Bulk updates oracle

Per th question, if you only want to continue updating even if record fails with error logging then i think you should go with the DML error logging clause of Oracle.

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Learn more. Bulk update with commit in oracle Ask Question. Asked 4 years, 10 months ago. Active 1 year, 7 months ago. Viewed 22k times. OldProgrammer Oracle technology is changing and we strive to update our BC Oracle support information. If you find an error or have a suggestion for improving our content, we would appreciate your feedback. Just e-mail: and include the URL for the page. All rights reserved by Burleson. Remote Emergency Support provided by Conversational.

Search BC Oracle Sites. I worry about how ETL tools apply updates did you know DataStage applys updates singly, but batches inserts in arrays? It would be fair to say I obsess about them. A little bit. The two most common forms of Bulk Updates are: Update almost every row in the table.

This is common when applying data patches and adding new columns. Updating a small proportion of rows in a very large table. Case 1 is uninteresting. The fastest way to update every row in the table is to rebuild the table from scratch. All of these methods below will perform worse. Case 2 is common in Data Warehouses and overnight batch jobs. We have a table containing years worth of data, most of which is static; we are updating selected rows that were recently inserted and are still volatile.

This case is the subject of our test. For the purposes of the test, we will assume that the target table of the update is arbitrarily large, and we want to avoid things like full-scans and index rebuilds. I want to test on a level playing field and remove special factors that unfairly favour one method, so there are some rules:.

The data has the following characteristics: TEST. PK will contain values PK is poorly clustered. PK values of 1,2, and 3 are adjacent in the primary key index but one-million rows apart in the table.

FK will contain values For the first round of testing, the column FK will be indexed with a simple b-tree index. I include it here because it allows us to compare the cost of context-switches to the cost of updates. Update-wise, it looks as though it should perform the same as the Explicit Cursor Loop.

The difference is that the Implicit Cursor internally performs bulk fetches, which should be faster than the Explicit Cursor because of the reduced context switches. This method is pretty common. I generally recommend against it for high-volume updates because the SET sub-query is nested, meaning it is performed once for each row updated.

This one is gaining in popularity. The biggest drawback to this method is readability. This needs a unique index on TEST1. PK in order to enforce key preservation. The modern equivalent of the Updateable Join View. We are using the update-only version here. The bulk collect method is faster method than traditional methods.

We require to create a type variable where we can fetch all customer data and we need to use bulk collect statement in forall clause so that the records in the forall clause or specified table will be updated correctly. If we can see the Elapsed time it is around 54 seconds which is more faster than other methods.

The direct update will take 58 seconds to update all the records. The fastest way to update the bulk of records is using the Merge statement. The merge statement took 36 seconds to update records in fast way. With using the inline view method the bulk update will complete approximately in 38 seconds which is also the fast way like Merge statement. If we can observe the details in above 6 queries the Update SQL statement would be giving the better performance than Bulk collect and for all.