over (Partition By CustomerId order by OrderDate asc) as RownAsc, ROW_NUMBER() over (Partition By CustomerId order by OrderDate Desc) as RownDesc from sales.SalesOrderHeader order by CustomerID,OrderDateoption(maxdop 1) If you look at the execution plan, you will see similar to this That is three sorts.  One for RownAsc,  one for RownDesc and the final one for the ‘Order by’ clause.  Sorting is an expensive operation and one that should be avoided if possible.  So with this in mind, it may come as some surprise that the optimizer does not re-order operations to group them together when the incoming data is in a similar (if not exactly the same) sorted sequence.  A simple change to swap the RownAsc and RownDesc columns to produce this statement : select SalesOrderID, CustomerID, OrderDate, ROW_NUMBER() over (Partition By CustomerId order by OrderDate Desc) as RownDesc , ROW_NUMBER() over (Partition By CustomerId order by OrderDate asc) as RownAsc from Sales.SalesOrderHeader order by CustomerID,OrderDateoption(maxdop 1) Will result a different and more efficient query plan with one less sort. The optimizer, although unable to automatically re-order operations, HAS taken advantage of the data ordering if it is as required.  This is well worth taking advantage of if you have different sorting requirements in one statement. Try grouping the functions that require the same order together and save yourself a few extra sorts.

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• Printing with an Eclipse RCP program

  - by Raven

  Hi, I am looking for a good, standard way to generate "output" in my RCP programm and print it. This should work as it works on Windows, Mac OS and Linux with the standard print dialog. I am aware of the Birt project, but I could not find any hints about how to implement it within a RCP programm and how to invoke the standard print dialog and how to pass the Birt generated report to the printer. Happy for all hints.

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• LockMode With Subclasses

  - by Lester

  I'm using Fluent Nhibernate with the following query on DerivedClass which extends BaseClass: var query = Session.CreateCriteria<DerivedClass>().SetLockMode(LockMode.Upgrade) What I want is the lock hints (updlock, rowlock) to be applied to both DerivedClass and BaseClass, but the generated SQL only applies the lock hints to DerivedClass: SELECT * FROM DerivedClass this_ with (updlock, rowlock) inner join [BaseClass] this_1_ on this_.Id=this_1_.Id WHERE ... This is the same situation described in http://opensource.atlassian.com/projects/hibernate/browse/HHH-2392 If anyone could point me in the right direction it would be much appreciated.

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• Simple GET operation with JSON data in ADF Mobile

