Mass updating sql database
A requirement arises in many systems to update multiple SQL database rows.For small numbers of rows requiring updates, it can be adequate to use an UPDATE statement for each row that requires an update.But if there are a large number of rows that require an update, then the overhead of issuing large numbers of UPDATE statements can result in the operation as a whole taking a long time to complete.The traditional advice for improving performance for multiple UPDATE statements is to “prepare” the required query once, and then “execute” the prepared query once for each row requiring an update.What I love about writing SQL Tuning articles is that I very rarely end up publishing the findings I set out to achieve. 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. 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.With this one, I set out to demonstrate the advantages of PARALLEL DML, didn't find what I thought I would, and ended up testing 8 different techniques to find out how they differed. The methods covered include both PL/SQL and SQL approaches.The first 4 records are already present in the Table, the only difference is that the countries of some records are modified for illustrating the bulk update operation.Here Mudassar Ahmed Khan has explained how to insert data from Excel sheet into SQL Server database table using Sql Bulk Copy in C# and VB. Sql Bulk Copy class as the name suggests does bulk insert from one source to another and hence all rows from the Excel sheet can be easily read and inserted using the Sql Bulk Copy class.
In addition to this, it might also cause blocking issues.
The SQL Server (Transact-SQL) UPDATE statement is used to update existing records in a table in a SQL Server database.
There are 3 syntaxes for the UPDATE statement depending on whether you are performing a traditional update or updating one table with data from another table.
I spend an inordinate proportion of design time of an ETL system worrying about the relative proportion of rows inserted vs updated.
I want to test on a level playing field and remove special factors that unfairly favour one method, so there are some rules: TEST (Update Source) - 100K rows TEST (Update target) - 10M rows Name Type Name Type ------------------------------ ------------ ------------------------------ ------------ PK NUMBER PK NUMBER FK NUMBER FK NUMBER FILL VARCHAR2(40) FILL VARCHAR2(40) Not many people code this way, but there are some Pro*C programmers out there who are used to Explicit Cursor Loops (OPEN, FETCH and CLOSE commands) and translate these techniques directly to PL/SQL.
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), how I might cluster rows together that are subject to updates, and what I might do if I just get too many updates to handle. The fastest way to update every row in the table is to rebuild the table from scratch. Case 2 is common in Data Warehouses and overnight batch jobs.