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Note It is likely that in the future the F# sequence expression syntax will include support for specifying

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Now, if we use two different transactions, we can see that both get different records. We also see that both get different records concurrently (using autonomous transactions once again to demonstrate the concurrency issues): ops$tkyte%ORA11GR2> declare 2 l_rec t%rowtype; 3 begin 4 l_rec := get_first_unlocked_row; 5 dbms_output.put_line( 'I got row ' || l_rec.id || ', ' || l_rec.payload ); 6 end; 7 / I got row 2, payload 2 PL/SQL procedure successfully completed. ops$tkyte%ORA11GR2> ops$tkyte%ORA11GR2> declare 2 pragma autonomous_transaction; 3 l_rec t%rowtype; 4 begin 5 l_rec := get_first_unlocked_row; 6 dbms_output.put_line( 'I got row ' || l_rec.id || ', ' || l_rec.payload ); 7 commit; 8 end; 9 / I got row 4, payload 4 PL/SQL procedure successfully completed. Now, in Oracle 11g Release 1 and above, we can achieve the above logic using the SKIP LOCKED clause. In the following example we ll do two concurrent transactions again, observing that they each find and lock separate records concurrently. ops$tkyte%ORA11GR2> declare 2 l_rec t%rowtype; 3 cursor c 4 is

5 select * 6 from t 7 where decode(processed_flag,'N','N') = 'N' 8 FOR UPDATE 9 SKIP LOCKED; 10 begin 11 open c; 12 fetch c into l_rec; 13 if ( c%found ) 14 then 15 dbms_output.put_line( 'I got row ' || l_rec.id || ', ' || l_rec.payload ); 16 end if; 17 close c; 18 end; 19 / I got row 2, payload 2 PL/SQL procedure successfully completed. ops$tkyte%ORA11GR2> ops$tkyte%ORA11GR2> declare 2 pragma autonomous_transaction; 3 l_rec t%rowtype; 4 cursor c 5 is 6 select * 7 from t 8 where decode(processed_flag,'N','N') = 'N' 9 FOR UPDATE 10 SKIP LOCKED; 11 begin 12 open c; 13 fetch c into l_rec; 14 if ( c%found ) 15 then 16 dbms_output.put_line( 'I got row ' || l_rec.id || ', ' || l_rec.payload ); 17 end if; 18 close c; 19 commit; 20 end; 21 / I got row 4, payload 4 PL/SQL procedure successfully completed. Both of the preceding solutions would help to solve the second serialization problem my client was having when processing messages. But how much easier would the solution have been if my client had just used Advanced Queuing and invoked DBMS_AQ.DEQUEUE To fix the serialization issue for the message producer, we had to implement a function-based index. To fix the serialization issue for the consumer, we had to use that function-based index to retrieve the records and write code. So we fixed their major problem, caused by not fully understanding the tools they were using and found only after lots of looking and study since the system was not nicely instrumented. What we hadn t fixed yet were the following issues:

grouping and aggregation operations within the expression syntax. However, at the time of writing, it was necessary to explicitly use operators such as Seq.orderBy and Seq.groupBy for these operations.

In 11, Indexes, we ll see the salient effects of this feature of PL/SQL when measuring the performance of reverse key indexes. If you d like to see how PL/SQL performs in the manner described above, skip there for a moment to review the reverse key index benchmark.

It is interesting to note exactly when integrity constraints are checked. By default, integrity constraints are checked after the entire SQL statement has been processed. There are also deferrable constraints that permit the validation of integrity constraints to be postponed until either the application requests they be validated by issuing a SET CONSTRAINTS ALL IMMEDIATE command or upon issuing a COMMIT.

In this section you saw how you can use aggregate sequence operators and sequence expressions to query and manipulate in-memory data structures using a SQL-like syntax. This is essentially the idea behind Microsoft s LINQ technology. We apply the same techniques to queries over relational data (LINQ to SQL) later in this chapter. In 3 you saw that sequences can be used to wrap collections and that a number of collection data types implement the sequence interface. It is possible to provide parallel implementations for the iteration, aggregation, and transformation operations of these data types for instance, a parallel list implementation that uses worker threads and assume independence between the transformation steps. This idea forms the basis of PLINQ, a parallel version of LINQ. PLINQ also covers LINQ to SQL where parallelism is introduced in the SQL code that is generated behind the scenes.