  - by PadmajaBhat

  Usecase: This sample uses a RESTful service which contains a GET method that fetches employee details for an employee with given employee ID along with other methods. The data is fetched in JSON format. This RESTful service is then invoked via ADF Mobile and the JSON data thus obtained is parsed and rendered in mobile in a table. Prerequisite: Download JDev build JDEVADF_11.1.2.4.0_GENERIC_130421.1600.6436.1 or higher with mobile support.  Steps: Run EmployeeService.java in JSONService.zip. This is a simple service with a method, getEmpById(id) that takes employee ID as parameter and produces employee details in JSON format. Copy the target URL generated on running this service. The target URL will be as shown below: http://127.0.0.1:7101/JSONService-Project1-context-root/jersey/project1 Now, let us invoke this service in our mobile application. For this, create an ADF Mobile application.  Name the application JSON_SearchByEmpID and finish the wizard. Now, let us create a connection to our service. To do this, we create a URL Connection. Invoke new gallery wizard on ApplicationController project.  Select URL Connection option. In the Create URL Connection window, enter connection name as ‘conn’. For URL endpoint, supply the URL you copied earlier on running the service. Remember to use your system IP instead of localhost. Test the connection and click OK. At this point, a connection to the REST service has been created. Since JSON data is not supported directly in WSDC wizard, we need to invoke the operation through Java code using RestServiceAdapter. For this, in the ApplicationController project, create a Java class called ‘EmployeeDC’. We will be creating DC from this class. Add the following code to the newly created class to invoke the getEmpById method. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 public Employee fetchEmpDetails(){ RestServiceAdapter restServiceAdapter = Model.createRestServiceAdapter(); restServiceAdapter.clearRequestProperties(); restServiceAdapter.setConnectionName("conn"); //URL connection created with this name restServiceAdapter.setRequestType(RestServiceAdapter.REQUEST_TYPE_GET); restServiceAdapter.addRequestProperty("Content-Type", "application/json"); restServiceAdapter.addRequestProperty("Accept", "application/json; charset=UTF-8"); restServiceAdapter.setRetryLimit(0); restServiceAdapter.setRequestURI("/getById/"+inputEmpID); String response = ""; JSONBeanSerializationHelper jsonHelper = new JSONBeanSerializationHelper(); try { response = restServiceAdapter.send(""); //Invoke the GET operation System.out.println("Response received!"); Employee responseObject = (Employee) jsonHelper.fromJSON(Employee.class, response); return responseObject; } catch (Exception e) { } return null; } Here, in lines 2 to 9, we create the RestServiceAdapter and set various properties required to invoke the web service. At line 4, we are pointing to the connection ‘conn’ created previously. Since we want to invoke getEmpById method of the service, which is defined by the URL http://IP:7101/REST_Sanity_JSON-Project1-context-root/resources/project1/getById/{id} we are updating the request URI to point to this URI at line 9. inputEmpID is a variable that will hold the value input by the user for employee ID. This we will be creating in a while. As the method we are invoking is a GET operation and consumes json data, these properties are being set in lines 5 through 7. Finally, we are sending the request in line 13. In line 15, we use jsonHelper.fromJSON to convert received JSON data to a Java object. The required Java objects' structure is defined in class Employee.java whose structure is provided later. Since the response from our service is a simple response consisting of attributes like employee Id, name, design etc, we will just return this parsed response (line 16) and use it to create DC. As mentioned previously, we would like the user to input the employee ID for which he/she wants to perform search. So, in the same class, define a variable inputEmpID which will hold the value input by the user. Generate accessors for this variable. Lastly, we need to create Employee class. Employee class will define how we want to structure the JSON object received from the service. To design the Employee class, run the services’ method in the browser or via analyzer using path parameter as 1. This will give you the output JSON structure. Ours is a simple service that returns a JSONObject with a set of data. Hence, Employee class will just contain this set of data defined with the proper data types. Create Employee.java in the same project as EmployeeDC.java and write the below code: package application; import oracle.adfmf.java.beans.PropertyChangeListener; import oracle.adfmf.java.beans.PropertyChangeSupport; public class Employee { private String dept; private String desig; private int id; private String name; private int salary; private PropertyChangeSupport propertyChangeSupport = new PropertyChangeSupport(this); public void setDept(String dept) {         String oldDept = this.dept; this.dept = dept; propertyChangeSupport.firePropertyChange("dept", oldDept, dept); } public String getDept() { return dept; } public void setDesig(String desig) { String oldDesig = this.desig; this.desig = desig; propertyChangeSupport.firePropertyChange("desig", oldDesig, desig); } public String getDesig() { return desig; } public void setId(int id) { int oldId = this.id; this.id = id; propertyChangeSupport.firePropertyChange("id", oldId, id); } public int getId() { return id; } public void setName(String name) { String oldName = this.name; this.name = name; propertyChangeSupport.firePropertyChange("name", oldName, name); } public String getName() { return name; } public void setSalary(int salary) { int oldSalary = this.salary; this.salary = salary; propertyChangeSupport.firePropertyChange("salary", oldSalary, salary); } public int getSalary() { return salary; } public void addPropertyChangeListener(PropertyChangeListener l) { propertyChangeSupport.addPropertyChangeListener(l); } public void removePropertyChangeListener(PropertyChangeListener l) { propertyChangeSupport.removePropertyChangeListener(l);     } } Now, let us create a DC out of EmployeeDC.java.  DC as shown below is created. Now, you can design the mobile page as usual and invoke the operation of the service. To design the page, go to ViewController project and locate adfmf-feature.xml. Create a new feature called ‘SearchFeature’ by clicking the plus icon. Go the content tab and add an amx page. Call it SearchPage.amx. Call it SearchPage.amx. Remove primary and secondary buttons as we don’t need them and rename the header. Drag and drop inputEmpID from the DC palette onto Panel Page in the structure pane as input text with label. Next, drop fetchEmpDetails method as an ADF button. For a change, let us display the output in a table component instead of the usual form. However, you will notice that if you drag and drop Employee onto the structure pane, there is no option for ADF Mobile Table. Hence, we will need to create the table on our own. To do this, let us first drop Employee as an ADF Read -Only form. This step is needed to get the required bindings. We will be deleting this form in a while. Now, from the Component palette, search for ‘Table Layout’. Drag and drop this below the command button.  Within the tablelayout, insert ‘Row Layout’ and ‘Cell Format’ components. Final table structure should be as shown below. Here, we have also defined some inline styling to render the UI in a nice manner. <amx:tableLayout id="tl1" borderWidth="2" halign="center" inlineStyle="vertical-align:middle;" width="100%" cellPadding="10"> <amx:rowLayout id="rl1" > <amx:cellFormat id="cf1" width="30%"> <amx:outputText value="#{bindings.dept.hints.label}" id="ot7" inlineStyle="color:rgb(0,148,231);"/> </amx:cellFormat> <amx:cellFormat id="cf2"> <amx:outputText value="#{bindings.dept.inputValue}" id="ot8" /> </amx:cellFormat> </amx:rowLayout> <amx:rowLayout id="rl2"> <amx:cellFormat id="cf3" width="30%"> <amx:outputText value="#{bindings.desig.hints.label}" id="ot9" inlineStyle="color:rgb(0,148,231);"/> </amx:cellFormat> <amx:cellFormat id="cf4" > <amx:outputText value="#{bindings.desig.inputValue}" id="ot10"/> </amx:cellFormat> </amx:rowLayout> <amx:rowLayout id="rl3"> <amx:cellFormat id="cf5" width="30%"> <amx:outputText value="#{bindings.id.hints.label}" id="ot11" inlineStyle="color:rgb(0,148,231);"/> </amx:cellFormat> <amx:cellFormat id="cf6" > <amx:outputText value="#{bindings.id.inputValue}" id="ot12"/> </amx:cellFormat> </amx:rowLayout> <amx:rowLayout id="rl4"> <amx:cellFormat id="cf7" width="30%"> <amx:outputText value="#{bindings.name.hints.label}" id="ot13" inlineStyle="color:rgb(0,148,231);"/> </amx:cellFormat> <amx:cellFormat id="cf8"> <amx:outputText value="#{bindings.name.inputValue}" id="ot14"/> </amx:cellFormat> </amx:rowLayout> <amx:rowLayout id="rl5"> <amx:cellFormat id="cf9" width="30%"> <amx:outputText value="#{bindings.salary.hints.label}" id="ot15" inlineStyle="color:rgb(0,148,231);"/> </amx:cellFormat> <amx:cellFormat id="cf10"> <amx:outputText value="#{bindings.salary.inputValue}" id="ot16"/> </amx:cellFormat> </amx:rowLayout>     </amx:tableLayout> The values used in the output text of the table come from the bindings obtained from the ADF Form created earlier. As we have used the bindings and don’t need the form anymore, let us delete the form.  One last thing before we deploy. When user changes employee ID, we want to clear the table contents. For this we associate a value change listener with the input text box. Click New in the resulting dialog to create a managed bean. Next, we create a method within the managed bean. For this, click on the New button associated with method. Call the method ‘empIDChange’. Open myClass.java and write the below code in empIDChange(). public void empIDChange(ValueChangeEvent valueChangeEvent) { // Add event code here... //Resetting the values to blank values when employee id changes AdfELContext adfELContext = AdfmfJavaUtilities.getAdfELContext(); ValueExpression ve = AdfmfJavaUtilities.getValueExpression("#{bindings.dept.inputValue}", String.class); ve.setValue(adfELContext, ""); ve = AdfmfJavaUtilities.getValueExpression("#{bindings.desig.inputValue}", String.class); ve.setValue(adfELContext, ""); ve = AdfmfJavaUtilities.getValueExpression("#{bindings.id.inputValue}", int.class); ve.setValue(adfELContext, ""); ve = AdfmfJavaUtilities.getValueExpression("#{bindings.name.inputValue}", String.class); ve.setValue(adfELContext, ""); ve = AdfmfJavaUtilities.getValueExpression("#{bindings.salary.inputValue}", int.class); ve.setValue(adfELContext, ""); } That’s it. Deploy the application to android emulator or device. Some snippets from the app.

