SLAM_load_bulk

Overview

Provides the highest level of control over large data loads, including batch sizes and serial vs parallel processing. Bulk v1 supports hardDelete. Note that Salesforce specifically has not validated Bulk v1 for use with custom address fields and therefore you should look to Bulk v2 in those situations

Performance Tip: By default, Speediful enables parallel data loading with Bulk v1 API. This parallelizes the loading operation on the Salesforce server. It can lead to dramatic time reductions in loading operations vs serial loading. However, judicious use is advised, as this option can potentially be detrimental to overall throughput when loading to objects with lengthy triggered business process flows or to junction objects. To disable parallel loading, set @bulk_parallel = 0 or consider using SLAM_lockbuster

Parameters

Name	Type	Default	Description
@sObject	NVARCHAR	Required	Salesforce object name to load data into
@table	NVARCHAR	Required	Input SQL table containing data to load
@operation	NVARCHAR	Required	Operation type ('insert', 'update', 'upsert', 'delete', 'hardDelete')
@bulk_parallel	BIT	1	Enable parallel batch processing when set to 1. Serial mode when 0
@batch_size	INT	10000	Number of records per batch (max 10000)
@externalId	NVARCHAR	NULL	External ID field name (required for upsert operations)
@failure_threshold	DECIMAL(5,2)	100	Allowable failure rate (0-100) before throwing a SQL error. When 100, no error will be thrown

Usage Examples

Insert new Account records with minimal parameters:

EXEC dbo.SLAM_load_bulk
    @sObject = 'Account',
    @table = 'Account_insert',
    @operation = 'insert'

Upsert Contact records using external ID with parallel processing:

EXEC dbo.SLAM_load_bulk
    @sObject = 'Contact',
    @table = 'Contact_upsert',
    @operation = 'upsert',
    @externalId = 'Contact_External_Id__c',
    @bulk_parallel = 1,
    @batch_size = 5000

Skip the recycle bin with hardDelete:

EXEC dbo.SLAM_load_bulk
    @sObject = 'Task',
    @table = 'Task_hardDelete',
    @operation = 'hardDelete',
    @batch_size = 2500