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August 8, 2024

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SQL Server 2022

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SQL Server 2022 Query Store Enhancements: A Comprehensive Guide

SQL Server 2022 brings significant enhancements to the Query Store, a powerful feature for monitoring and optimizing query performance. In this blog, we’ll explore the improvements, how to leverage Query Store for performance tuning, and its application in Always On Availability Groups. We’ll also provide T-SQL queries to identify costly queries and discuss the advantages and business use cases of using Query Store.

What is Query Store? 🤔

Query Store is a feature in SQL Server that captures a history of queries, plans, and runtime statistics. It helps database administrators (DBAs) and developers identify and troubleshoot performance issues by providing insights into how queries are performing over time.

Key Enhancements in SQL Server 2022 🛠️

Support for Always On Availability Groups Read Replicas: One of the standout features in SQL Server 2022 is the extension of Query Store to read-only replicas in Always On Availability Groups. This allows monitoring of read workload performance without affecting the primary replica’s performance.
Improved Query Performance Analysis: Enhancements in Query Store provide more granular control over data collection and retention policies, allowing for more precise performance tuning.
Automatic Plan Correction: Query Store can automatically identify and revert to a previously good query plan if the current plan causes performance regressions.
Enhanced Data Cleanup: SQL Server 2022 introduces more efficient data cleanup processes, ensuring that Query Store doesn’t consume unnecessary storage space.

Leveraging Query Store for Performance Tuning 🎛️

To make the most of Query Store, follow these steps:

Enable Query Store: Ensure that Query Store is enabled for your database. You can do this using the following T-SQL command.

ALTER DATABASE [YourDatabaseName] SET QUERY_STORE = ON;

Monitor Performance: Use Query Store views and built-in reports in SQL Server Management Studio (SSMS) to analyze query performance over time.

Identify Regressions: Leverage the Automatic Plan Correction feature to detect and fix query performance regressions automatically.

Optimize Queries: Use the insights from Query Store to optimize queries and indexes, reducing resource consumption and improving response times.

Using Query Store on Always On Read Replicas 🛡️

Query Store on read replicas allows you to monitor read-only workloads without impacting the primary replica. To enable and configure Query Store on read replicas, use the following steps:

Enable Query Store on Primary and Read Replicas: Ensure that Query Store is enabled on both primary and secondary replicas.

ALTER DATABASE [YourDatabaseName] SET QUERY_STORE = ON (OPERATION_MODE = READ_WRITE);

On read replicas:

ALTER DATABASE [YourDatabaseName] SET QUERY_STORE = ON (OPERATION_MODE = READ_ONLY);

Monitor Read Workloads: Use Query Store to analyze read workload performance on secondary replicas. This helps in identifying and optimizing queries executed on read-only replicas.

T-SQL Queries to Check Costly Queries 🔍

Here are some T-SQL queries to find costly queries in terms of CPU, reads, and duration:

On Primary Replica

Top Queries by CPU Usage:

SELECT TOP 10
    qs.query_id,
    qs.execution_type_desc,
    qs.total_cpu_time / qs.execution_count AS avg_cpu_time,
    q.text AS query_text
FROM
    sys.query_store_runtime_stats qs
JOIN
    sys.query_store_query q ON qs.query_id = q.query_id
ORDER BY
    avg_cpu_time DESC;

Top Queries by Logical Reads:

SELECT TOP 10
    qs.query_id,
    qs.execution_type_desc,
    qs.total_logical_reads / qs.execution_count AS avg_logical_reads,
    q.text AS query_text
FROM
    sys.query_store_runtime_stats qs
JOIN
    sys.query_store_query q ON qs.query_id = q.query_id
ORDER BY
    avg_logical_reads DESC;

Top Queries by Duration:

SELECT TOP 10
    qs.query_id,
    qs.execution_type_desc,
    qs.total_duration / qs.execution_count AS avg_duration,
    q.text AS query_text
FROM
    sys.query_store_runtime_stats qs
JOIN
    sys.query_store_query q ON qs.query_id = q.query_id
ORDER BY
    avg_duration DESC;

On Read Replica

The queries on the read replica are similar but consider that the Query Store on read replicas operates in a read-only mode:

-- For CPU Usage, Logical Reads, and Duration, the same queries as above can be used.

Advantages of Using Query Store 🌟

Historical Performance Data: Query Store maintains historical data, making it easier to analyze and troubleshoot performance issues over time.
Automated Plan Correction: Automatically detects and corrects query plan regressions, reducing the need for manual intervention.
Enhanced Monitoring: Extended support to read replicas allows comprehensive monitoring of all workloads in Always On Availability Groups.
Improved Resource Management: Helps in identifying resource-intensive queries, enabling better resource allocation and management.

Business Use Case: E-commerce Website 🛒

Consider an e-commerce platform where performance is critical, especially during peak shopping seasons. By leveraging Query Store:

The DBA can monitor and optimize queries that retrieve product details, prices, and inventory status, ensuring quick response times for users.
Automatic Plan Correction helps maintain optimal performance even when changes are made to the database or application code.
Using Query Store on read replicas allows offloading read workloads from the primary replica, ensuring that write operations remain unaffected.