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• SQL Server Table Polling by Multiple Subscribers

  - by Daniel Hester

  Background Designing Stored Procedures that are safe for multiple subscribers (to call simultaneously) can be challenging.  For example let’s say that you want multiple worker processes to poll a shared work queue that’s encapsulated as a SQL Table. This is a common scenario and through experience you’ll find that you want to use Table Hints to prevent unwanted locking when performing simultaneous queries on the same table. There are three table hints to consider: NOLOCK, READPAST and UPDLOCK. Both NOLOCK and READPAST table hints allow you to SELECT from a table without placing a LOCK on that table. However, SELECTs with the READPAST hint will ignore any records that are locked due to being updated/inserted (or otherwise “dirty”), whereas a SELECT with NOLOCK ignores all locks including dirty reads. For the initial update of the flag (that marks the record as available for subscription) I don’t use the NOLOCK Table Hint because I want to be sensitive to the “active” records in the table and I want to exclude them.  I use an Update Lock (UPDLOCK) in conjunction with a WHERE clause that uses a sub-select with a READPAST Table Hint in order to explicitly lock the records I’m updating (UPDLOCK) but not place a lock on the table when selecting the records that I’m going to update (READPAST). UPDATES should be allowed to lock the rows affected because we’re probably changing a flag on a record so that it is not included in a SELECT from another subscriber. On the UPDATE statement we should explicitly use the UPDLOCK to guard against lock escalation. A SELECT to check for the next record(s) to process can result in a shared read lock being held by more than one subscriber polling the shared work queue (SQL table). It is expected that more than one worker process (or server) might try to process the same new record(s) at the same time. When each process then tries to obtain the update lock, none of them can because another process has a shared read lock in place. Thus without the UPDLOCK hint the result would be a lock escalation deadlock; however with the UPDLOCK hint this condition is mitigated against. Note that using the READPAST table hint requires that you also set the ISOLATION LEVEL of the transaction to be READ COMMITTED (rather than the default of SERIALIZABLE). Guidance In the Stored Procedure that returns records to the multiple subscribers: Perform the UPDATE first. Change the flag that makes the record available to subscribers.  Additionally, you may want to update a LastUpdated datetime field in order to be able to check for records that “got stuck” in an intermediate state or for other auditing purposes. In the UPDATE statement use the (UPDLOCK) Table Hint on the UPDATE statement to prevent lock escalation. In the UPDATE statement also use a WHERE Clause that uses a sub-select with a (READPAST) Table Hint to select the records that you’re going to update. In the UPDATE statement use the OUTPUT clause in conjunction with a Temporary Table to isolate the record(s) that you’ve just updated and intend to return to the subscriber. This is the fastest way to update the record(s) and to get the records’ identifiers within the same operation. Finally do a set-based SELECT on the main Table (using the Temporary Table to identify the records in the set) with either a READPAST or NOLOCK table hint.  Use NOLOCK if there are other processes (besides the multiple subscribers) that might be changing the data that you want to return to the multiple subscribers; or use READPAST if you're sure there are no other processes (besides the multiple subscribers) that might be updating column data in the table for other purposes (e.g. changes to a person’s last name).  NOLOCK is generally the better fit in this part of the scenario. See the following as an example: CREATE PROCEDURE [dbo].[usp_NewCustomersSelect] AS BEGIN -- OVERRIDE THE DEFAULT ISOLATION LEVEL SET TRANSACTION ISOLATION LEVEL READ COMMITTED -- SET NOCOUNT ON SET NOCOUNT ON -- DECLARE TEMP TABLE -- Note that this example uses CustomerId as an identifier; -- you could just use the Identity column Id if that’s all you need. DECLARE @CustomersTempTable TABLE ( CustomerId NVARCHAR(255) ) -- PERFORM UPDATE FIRST -- [Customers] is the name of the table -- [Id] is the Identity Column on the table -- [CustomerId] is the business document key used to identify the -- record globally, i.e. in other systems or across SQL tables -- [Status] is INT or BIT field (if the status is a binary state) -- [LastUpdated] is a datetime field used to record the time of the -- last update UPDATE [Customers] WITH (UPDLOCK) SET [Status] = 1, [LastUpdated] = GETDATE() OUTPUT [INSERTED].[CustomerId] INTO @CustomersTempTable WHERE ([Id] = (SELECT TOP 100 [Id] FROM [Customers] WITH (READPAST) WHERE ([Status] = 0) ORDER BY [Id] ASC)) -- PERFORM SELECT FROM ENTITY TABLE SELECT [C].[CustomerId], [C].[FirstName], [C].[LastName], [C].[Address1], [C].[Address2], [C].[City], [C].[State], [C].[Zip], [C].[ShippingMethod], [C].[Id] FROM [Customers] AS [C] WITH (NOLOCK), @CustomersTempTable AS [TEMP] WHERE ([C].[CustomerId] = [TEMP].[CustomerId]) END In a system that has been designed to have multiple status values for records that need to be processed in the Work Queue it is necessary to have a “Watch Dog” process by which “stale” records in intermediate states (such as “In Progress”) are detected, i.e. a [Status] of 0 = New or Unprocessed; a [Status] of 1 = In Progress; a [Status] of 2 = Processed; etc.. Thus, if you have a business rule that states that the application should only process new records if all of the old records have been processed successfully (or marked as an error), then it will be necessary to build a monitoring process to detect stalled or stale records in the Work Queue, hence the use of the LastUpdated column in the example above. The Status field along with the LastUpdated field can be used as the criteria to detect stalled / stale records. It is possible to put this watchdog logic into the stored procedure above, but I would recommend making it a separate monitoring function. In writing the stored procedure that checks for stale records I would recommend using the same kind of lock semantics as suggested above. The example below looks for records that have been in the “In Progress” state ([Status] = 1) for greater than 60 seconds: CREATE PROCEDURE [dbo].[usp_NewCustomersWatchDog] AS BEGIN -- TO OVERRIDE THE DEFAULT ISOLATION LEVEL SET TRANSACTION ISOLATION LEVEL READ COMMITTED -- SET NOCOUNT ON SET NOCOUNT ON DECLARE @MaxWait int; SET @MaxWait = 60 IF EXISTS (SELECT 1 FROM [dbo].[Customers] WITH (READPAST) WHERE ([Status] = 1) AND (DATEDIFF(s, [LastUpdated], GETDATE()) > @MaxWait)) BEGIN SELECT 1 AS [IsWatchDogError] END ELSE BEGIN SELECT 0 AS [IsWatchDogError] END END Downloads The zip file below contains two SQL scripts: one to create a sample database with the above stored procedures and one to populate the sample database with 10,000 sample records.  I am very grateful to Red-Gate software for their excellent SQL Data Generator tool which enabled me to create these sample records in no time at all. References http://msdn.microsoft.com/en-us/library/ms187373.aspx http://www.techrepublic.com/article/using-nolock-and-readpast-table-hints-in-sql-server/6185492 http://geekswithblogs.net/gwiele/archive/2004/11/25/15974.aspx http://grounding.co.za/blogs/romiko/archive/2009/03/09/biztalk-sql-receive-location-deadlocks-dirty-reads-and-isolation-levels.aspx

