Скачать или смотреть 🎯SQL Server Query Tuning Series: Best Practices to Handle Gather Streams in High CPU Scenarios🎯

What Is the Gather Streams Operator? 🤔
The Gather Streams operator plays an essential role in parallel execution plans in SQL Server. When queries are executed in parallel, the Gather Streams operator is used to combine the multiple parallel threads into a single result set for final output.

In a nutshell:

It gathers parallel streams of data and consolidates them into one.
It’s typically found when SQL Server decides to parallelize a query for better performance.
Sounds straightforward, right? But this operator can become a significant performance bottleneck when there are CPU constraints or poor query design. Let’s understand why. 👇

How Gather Streams Operator Works 💡
Before diving into the optimization techniques, let's break down how the Gather Streams operator works at a technical level.

1. Parallel Execution Plan 🛠️
Parallelism in SQL Server is designed to speed up queries by splitting the workload across multiple CPUs. When SQL Server detects that a query would benefit from parallelism (based on the cost and available system resources), it splits the execution across multiple threads.

However, SQL Server needs a mechanism to gather all these parallel streams back into a single cohesive result. This is where the Gather Streams operator comes into play.

2. Consolidation Process 🔄
The Gather Streams operator collects rows from each parallel thread and then returns them in the original order (if order preservation is required) or any order (when not needed). While this works efficiently in many cases, there are times when it can be a bottleneck.

Here’s how:

When there are a high number of parallel threads, the CPU must work harder to coordinate and consolidate the results.
If SQL Server needs to maintain row order, it can further add to the complexity of the gathering process.
In some cases, the CPU cost of handling these parallel streams can outweigh the benefits of parallelism itself! 😲

How Gather Streams Operator Can Lead to CPU Bottlenecks 🖥️💣
Now, let’s talk about why the Gather Streams operator can degrade performance, particularly in cases of CPU bottlenecks.

1. High CPU Usage from Thread Consolidation 🏋️‍♂️
When SQL Server runs queries in parallel, each thread runs independently to speed up operations. However, bringing back all those independent threads into one final result set is not trivial. The CPU has to handle the synchronization and combination of data, which can be resource-intensive—especially if:

Data skew exists, meaning some threads have a significantly larger workload than others.
The CPU has to ensure that the gathered results are in the correct order, adding another layer of complexity.
This added workload can cause CPU spikes, resulting in degraded performance and longer query execution times.

2. Parallelism Threshold Mismanagement 🎛️
The cost threshold for parallelism setting determines when SQL Server will parallelize a query. If this value is set too low, simple queries might unnecessarily run in parallel, leading to excessive use of the Gather Streams operator, and therefore, excessive CPU consumption.

If your system is already experiencing high CPU utilization, excessive parallelism can push your system into CPU overload and negatively impact overall performance.

3. Inefficient Query Design 🛑
Even though the Gather Streams operator is a key feature of parallel execution, bad query design can exacerbate its negative impact. For instance:

Suboptimal indexing strategies can increase the need for parallelism unnecessarily.
Data skew across partitions can lead to some threads being overloaded with data, while others remain idle, further increasing CPU pressure.
An inefficient query plan might end up misusing the Gather Streams operator, causing significant performance degradation.

Best Practices for Handling Gather Streams in High CPU Scenarios 🔧
Handling the Gather Streams operator effectively requires optimizing both the query and the server settings. Let’s walk through some best practices to minimize CPU impact and improve performance.

1. Adjust the Cost Threshold for Parallelism ⚙️
The cost threshold for parallelism is a critical configuration setting in SQL Server that dictates when a query should be considered for parallel execution. By default, this value is set to 5, which might be too low for modern hardware.

Recommended Approach:
Increase the threshold value: Start by increasing the cost threshold for parallelism to 25-50, depending on the hardware capabilities.
By increasing this value, you prevent simple queries from running in parallel unnecessarily, which can reduce the CPU load from the Gather Streams operator.
T-SQL Example:
EXEC sp_configure 'show advanced options', 1;
RECONFIGURE;
EXEC sp_configure 'cost threshold for parallelism', 30; -- Adjust as per your needs
RECONFIGURE;