Where does direct path load perform SQL processing in oracle? - oracle

I am new to oracle database. Does direct path load perform SQL processing like syntax check, semantic check etc .. If direct path engine bypass SGA and use PGA to load the data in parallel faster above the high water mark of object, where does SQL processing happen? In PGA?
Thanks in advance!

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What is the difference between Parse, Execute and Fetch?

The tkprof utility generates the trace file with three types of information which are Parse, Execute and Fetch. Could you please explain what is the difference between these three? What will be counted as Parse and Execute and Fetch?
Thanks in advance for your help.
When you issue a SQL statement, Oracle:
Parses your SQL statement. That means Oracle analyzes the correctness of the syntax, checks the access rights, and creates the execution plan (or takes it from the cache).
Actually executes your SQL statement.
For SELECT statements, Oracle fetches the rows returned by your query. (For INSERT, DELETE, and UPDATE Oracle fetches nothing).
The numbers of these operations is written in the trace.
If we are talking about the performance tuning, the idea is to parse SQL statements once and then keep them in cache, execute them when you need and do not close cursors if you will need them again to reduce number of fetches.

Parameter for setting up parallel processing in Oracle Thin JDBC Connect String

i would like to know if there is a connect param, that i can use in JDBC Thin Oracle Connection URL,
to tell the Oracle DB that i want to use Parallelism in processing the queries.
The Application, that should be use this parameter generates Statements during runtime and fires them against the Database, so i can't update or optimize them. In nearly every query i run in timeouts and the User on the other side gets an error message.
If i fire the generated Statements and send them with /* parallel */ Hint with the SQL Developer, i have a much better performance.
Maybe someone has a hint, that i can achive a better performance.
You could use a logon trigger to force parallel execution of all query statements in the session for which parallelization is possible. This would override any default parallelism property on individual objects.
CREATE OR REPLACE TRIGGER USER1.LOGON_TRG
AFTER LOGON ON SCHEMA
BEGIN
EXECUTE IMMEDIATE 'ALTER SESSION FORCE PARALLEL QUERY 4';
END;
/
https://docs.oracle.com/en/database/oracle/oracle-database/19/vldbg/parameters-parallel-exec.html#GUID-FEDED00B-57AF-4BB0-ACDB-73F43B71754A

in a jdbc batch insert, when exactly the blob must be free

When using (oracle) jdbc addbatch for an insert statement having a blob, when should we free the blob - after the addBatch or after the executeBatch?
You should free them only after execution. The JDBC 4.3 specification (section 14.1.4) says:
The sets of parameter values together with their associated
parameterized update commands can then be sent to the underlying data
source engine for execution as a single unit.
In other words, the blob will be used on execution of the batch, freeing it earlier would mean it is no longer available to be used at time of execution.

Is there a way to call SQL before SQL*Loader imports?

I am using sqlldr to do a bulk load of data, but I need to set a context value before the data loads so that a trigger has a value, but I cannot find a way to execute arbitrary sql as part of a data load.
In theory an after logon trigger can run code for you, but it would be difficult to switch functionality like that on and off on demand.
Consider using an external table instead of SQL*Loader, and you can do just about whatever you like as part of the session.

Cursors in Database compared to JDBC cursors and SQLJ cursors

Could someone briefly compare and contrast the use of cursors in SQL procedures with their use
in
JDBC
SQLJ
Queries as static when using SQLj. Instead, they are dynamic when using JDBC, this means that query compilation and access plan is calculated when the query is executed. In SQLj, these steps are done at compilation time, leaving the execution only to access the data.

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