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• Setting a cookie before Javascript Redirection

  - by Jason

  Hello, I have a Rails app where I set a set a session variable the moment a user lands on my site with the referer and the page they hit. Additionally, I have Google Optimizer sending traffic from my homepage to various landing pages. The problem is that I think Google Optimizer is sending users away before the cookie is set. Is that even possible? I believe that the cookie is set from the HTTP Header, which must have fully loaded before Google's Javascript has even loaded. Thanks, Jason

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• sql server 2005 indexes and low cardinality

  - by Peanut

  How does SQL Server determine whether a table column has low cardinality? The reason I ask is because query optimizer would most probably not use an index on a gender column (values 'm' and 'f'). However how would it determine the cardinality of the gender column to come to that decision? On top of this, if in the unlikely event that I had a million entries in my table and only one entry in the gender column was 'm', would SQL server be able to determine this and use the index to retrieve that single row? Or would it just know there are only 2 distinct values in the column and not use the index? I appreciate the above discusses some poor db design, but I'm just trying to understand how query optimizer comes to its decisions. Many thanks.

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• Oracle EXECUTE IMMEDIATE changes explain plan of query.

  - by Gunny

  I have a stored procedure that I am calling using EXECUTE IMMEDIATE. The issue that I am facing is that the explain plan is different when I call the procedure directly vs when I use EXECUTE IMMEDIATE to call the procedure. This is causing the execution time to increase 5x. The main difference between the plans is that when I use execute immediate the optimizer isn't unnesting the subquery (I'm using a NOT EXISTS condition). We are using Rule Based Optimizer here at work. Example: Fast: begin package.procedure; end; / Slow: begin execute immediate 'begin package.' || proc_name || '; end;'; end; /

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• MYSQL Optimizing recurring expressions?

