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Query Insights

Find and optimize long-running queries in your application, anomalies in your database, and more.

Overview

PlanetScale Insights gives you a detailed look into all active queries running against your database. This in-dashboard tool allows you to identify queries that are running too often, too long, returning too much data, producing errors, and more. You can scroll through the performance graph to detect the time that a query was impacted and, if applicable, the Deploy Request that affected it.

You can also see a list of all queries performed on your database in the last 24 hours. For further analysis, you can sort these by metrics like amount of rows read, time per query, and more.

With this built-in tool, you can easily diagnose issues with your queries, allowing you to optimize individual queries without much digging. We will also alert you of any active issues your database may be having in the Anomalies tab. This feature flags queries that are running significantly slower than expected.

Insights will also automatically recommend schema changes to improve database performance, reduce memory and storage, and improve your schema based on production database traffic. Read more about the supported recommendations and how to use them in the schema recommendations documentation.

Insights page overview

To view Insights for your database, head to the PlanetScale dashboard, select your database, and click the "Insights" tab.

Note

If you are a single-tenant or PlanetScale Managed customer, you will need to request access to Insights through your PlanetScale account manager.

The dropdown on the top right lets you select which branch you want to analyze. You can also choose which servers you want to view insights for: primary or replicas.

You can click the dates listed above the graph to scroll through the past seven days. To further narrow down query analysis, you can select a time range by clicking on the graph and dragging the cursor across. This will zoom in on the selected timeframe.

Note

On the free Hobby plan, query insights are limited to the previous 24 hours. To unlock the full seven days of analytics, upgrade to a paid plan.

You also have the option to save a screenshot of the graph by clicking "Save".

If any deploy requests were deployed during the selected period, you will also see an overlay with a link to the deploy request. This can help you quickly assess any impact a deploy request had on your database.

Queries overview table

The table underneath the graph shows all queries performed on your database in the selected timeframe (last 24 hours by default).

For more information about how to read and interpret this data, see the Queries overview section.

Insights graph tabs

Once you have selected the branch and server you want to analyze, you can begin exploring the insights for them in the following tabs:

The remaining sections of this doc walk through how to interpret and act on the data in each tab. If you'd like to see a practical example of how to use Insights to debug a performance issue, check out our Announcing Insights blog post or this YouTube video walking you through an example.

Query latency

The default tab depicts your database's query latency in milliseconds over the last 24 hours.

By default, the graph contains two line charts showing p50 and p95 latency. This means 50% and 95% of requests, respectively, completed faster than the time listed. You can also click on the p99 and p99.9 pills to toggle those on, or click p50 or p95 to toggle those off.

Queries

The Queries tab displays insights about all active running queries in your database. The graph displays total queries per second against the specified time period.

Rows read

The Rows read tab displays the total number of rows read per second across the selected time period.

Rows written

The Rows written tab displays the total number of rows written per second across the selected time period.

Errors

The Errors tab surfaces any errors that have been captured on your database in a 24 hour period.

Underneath the graph, you'll find a list of database error messages that have been captured over the selected period.

You can click on any of the error messages on the Errors tab to open a more detailed view. This view shows you the individual queries that produced the error, when they ran, how long they ran, and any query tags attached to them.

Queries overview

The table underneath the graph shows all queries performed on your database in the selected timeframe (last 24 hours by default).

You may see some placeholder values in the queries, such as :v1. This is because we consider the actual data private and normalize it away.

Note

You have the option to opt in to complete query collection to see the full SQL statements.

You may also see a red shards icon next to some queries. This signifies that the query requires execution across multiple shards.

This query overviews table shows the same data for all graph tabs except for Anomalies and Errors. For more information about the content for each of those, refer to each Anomalies and Errors sections above.

Available query statistics

You can customize the metrics that show up on the Queries list by clicking the "Columns" dropdown.

  • Keyspace — The keyspace(s) being queried or modified.
  • Table — The table(s) being queried or modified.
  • Count — The number of times this query has run.
  • Total time (ms) — The total time the query has run in milliseconds.
  • p50 latency — The p50 latency for the query in milliseconds. This means that 50% of requests completed faster than the time listed.
  • p99 latency — The p99 latency for the query in milliseconds. This means that 99% of requests completed faster than the time listed.
  • Rows returned — The total number of rows fetched by a SELECT statement. This includes all times the query has run in the displayed time frame.
  • Rows read — The total number of rows read. This includes all times the query has run in the displayed time frame. This is the number that directly affects your rows read billing calculation.
  • Rows read/rows returned — The result of dividing total rows read by rows returned in a query. A high number can indicate that your database is reading unnecessary rows, and they query may be improved by adding an index.
  • Rows affected — The total number of rows modified by an INSERT, UPDATE, or DELETE statement. This includes all times the query has run in the displayed time frame.
  • Last run — The last time a query was run.

You can also sort the columns for quick analysis by clicking on the title at the top of each column.

Query filtering

The search bar above the table allows you to filter queries as needed. You can filter for table name, tag name, tag value, user name, exact string match, query count, multisharded queries, and Boosted queries. Click on the ? next to the search bar for the full list of search syntax.

Query deep dive

Clicking on a query in the Queries list will open a new page with more information about that query.

You'll first see the full query pattern, which displays the query with data normalized away. This query may run several times with different values, which Insights combines into a single query pattern.

You can also toggle on the query EXPLAIN plan by clicking "Show explain plan", which generates the execution plan for the selected query. You may have to fill in some sample values designated with placeholders like :v1. We use placeholders in the patterns both so you can look at whole patterns at once and so the literal values remain private.

Note, if you're viewing the EXPLAIN plan on a production branch, this button will be disabled unless you enable production web console access in your database Settings page.

If you'd like to further interact with the query, click "Open query in web console", and you'll be taken to your in-dashboard web console, where you can run the EXPLAIN plan.

Additional query information

Beneath the query pattern is a graph with more information about the query. The set of available metrics/tabs is the same as the main database-level metrics graphs: Query latency, Queries, Rows read, Rows written, and Errors.

Notable queries

Underneath the graph, you'll see a table with more information about notable instances of the query, which are defined as queries that took longer than 1s, read more than 10,000 rows, or produced an error.

If any of the selected queries have SQL comment tags attached, you'll see the key-value pairs in the table under Tags.

Note

If you're sending queries with comments using the MySQL shell, make sure you have enabled comments with the -c flag.

The table also surfaces when the query started, rows returned, rows read, rows affected, the time it took the query to run (in ms), and the user associated with the query.

Complete query collection

If you would prefer to view the raw query data using Insights, you can enable this option in your database settings page. In the dashboard, select your database, click "Settings", scroll down until you see "Complete query collection", and click "Enable" to opt in.

With this enabled, Insights will gather the complete raw SQL statements and display them when a query deep dive is selected and in the EXPLAIN plan. For example, if you select a query from the table on the Insights page, the query pattern and the selected queries below it will display the full query.

Enabling complete query collection is beneficial when performance varies significantly within the same query pattern, and you need to see the full SQL statement, without placeholders, to identify the correct source of the performance issue.

However, full queries may contain personally identifiable information, so it's important to consider this before opting in to the feature. Because of this, only Organization Administrators can choose to opt a database into complete query collection. Please read our Privacy Policy for more information on how we collect, process, and disclose your personally identifiable information.

Need help?

Get help from the PlanetScale support team, or join our GitHub discussion board to see how others are using PlanetScale.

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