Slow Query Log Analyzer

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Optimize these views for optimal performance ...

The following views are used in this query. Optimizing the internals of the views is crucial for this query's optimal performance. Click on the view names to optimize them.

The optimal indexes for this query are ...

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By default, the database cannot use indexes on columns used as function parameters, e.g. MONTH(date) = 5.
You can index the these statements by creating and indexing virtual columns:

Please create these indexes before executing the optimized query:

I use ORM and I can't modify my query (retrieve optimal indexes based on the original query).

Generate another alternative with Covering Indexes (larger, but can be faster)

The following indexes already exist in your database and were found as useful for optimal query performance:

Can't create the suggested temporary tables below? Click here to avoid them.

If the relationship between the tables isn't 1:1, the output from this optimized query may not match the original query's output. If that's the case, click here to retrieve another alternative.

The new optimized query is ...

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Trusted by more than 100,000 engineers, including:

Advanced capabilities for Plus and Enterprise customers

Our advanced capabilities and insights are available for Plus and Enterprise subscribers.
Please consider upgrading to unlock these advanced capabilities.

Trusted by more than 100,000 engineers, including:

Advanced capabilities for Enterprise customers

360° indexing insights are available for Enterprise subscribers.
Please consider upgrading to unlock this advanced capability.

Trusted by more than 100,000 engineers, including:

Optimizing a SQL query

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* Current active database is: .

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Query Performance Trend

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Resubmit a query for optimization

Please adjust the query's syntax and re-submit it for optimization:

Redundant indexes report

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Installing EverSQL Performance Sensor

EverSQL performance sensor will track your databases slow query logs on an on-going basis and generate personalized optimization insights for you automatically. You can use the performance sensor with MySQL, MariaDB and Percona databases.

Step 1: Enable the slow query log

The performance sensor requires slow query logs to be enabled.
Click here for instructions if you don't have them enabled.

To enable slow query logs, please add the following parameters to MySQL's configuration file. By default, the configuration file is at /etc/my.cnf, or at /etc/mysql/my.cnf.

[mysqld]
slow_query_log=1
long_query_time=1 # Logs queries longer than 1 second
log_output=FILE
slow_query_log_file=/var/lib/mysql/slow.log

To apply the changes, please restart the database (requires short downtime):

sudo /etc/init.d/mysql restart

Step 2: Install the performance sensor

To install the performance sensor, please run the following commands.
If your slow query log file is not at /var/lib/mysql/slow.log, please modify the path below.

curl https://www.eversql.com/install/ubuntu_18_04 > install_sensor
sudo bash -x install_sensor /var/lib/mysql/slow.log

Once installed, the sensor will start collecting slow queries within up to 30 minutes.

EverSQL performance sensor will track your databases slow query logs on an on-going basis and generate personalized optimization insights for you automatically. You can find more information here.
You can use the performance sensor with Amazon RDS MySQL / RDS MariaDB / Aurora MySQL databases.

Step 1: Enable the slow query log

To enable slow query logs on your database instances, please follow the 'Enable slow query log' section here.

Once you're done editing the parameter group and assigning it to your instance, please make sure you restart the database to apply the changes (may require downtime).

Step 2: Install the performance sensor

You can now deploy the performance sensor from the Amazon Serverless Application repository.
Your personal API key (required as part of the installation):

Once installed, the sensor will start collecting slow queries within up to 30 minutes.

EverSQL performance sensor will track your databases slow query logs on an on-going basis and generate personalized optimization insights for you automatically.
You can use the performance sensor with Cloud SQL MySQL / Cloud SQL PostgreSQL databases.

Step 1: Enable the slow query log

To enable slow query logs on your Cloud SQL instances and redirect them to a Cloud Storage Bucket, please follow the instructions here.

Once you're done editing the parameter group and assigning it to your instance, please make sure you restart the database to apply the changes (may require downtime).

Step 2: Install the performance sensor

To install the performance sensor, please run the following commands in your GCloud CLI.
Please make sure to configure the following in the commands before executing them:
* GCP_FUNCTION_NAME: Name the sensor (alphanumeric and dashes allowed).
* GCP_REGION: The region where your Cloud SQL instance is located (example: us-central1).
* GCP_PROJECT_ID: Your GCP project ID.
* GCP_BUCKET_NAME: The name of the bucket you created in step #1 above.
* SERVER_NAME: The name of this instance as will be shown on EverSQL.

curl -sSL -o eversql_gcp_sensor_installation.zip https://www.eversql.com/install/eversql_gcp_sensor_installation.zip
unzip eversql_gcp_sensor_installation.zip -d eversql_gcp_sensor_installation/ gcloud functions deploy GCP_FUNCTION_NAME --project=GCP_PROJECT_ID --region=GCP_REGION --trigger-resource=GCP_BUCKET_NAME --set-env-vars="server_name=SERVER_NAME,api_key=" --runtime=python39 --memory=1024MB --timeout=600s --entry-point=main_func --source=eversql_gcp_sensor_installation --trigger-event=google.storage.object.finalize

Once installed, the sensor will start collecting slow queries within up to 30 minutes.

Visualize & optimize queries from slow query logs

EverSQL Slow Log Analyzer will analyze your MySQL and PostgreSQL slow query log files and visualize them in a timeline, to allow you to quickly locate the queries to optimize.

Which server did this log file originated from?

Please submit a MySQL or PostgreSQL slow query log (How?):

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