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A Bulk insert is a process or method provided by a database management system to load multiple rows of data into a database table. Bulk insert may refer to: Transact-SQL BULK INSERT statement; PL/SQL BULK COLLECT and FORALL statements; MySQL LOAD DATA INFILE statement; PostgreSQL COPY statement
An INSERT statement can also be used to retrieve data from other tables, modify it if necessary and insert it directly into the table. All this is done in a single SQL statement that does not involve any intermediary processing in the client application. A subselect is used instead of the VALUES clause. The subselect can contain joins, function ...
Transact-SQL is central to using Microsoft SQL Server. All applications that communicate with an instance of SQL Server do so by sending Transact-SQL statements to the server, regardless of the user interface of the application. Stored procedures in SQL Server are executable server-side routines. The advantage of stored procedures is the ...
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
It also supports >REPLACE INTO syntax, [6] which first attempts an insert, and if that fails, deletes the row, if exists, and then inserts the new one. There is also an IGNORE clause for the INSERT statement, [ 7 ] which tells the server to ignore "duplicate key" errors and go on (existing rows will not be inserted or updated, but all new rows ...
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A commitment to SQL code containing inner joins assumes NULL join columns will not be introduced by future changes, including vendor updates, design changes and bulk processing outside of the application's data validation rules such as data conversions, migrations, bulk imports and merges.
Bulk load operations whenever possible; Still, even using bulk operations, database access is usually the bottleneck in the ETL process. Some common methods used to increase performance are: Partition tables (and indices): try to keep partitions similar in size (watch for null values that can skew the partitioning)