SQL Batch Processing: A Comprehensive Guide 101

on Batch Processing, SQL, SQL Server • May 5th, 2022 • Write for Hevo

Batch Processing is essential for corporations and organizations to effectively manage massive volumes of data. It’s particularly well-suited to managing regular, repetitive tasks. Batch Processing operations are supported by SQL Server using a variety of ways. SQL Server is a relational database management system from Microsoft that is leveraged by many Fortune 100 companies.

In this article, you will understand what Batch Processing is and gain some understanding of SQL Server Integration Services(SSIS). Further in this article, you will learn about various methods to set up your SQL Batch Processing. At the end of this article, you will explore some of the key benefits offered by the SQL Batch Processing methods. So, let’s get started on setting up SQL Batch Processing.

Table of Contents

What is Batch Processing?

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Batch Processing is a method for processing huge volumes of data in a consistent and repeatable way. The batch approach allows users to process data with little or no human interaction. Batch Processing, to put it simply, is the way through which a computer completes batches of work in a nonstop, sequential manner, usually at the same time. It’s also a command that ensures that large jobs are split down into smaller portions for easier debugging.

Users acquire and store data in batches for the period of a “batch window” in batch ETL processing. This saves time and improves data processing efficiency, allowing organizations and enterprises to handle and analyze large amounts of data quickly.

You can refer to What is Batch Processing? 2022’s Comprehensive Guide to understand more about Batch Processing.

What is Microsoft SQL Server?

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Microsoft SQL Server is a Relational Database Management System (RDBMS) that is used in corporate IT to support a variety of applications such as Transaction Processing, Business Intelligence, and Analytics. SQL Server, as the name implies, is built on top of SQL, a database management and search language used by database administrators and IT professionals.

Microsoft SQL Server was first released in 1989. It is largely recognized as a superior RDBMS for on-premise and cloud implementations. This flexible database has built-in intelligence that allows businesses to boost performance, availability, and security as needed. It works with both Windows and Linux operating systems.

What is SSIS?

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SQL Server Integration Services(SSIS) is a platform that allows you to create enterprise-level data integration and data transformation solutions. SSIS is a data warehousing technology that can be used for data extraction, loading, and transformations such as cleaning, aggregating, and combining data.

Data can be extracted and transformed from several sources, including XML data files, flat files, and relational data sources, and then loaded into one or more destinations using Integration Services. Further, in this article, you read how to set up SQL Batch Processing using SSIS.

A comprehensive collection of built-in activities and transformations are included in Integration Services. Package-building graphical tools and the SSIS Catalog database to store, launch, and manage packages are also offered in the SSIS. Refer to SSIS How to Create an ETL Package to learn more.

Want to dive deeper into the architecture and other features of SSIS? Read SQL Server Integration Services: A Comprehensive Guide to gain a better understanding of SSIS.

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How to Set Up SQL Server Batch Processing?

In this section, you will learn 2 methods to work with SQL Batch Processing:

Method 1: Batch Mode on Rowstore

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Many situations exist where the data set and query attributes are ideal for SQL Batch Processing, yet the table isn’t a strong fit for columnstore indexes in the SQL Server. Some of these situations can be:

  • It might be a table with a high update rate, which, if not managed effectively, can affect columnstore performance.
  • It might be a legacy table constructed before columnstore indexes were available, or a table with a schema that can’t be modified.

To solve these challenges, Batch Mode on Rowstore processing was introduced in SQL Server 2019. The Batch Mode on Rowstore execution feature offers multiple row handling capabilities simultaneously instead of the typical row-by-row processing technique.

Batch Mode on Rowstore execution is a query processing approach that has the advantage of being able to handle several rows at once. When a query conducts aggregation, sorting, and group-by operations on a big quantity of data, this strategy improves speed and reduces CPU utilization.

Method 2: SSIS Batch Processing

SQL Server Integration Services(SSIS) works well with the Toolbox’s current components to facilitate Batch Processing. An easy way to perform SQL Batch Processing in SSIS is to devise a method for grouping the rows to be processed into batches, processing each batch, and then updating each group when it is completed. 

Let’s create a simple logical flow to perform SQL Batch Processing using the SSIS package to complete the task.

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Step 1: Set Up the Database

You can choose any sample database and load it into your SQL Server. After uploading, check that all the rows are processed.

Step 2: Get a Batch List

In this step, you get a batch list. This batch list will divide the source data into batches and creates a result set with a single row for each batch.

Step 3: Process Batch Loop

After creating batches, now you create a batch loop. You can design a Foreach Loop container that iterates across the rows of the result set, executing once for each row.

Step 4: Create a Transaction Container

You need to set up a Sequence container. It includes the tasks that must be completed for each loop iteration. It also controls the transaction that will commit if everything goes well or roll back if something goes wrong.

Step 5: Append Batch

You can run a SQL task that extracts a batch of rows and inserts them into history or another table at this stage.

Step 6: Execute SQL Task

You can now conduct any SQL job, such as aggregation, which executes batch aggregations & updates an aggregation table.

Step 7: Mark Batch as Processed

After you’ve completed all of the preceding stages, you’ll need to write a script to run a SQL job that updates rows in the source table as processed.

The above steps are just one way to approach your SQL Batch Processing using SSIS. You can check out some sample examples here

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What are the Benefits of SQL Batch Processing?

Now that you have explored the 2 methods of working with SQL Batch Processing, let’s understand some of the benefits offered by these methods.

Benefits of Batch Mode on Rowstore in SQL Server

  • This method boosts the speed of analytical queries.
  • It also lowers the CPU utilization for analytical queries.
  • You can handle numerous rows simultaneously.

The results in terms of query performance and efficiency are quite excellent for queries that need aggregations over a large number of rows, which batch processing was built for.

In this example – Introducing Batch Mode on Rowstore – Microsoft Tech Community, on the same hardware, the execution time for the same query, with the same data set, went from 10 seconds to 3 seconds. That’s nearly 3x quicker with no modifications to the application or query!

Benefits of SQL Batch Processing using SSIS

  • SSIS can read from a wide range of data sources, can easily transform data in memory, and can bulk load data without the need to stage it.
  • SSIS operates as a distinct process from the database engine, allowing you to do many CPU-intensive processes without putting the database engine under strain. You can also run SSIS on a separate machine.
  • Bulk load procedures can be readily scaled up to obtain exceptionally high throughput.

Conclusion

In this article, you learned various methods to set up SQL Batch Processing. You can use the Batch mode on Rowstore or perform SQL Batch Processing in SSIS. Apart from these methods, you also explored some of the notable benefits provided by each of these methods.

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