  - by Johannes

  Does the Optimizer evaluate the avergae only one time, or two times? SELECT AVG(col1), 1/AVG(col1) FROM table Thanks

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• Basics of Join Predicate Pushdown in Oracle

  - by Maria Colgan

  Happy New Year to all of our readers! We hope you all had a great holiday season. We start the new year by continuing our series on Optimizer transformations. This time it is the turn of Predicate Pushdown. I would like to thank Rafi Ahmed for the content of this blog.Normally, a view cannot be joined with an index-based nested loop (i.e., index access) join, since a view, in contrast with a base table, does not have an index defined on it. A view can only be joined with other tables using three methods: hash, nested loop, and sort-merge joins. Introduction The join predicate pushdown (JPPD) transformation allows a view to be joined with index-based nested-loop join method, which may provide a more optimal alternative. In the join predicate pushdown transformation, the view remains a separate query block, but it contains the join predicate, which is pushed down from its containing query block into the view. The view thus becomes correlated and must be evaluated for each row of the outer query block. These pushed-down join predicates, once inside the view, open up new index access paths on the base tables inside the view; this allows the view to be joined with index-based nested-loop join method, thereby enabling the optimizer to select an efficient execution plan. The join predicate pushdown transformation is not always optimal. The join predicate pushed-down view becomes correlated and it must be evaluated for each outer row; if there is a large number of outer rows, the cost of evaluating the view multiple times may make the nested-loop join suboptimal, and therefore joining the view with hash or sort-merge join method may be more efficient. The decision whether to push down join predicates into a view is determined by evaluating the costs of the outer query with and without the join predicate pushdown transformation under Oracle's cost-based query transformation framework. The join predicate pushdown transformation applies to both non-mergeable views and mergeable views and to pre-defined and inline views as well as to views generated internally by the optimizer during various transformations. The following shows the types of views on which join predicate pushdown is currently supported. UNION ALL/UNION view Outer-joined view Anti-joined view Semi-joined view DISTINCT view GROUP-BY view Examples Consider query A, which has an outer-joined view V. The view cannot be merged, as it contains two tables, and the join between these two tables must be performed before the join between the view and the outer table T4. A: SELECT T4.unique1, V.unique3 FROM T_4K T4,            (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3) VWHERE T4.unique3 = V.hundred(+) AND       T4.ten = V.ten(+) AND       T4.thousand = 5; The following shows the non-default plan for query A generated by disabling join predicate pushdown. When query A undergoes join predicate pushdown, it yields query B. Note that query B is expressed in a non-standard SQL and shows an internal representation of the query. B: SELECT T4.unique1, V.unique3 FROM T_4K T4,           (SELECT T10.unique3, T10.hundred, T10.ten             FROM T_5K T5, T_10K T10             WHERE T5.unique3 = T10.unique3             AND T4.unique3 = V.hundred(+)             AND T4.ten = V.ten(+)) V WHERE T4.thousand = 5; The execution plan for query B is shown below. In the execution plan BX, note the keyword 'VIEW PUSHED PREDICATE' indicates that the view has undergone the join predicate pushdown transformation. The join predicates (shown here in red) have been moved into the view V; these join predicates open up index access paths thereby enabling index-based nested-loop join of the view. With join predicate pushdown, the cost of query A has come down from 62 to 32.  As mentioned earlier, the join predicate pushdown transformation is cost-based, and a join predicate pushed-down plan is selected only when it reduces the overall cost. Consider another example of a query C, which contains a view with the UNION ALL set operator.C: SELECT R.unique1, V.unique3 FROM T_5K R,            (SELECT T1.unique3, T2.unique1+T1.unique1             FROM T_5K T1, T_10K T2             WHERE T1.unique1 = T2.unique1             UNION ALL             SELECT T1.unique3, T2.unique2             FROM G_4K T1, T_10K T2             WHERE T1.unique1 = T2.unique1) V WHERE R.unique3 = V.unique3 and R.thousand < 1; The execution plan of query C is shown below. In the above, 'VIEW UNION ALL PUSHED PREDICATE' indicates that the UNION ALL view has undergone the join predicate pushdown transformation. As can be seen, here the join predicate has been replicated and pushed inside every branch of the UNION ALL view. The join predicates (shown here in red) open up index access paths thereby enabling index-based nested loop join of the view. Consider query D as an example of join predicate pushdown into a distinct view. We have the following cardinalities of the tables involved in query D: Sales (1,016,271), Customers (50,000), and Costs (787,766).  D: SELECT C.cust_last_name, C.cust_city FROM customers C,            (SELECT DISTINCT S.cust_id             FROM sales S, costs CT             WHERE S.prod_id = CT.prod_id and CT.unit_price > 70) V WHERE C.cust_state_province = 'CA' and C.cust_id = V.cust_id; The execution plan of query D is shown below. As shown in XD, when query D undergoes join predicate pushdown transformation, the expensive DISTINCT operator is removed and the join is converted into a semi-join; this is possible, since all the SELECT list items of the view participate in an equi-join with the outer tables. Under similar conditions, when a group-by view undergoes join predicate pushdown transformation, the expensive group-by operator can also be removed. With the join predicate pushdown transformation, the elapsed time of query D came down from 63 seconds to 5 seconds. Since distinct and group-by views are mergeable views, the cost-based transformation framework also compares the cost of merging the view with that of join predicate pushdown in selecting the most optimal execution plan. Summary We have tried to illustrate the basic ideas behind join predicate pushdown on different types of views by showing example queries that are quite simple. Oracle can handle far more complex queries and other types of views not shown here in the examples. Again many thanks to Rafi Ahmed for the content of this blog post.

