Analyze query execution with Query Explain

This page describes how to retrieve query execution information when you execute a query.

Use Query Explain

You can use Query Explain to understand how your queries are being executed. This provides details that you can use to optimize your queries .

You can use Query Explain through the Google Cloud console.

Console

Execute a query in the Query Editor and open the Explanation tab:

In the Google Cloud console, go to the Databases page.

Go to Databases
From the list of databases, select a Firestore database. The Google Cloud console opens the Firestore Explorer for that database.
Enter a query in the query editor and click Run .
Click the Explanation tab to view the query analysis output.

Analysis

The output of Query Explain contains two main components-the Summary Statistics and Execution Tree. Consider this query as an example:

 db.pipeline().collection('/users').sort(field("status").ascending()).limit(100)

Summary Statistics

The top of the explained output contains a summary of the execution statistics. Use these statistics to determine if a query has high latency or cost. It also contains memory statistics which let you know how close your query is to memory limits .

 Execution:
 results returned: 2
 request peak memory usage: 20.25 KiB (20,736 B)
 data bytes read: 148 B
 entity row scanned: 2

Billing:
 read units: 1

Execution Tree

The execution tree describes the query execution as a series of nodes. The bottom nodes (leaf nodes) retrieve data from the storage layer which traverses up the tree to generate a query response.

For details about each execution node, refer to the Execution reference .

For details on how to use this information to optimize your queries, see Optimize query execution .

The following is an example of an execution tree:

 Tree:
• Compute
|  $out_1: map_set($record_1, "__name__", $__name___1, "__key__", unset)
|  is query result: true
|
|  Execution:
|   records returned: 2
|   latency: 5.96 ms (local <1 ms)
|
└── • Compute
    |  $__name___1: map_get($record_1, "__key__")
    |
    |  Execution:
    |   records returned: 2
    |   latency: 5.88 ms (local <1 ms)
    |
    └── • MajorSort
        |  fields: [$v_1 ASC]
        |  output: [$record_1]
        |  limit: 100
        |
        |  Execution:
        |   records returned: 2
        |   latency: 5.86 ms (local <1 ms)
        |   peak memory usage: 20.25 KiB (20,736 B)
        |
        └── • Compute
            |  $v_1: map_get($record_1, "status")
            |
            |  Execution:
            |   records returned: 2
            |   latency: 5.23 ms (local <1 ms)
            |
            └── • TableScan
                   source: /users
                   order: UNDEFINED
                   properties: *
                   row range: (-∞..+∞)
                   output record: $record_1
                   variables: [$record_1]

                   Execution:
                    records returned: 2
                    latency: 4.68 ms
                    records scanned: 2
                    data bytes read: 148 B

What's next

To learn about the execution tree nodes, see the Query execution reference .
To learn how to optimize your queries, see Optimize query execution .