Conclusion 🎉

SQL Server 2022’s Query Store enhancements offer a powerful toolset for monitoring and optimizing database performance. Whether you’re managing a high-traffic e-commerce site or a critical financial application, leveraging Query Store can lead to significant performance improvements and resource optimization. Start exploring these features today to get the most out of your SQL Server environment!

For more tutorials and tips on SQL Server, including performance tuning and database management, be sure to check out our JBSWiki YouTube channel.

Thank You,
Vivek Janakiraman

Disclaimer:
The views expressed on this blog are mine alone and do not reflect the views of my company or anyone else. All postings on this blog are provided “AS IS” with no warranties, and confers no rights.

Posted by

Vivek Janakiraman

Posted on

August 3, 2024

Posted under

SQL Server 2022

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Deploying and Managing SQL Server 2022 on Kubernetes: A Comprehensive Guide

Kubernetes has become a popular choice for managing containerized applications, and SQL Server 2022 is no exception. This guide will walk you through deploying and managing SQL Server 2022 on Kubernetes, offering examples and screenshots to illustrate the process.

🛠️ Prerequisites

Before diving into the deployment, ensure you have the following:

Kubernetes Cluster: A running Kubernetes cluster (e.g., Minikube, Azure Kubernetes Service, Amazon EKS).
kubectl: The Kubernetes command-line tool, installed and configured.
Docker: Installed for container image management.

🏗️ Step-by-Step Deployment

1. Create a Namespace

Namespaces in Kubernetes help organize your resources. Let’s create one for SQL Server:

kubectl create namespace sqlserver

2. Persistent Storage Setup

SQL Server requires persistent storage for data. We’ll use Persistent Volume (PV) and Persistent Volume Claim (PVC).

Persistent Volume (PV) Definition:

apiVersion: v1
kind: PersistentVolume
metadata:
  name: sql-pv
  namespace: sqlserver
spec:
  capacity:
    storage: 20Gi
  accessModes:
    - ReadWriteOnce
  hostPath:
    path: /mnt/sqlserver

Persistent Volume Claim (PVC) Definition:

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: sql-pvc
  namespace: sqlserver
spec:
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 20Gi

Apply these configurations:

kubectl apply -f sql-pv.yaml
kubectl apply -f sql-pvc.yaml

3. Deploying SQL Server 2022

Create a Deployment manifest for SQL Server:

Deployment YAML:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: sqlserver-deployment
  namespace: sqlserver
spec:
  replicas: 1
  selector:
    matchLabels:
      app: sqlserver
  template:
    metadata:
      labels:
        app: sqlserver
    spec:
      containers:
      - name: sqlserver
        image: mcr.microsoft.com/mssql/server:2022-latest
        ports:
        - containerPort: 1433
        env:
        - name: ACCEPT_EULA
          value: "Y"
        - name: MSSQL_SA_PASSWORD
          value: "YourStrongPassword!"
        volumeMounts:
        - name: mssql-data
          mountPath: /var/opt/mssql
      volumes:
      - name: mssql-data
        persistentVolumeClaim:
          claimName: sql-pvc

Apply the deployment:

kubectl apply -f sqlserver-deployment.yaml

4. Exposing SQL Server

To access SQL Server externally, create a Service:

Service YAML:

apiVersion: v1
kind: Service
metadata:
  name: sqlserver-service
  namespace: sqlserver
spec:
  type: LoadBalancer
  ports:
  - port: 1433
    targetPort: 1433
  selector:
    app: sqlserver

Apply the service configuration:

kubectl apply -f sqlserver-service.yaml

🔍 Managing SQL Server on Kubernetes

1. Scaling

To scale SQL Server instances, modify the replicas field in the Deployment YAML:

spec:
  replicas: 3

Apply the changes:

kubectl apply -f sqlserver-deployment.yaml

2. Monitoring

Monitor the SQL Server pods and services using kubectl:

kubectl get pods -n sqlserver
kubectl get svc -n sqlserver

For detailed logs:

kubectl logs <pod-name> -n sqlserver

3. Updating SQL Server Image

To update the SQL Server container image, modify the image field in the Deployment YAML and apply the changes:

image: mcr.microsoft.com/mssql/server:2022-latest

kubectl apply -f sqlserver-deployment.yaml

4. Backup and Restore

Backup: Use the sqlcmd tool or any SQL Server Management tool to perform a backup.

Restore: Similarly, use sqlcmd or another tool to restore from a backup.

Example backup command:

BACKUP DATABASE [YourDatabase] TO DISK = '/var/opt/mssql/backup/YourDatabase.bak'

🏁 Conclusion

Deploying and managing SQL Server 2022 on Kubernetes provides flexibility and scalability for your containerized environments. By following the steps outlined in this guide, you can set up SQL Server, scale it, monitor performance, and perform backups and updates with ease.

Kubernetes and SQL Server 2022 together form a powerful combination for modern cloud-native applications. If you have any questions or run into issues, feel free to explore the official documentation or community forums. Happy deploying! 🚀