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• Using Durandal to Create Single Page Apps

  - by Stephen.Walther

  A few days ago, I gave a talk on building Single Page Apps on the Microsoft Stack. In that talk, I recommended that people use Knockout, Sammy, and RequireJS to build their presentation layer and use the ASP.NET Web API to expose data from their server. After I gave the talk, several people contacted me and suggested that I investigate a new open-source JavaScript library named Durandal. Durandal stitches together Knockout, Sammy, and RequireJS to make it easier to use these technologies together. In this blog entry, I want to provide a brief walkthrough of using Durandal to create a simple Single Page App. I am going to demonstrate how you can create a simple Movies App which contains (virtual) pages for viewing a list of movies, adding new movies, and viewing movie details. The goal of this blog entry is to give you a sense of what it is like to build apps with Durandal. Installing Durandal First things first. How do you get Durandal? The GitHub project for Durandal is located here: https://github.com/BlueSpire/Durandal The Wiki — located at the GitHub project — contains all of the current documentation for Durandal. Currently, the documentation is a little sparse, but it is enough to get you started. Instead of downloading the Durandal source from GitHub, a better option for getting started with Durandal is to install one of the Durandal NuGet packages. I built the Movies App described in this blog entry by first creating a new ASP.NET MVC 4 Web Application with the Basic Template. Next, I executed the following command from the Package Manager Console: Install-Package Durandal.StarterKit As you can see from the screenshot of the Package Manager Console above, the Durandal Starter Kit package has several dependencies including: · jQuery · Knockout · Sammy · Twitter Bootstrap The Durandal Starter Kit package includes a sample Durandal application. You can get to the Starter Kit app by navigating to the Durandal controller. Unfortunately, when I first tried to run the Starter Kit app, I got an error because the Starter Kit is hard-coded to use a particular version of jQuery which is already out of date. You can fix this issue by modifying the App_Start\DurandalBundleConfig.cs file so it is jQuery version agnostic like this: bundles.Add( new ScriptBundle("~/scripts/vendor") .Include("~/Scripts/jquery-{version}.js") .Include("~/Scripts/knockout-{version}.js") .Include("~/Scripts/sammy-{version}.js") // .Include("~/Scripts/jquery-1.9.0.min.js") // .Include("~/Scripts/knockout-2.2.1.js") // .Include("~/Scripts/sammy-0.7.4.min.js") .Include("~/Scripts/bootstrap.min.js") ); The recommendation is that you create a Durandal app in a folder off your project root named App. The App folder in the Starter Kit contains the following subfolders and files: · durandal – This folder contains the actual durandal JavaScript library. · viewmodels – This folder contains all of your application’s view models. · views – This folder contains all of your application’s views. · main.js — This file contains all of the JavaScript startup code for your app including the client-side routing configuration. · main-built.js – This file contains an optimized version of your application. You need to build this file by using the RequireJS optimizer (unfortunately, before you can run the optimizer, you must first install NodeJS). For the purpose of this blog entry, I wanted to start from scratch when building the Movies app, so I deleted all of these files and folders except for the durandal folder which contains the durandal library. Creating the ASP.NET MVC Controller and View A Durandal app is built using a single server-side ASP.NET MVC controller and ASP.NET MVC view. A Durandal app is a Single Page App. When you navigate between pages, you are not navigating to new pages on the server. Instead, you are loading new virtual pages into the one-and-only-one server-side view. For the Movies app, I created the following ASP.NET MVC Home controller: public class HomeController : Controller { public ActionResult Index() { return View(); } } There is nothing special about the Home controller – it is as basic as it gets. Next, I created the following server-side ASP.NET view. This is the one-and-only server-side view used by the Movies app: @{ Layout = null; } <!DOCTYPE html> <html> <head> <title>Index</title> </head> <body> <div id="applicationHost"> Loading app.... </div> @Scripts.Render("~/scripts/vendor") <script type="text/javascript" src="~/App/durandal/amd/require.js" data-main="/App/main"></script> </body> </html> Notice that I set the Layout property for the view to the value null. If you neglect to do this, then the default ASP.NET MVC layout will be applied to the view and you will get the <!DOCTYPE> and opening and closing <html> tags twice. Next, notice that the view contains a DIV element with the Id applicationHost. This marks the area where virtual pages are loaded. When you navigate from page to page in a Durandal app, HTML page fragments are retrieved from the server and stuck in the applicationHost DIV element. Inside the applicationHost element, you can place any content which you want to display when a Durandal app is starting up. For example, you can create a fancy splash screen. I opted for simply displaying the text “Loading app…”: Next, notice the view above includes a call to the Scripts.Render() helper. This helper renders out all of the JavaScript files required by the Durandal library such as jQuery and Knockout. Remember to fix the App_Start\DurandalBundleConfig.cs as described above or Durandal will attempt to load an old version of jQuery and throw a JavaScript exception and stop working. Your application JavaScript code is not included in the scripts rendered by the Scripts.Render helper. Your application code is loaded dynamically by RequireJS with the help of the following SCRIPT element located at the bottom of the view: <script type="text/javascript" src="~/App/durandal/amd/require.js" data-main="/App/main"></script> The data-main attribute on the SCRIPT element causes RequireJS to load your /app/main.js JavaScript file to kick-off your Durandal app. Creating the Durandal Main.js File The Durandal Main.js JavaScript file, located in your App folder, contains all of the code required to configure the behavior of Durandal. Here’s what the Main.js file looks like in the case of the Movies app: require.config({ paths: { 'text': 'durandal/amd/text' } }); define(function (require) { var app = require('durandal/app'), viewLocator = require('durandal/viewLocator'), system = require('durandal/system'), router = require('durandal/plugins/router'); //>>excludeStart("build", true); system.debug(true); //>>excludeEnd("build"); app.start().then(function () { //Replace 'viewmodels' in the moduleId with 'views' to locate the view. //Look for partial views in a 'views' folder in the root. viewLocator.useConvention(); //configure routing router.useConvention(); router.mapNav("movies/show"); router.mapNav("movies/add"); router.mapNav("movies/details/:id"); app.adaptToDevice(); //Show the app by setting the root view model for our application with a transition. app.setRoot('viewmodels/shell', 'entrance'); }); }); There are three important things to notice about the main.js file above. First, notice that it contains a section which enables debugging which looks like this: //>>excludeStart(“build”, true); system.debug(true); //>>excludeEnd(“build”); This code enables debugging for your Durandal app which is very useful when things go wrong. When you call system.debug(true), Durandal writes out debugging information to your browser JavaScript console. For example, you can use the debugging information to diagnose issues with your client-side routes: (The funny looking //> symbols around the system.debug() call are RequireJS optimizer pragmas). The main.js file is also the place where you configure your client-side routes. In the case of the Movies app, the main.js file is used to configure routes for three page: the movies show, add, and details pages. //configure routing router.useConvention(); router.mapNav("movies/show"); router.mapNav("movies/add"); router.mapNav("movies/details/:id");   The route for movie details includes a route parameter named id. Later, we will use the id parameter to lookup and display the details for the right movie. Finally, the main.js file above contains the following line of code: //Show the app by setting the root view model for our application with a transition. app.setRoot('viewmodels/shell', 'entrance'); This line of code causes Durandal to load up a JavaScript file named shell.js and an HTML fragment named shell.html. I’ll discuss the shell in the next section. Creating the Durandal Shell You can think of the Durandal shell as the layout or master page for a Durandal app. The shell is where you put all of the content which you want to remain constant as a user navigates from virtual page to virtual page. For example, the shell is a great place to put your website logo and navigation links. The Durandal shell is composed from two parts: a JavaScript file and an HTML file. Here’s what the HTML file looks like for the Movies app: <h1>Movies App</h1> <div class="container-fluid page-host"> <!--ko compose: { model: router.activeItem, //wiring the router afterCompose: router.afterCompose, //wiring the router transition:'entrance', //use the 'entrance' transition when switching views cacheViews:true //telling composition to keep views in the dom, and reuse them (only a good idea with singleton view models) }--><!--/ko--> </div> And here is what the JavaScript file looks like: define(function (require) { var router = require('durandal/plugins/router'); return { router: router, activate: function () { return router.activate('movies/show'); } }; }); The JavaScript file contains the view model for the shell. This view model returns the Durandal router so you can access the list of configured routes from your shell. Notice that the JavaScript file includes a function named activate(). This function loads the movies/show page as the first page in the Movies app. If you want to create a different default Durandal page, then pass the name of a different age to the router.activate() method. Creating the Movies Show Page Durandal pages are created out of a view model and a view. The view model contains all of the data and view logic required for the view. The view contains all of the HTML markup for rendering the view model. Let’s start with the movies show page. The movies show page displays a list of movies. The view model for the show page looks like this: define(function (require) { var moviesRepository = require("repositories/moviesRepository"); return { movies: ko.observable(), activate: function() { this.movies(moviesRepository.listMovies()); } }; }); You create a view model by defining a new RequireJS module (see http://requirejs.org). You create a RequireJS module by placing all of your JavaScript code into an anonymous function passed to the RequireJS define() method. A RequireJS module has two parts. You retrieve all of the modules which your module requires at the top of your module. The code above depends on another RequireJS module named repositories/moviesRepository. Next, you return the implementation of your module. The code above returns a JavaScript object which contains a property named movies and a method named activate. The activate() method is a magic method which Durandal calls whenever it activates your view model. Your view model is activated whenever you navigate to a page which uses it. In the code above, the activate() method is used to get the list of movies from the movies repository and assign the list to the view model movies property. The HTML for the movies show page looks like this: <table> <thead> <tr> <th>Title</th><th>Director</th> </tr> </thead> <tbody data-bind="foreach:movies"> <tr> <td data-bind="text:title"></td> <td data-bind="text:director"></td> <td><a data-bind="attr:{href:'#/movies/details/'+id}">Details</a></td> </tr> </tbody> </table> <a href="#/movies/add">Add Movie</a> Notice that this is an HTML fragment. This fragment will be stuffed into the page-host DIV element in the shell.html file which is stuffed, in turn, into the applicationHost DIV element in the server-side MVC view. The HTML markup above contains data-bind attributes used by Knockout to display the list of movies (To learn more about Knockout, visit http://knockoutjs.com). The list of movies from the view model is displayed in an HTML table. Notice that the page includes a link to a page for adding a new movie. The link uses the following URL which starts with a hash: #/movies/add. Because the link starts with a hash, clicking the link does not cause a request back to the server. Instead, you navigate to the movies/add page virtually. Creating the Movies Add Page The movies add page also consists of a view model and view. The add page enables you to add a new movie to the movie database. Here’s the view model for the add page: define(function (require) { var app = require('durandal/app'); var router = require('durandal/plugins/router'); var moviesRepository = require("repositories/moviesRepository"); return { movieToAdd: { title: ko.observable(), director: ko.observable() }, activate: function () { this.movieToAdd.title(""); this.movieToAdd.director(""); this._movieAdded = false; }, canDeactivate: function () { if (this._movieAdded == false) { return app.showMessage('Are you sure you want to leave this page?', 'Navigate', ['Yes', 'No']); } else { return true; } }, addMovie: function () { // Add movie to db moviesRepository.addMovie(ko.toJS(this.movieToAdd)); // flag new movie this._movieAdded = true; // return to list of movies router.navigateTo("#/movies/show"); } }; }); The view model contains one property named movieToAdd which is bound to the add movie form. The view model also has the following three methods: 1. activate() – This method is called by Durandal when you navigate to the add movie page. The activate() method resets the add movie form by clearing out the movie title and director properties. 2. canDeactivate() – This method is called by Durandal when you attempt to navigate away from the add movie page. If you return false then navigation is cancelled. 3. addMovie() – This method executes when the add movie form is submitted. This code adds the new movie to the movie repository. I really like the Durandal canDeactivate() method. In the code above, I use the canDeactivate() method to show a warning to a user if they navigate away from the add movie page – either by clicking the Cancel button or by hitting the browser back button – before submitting the add movie form: The view for the add movie page looks like this: <form data-bind="submit:addMovie"> <fieldset> <legend>Add Movie</legend> <div> <label> Title: <input data-bind="value:movieToAdd.title" required /> </label> </div> <div> <label> Director: <input data-bind="value:movieToAdd.director" required /> </label> </div> <div> <input type="submit" value="Add" /> <a href="#/movies/show">Cancel</a> </div> </fieldset> </form> I am using Knockout to bind the movieToAdd property from the view model to the INPUT elements of the HTML form. Notice that the FORM element includes a data-bind attribute which invokes the addMovie() method from the view model when the HTML form is submitted. Creating the Movies Details Page You navigate to the movies details Page by clicking the Details link which appears next to each movie in the movies show page: The Details links pass the movie ids to the details page: #/movies/details/0 #/movies/details/1 #/movies/details/2 Here’s what the view model for the movies details page looks like: define(function (require) { var router = require('durandal/plugins/router'); var moviesRepository = require("repositories/moviesRepository"); return { movieToShow: { title: ko.observable(), director: ko.observable() }, activate: function (context) { // Grab movie from repository var movie = moviesRepository.getMovie(context.id); // Add to view model this.movieToShow.title(movie.title); this.movieToShow.director(movie.director); } }; }); Notice that the view model activate() method accepts a parameter named context. You can take advantage of the context parameter to retrieve route parameters such as the movie Id. In the code above, the context.id property is used to retrieve the correct movie from the movie repository and the movie is assigned to a property named movieToShow exposed by the view model. The movie details view displays the movieToShow property by taking advantage of Knockout bindings: <div> <h2 data-bind="text:movieToShow.title"></h2> directed by <span data-bind="text:movieToShow.director"></span> </div> Summary The goal of this blog entry was to walkthrough building a simple Single Page App using Durandal and to get a feel for what it is like to use this library. I really like how Durandal stitches together Knockout, Sammy, and RequireJS and establishes patterns for using these libraries to build Single Page Apps. Having a standard pattern which developers on a team can use to build new pages is super valuable. Once you get the hang of it, using Durandal to create new virtual pages is dead simple. Just define a new route, view model, and view and you are done. I also appreciate the fact that Durandal did not attempt to re-invent the wheel and that Durandal leverages existing JavaScript libraries such as Knockout, RequireJS, and Sammy. These existing libraries are powerful libraries and I have already invested a considerable amount of time in learning how to use them. Durandal makes it easier to use these libraries together without losing any of their power. Durandal has some additional interesting features which I have not had a chance to play with yet. For example, you can use the RequireJS optimizer to combine and minify all of a Durandal app’s code. Also, Durandal supports a way to create custom widgets (client-side controls) by composing widgets from a controller and view. You can download the code for the Movies app by clicking the following link (this is a Visual Studio 2012 project): Durandal Movie App

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• Partition Wise Joins II

  - by jean-pierre.dijcks

  One of the things that I did not talk about in the initial partition wise join post was the effect it has on resource allocation on the database server. When Oracle applies a different join method - e.g. not PWJ - what you will see in SQL Monitor (in Enterprise Manager) or in an Explain Plan is a set of producers and a set of consumers. The producers scan the tables in the the join. If there are two tables the producers first scan one table, then the other. The producers thus provide data to the consumers, and when the consumers have the data from both scans they do the join and give the data to the query coordinator. Now that behavior means that if you choose a degree of parallelism of 4 to run such query with, Oracle will allocate 8 parallel processes. Of these 8 processes 4 are producers and 4 are consumers. The consumers only actually do work once the producers are fully done with scanning both sides of the join. In the plan above you can see that the producers access table SALES [line 11] and then do a PX SEND [line 9]. That is the producer set of processes working. The consumers receive that data [line 8] and twiddle their thumbs while the producers go on and scan CUSTOMERS. The producers send that data to the consumer indicated by PX SEND [line 5]. After receiving that data [line 4] the consumers do the actual join [line 3] and give the data to the QC [line 2]. BTW, the myth that you see twice the number of processes due to the setting PARALLEL_THREADS_PER_CPU=2 is obviously not true. The above is why you will see 2 times the processes of the DOP. In a PWJ plan the consumers are not present. Instead of producing rows and giving those to different processes, a PWJ only uses a single set of processes. Each process reads its piece of the join across the two tables and performs the join. The plan here is notably different from the initial plan. First of all the hash join is done right on top of both table scans [line 8]. This query is a little more complex than the previous so there is a bit of noise above that bit of info, but for this post, lets ignore that (sort stuff). The important piece here is that the PWJ plan typically will be faster and from a PX process number / resources typically cheaper. You may want to look out for those plans and try to get those to appear a lot... CREDITS: credits for the plans and some of the info on the plans go to Maria, as she actually produced these plans and is the expert on plans in general... You can see her talk about explaining the explain plan and other optimizer stuff over here: ODTUG in Washington DC, June 27 - July 1 On the Optimizer blog At OpenWorld in San Francisco, September 19 - 23 Happy joining and hope to see you all at ODTUG and OOW...

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