Documentation

Get started querying data

InfluxDB Cloud Serverless supports multiple query languages:

  • SQL: Traditional SQL powered by the Apache Arrow DataFusion query engine. The supported SQL syntax is similar to PostgreSQL.
  • InfluxQL: An SQL-like query language designed to query time series data stored in InfluxDB.

This tutorial walks you through the fundamentals of querying data in InfluxDB and focuses on using SQL to query your time series data. The InfluxDB SQL implementation is built using Arrow Flight SQL, a protocol for interacting with SQL databases using the Arrow in-memory format and the Flight RPC framework. It leverages the performance of Apache Arrow with the simplicity of SQL.

The examples in this section of the tutorial query the get-started bucket for data written in the Get started writing data section.

Tools to execute queries

InfluxDB Cloud Serverless supports many different tools for querying data, including:

* Covered in this tutorial

Avoid using /api/v2/query

Avoid using the /api/v2/query API endpoint and associated tooling, such as the influx query CLI command and InfluxDB v2 client libraries, with InfluxDB Cloud Serverless.

SQL query basics

The InfluxDB Cloud Serverless SQL implementation is powered by the Apache Arrow DataFusion query engine which provides an SQL syntax similar to PostgreSQL.

This is a brief introduction to writing SQL queries for InfluxDB. For more in-depth details, see Query data with SQL.

InfluxDB SQL queries most commonly include the following clauses:

* Required
  • * SELECT: Identify specific fields and tags to query from a measurement or use the wildcard alias (*) to select all fields and tags from a measurement.
  • * FROM: Identify the measurement to query. If coming from an SQL background, an InfluxDB measurement is the equivalent of a relational table.
  • WHERE: Only return data that meets defined conditions such as falling within a time range, containing specific tag values, etc.
  • GROUP BY: Group data into SQL partitions and apply an aggregate or selector function to each group.
-- Return the average temperature and humidity within time bounds from each room
SELECT
  avg(temp),
  avg(hum),
  room
FROM
  home
WHERE
  time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
GROUP BY
  room

Example SQL queries

Select all data in a measurement
SELECT * FROM home
Select all data in a measurement within time bounds
SELECT
  *
FROM
  home
WHERE
  time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
Select a specific field within relative time bounds
SELECT temp FROM home WHERE time >= now() - INTERVAL '1 day'
Select specific fields and tags from a measurement
SELECT temp, room FROM home
Select data based on tag value
SELECT * FROM home WHERE room = 'Kitchen'
Select data based on tag value within time bounds
SELECT
  *
FROM
  home
WHERE
  time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'
  AND room = 'Living Room'
Downsample data by applying interval-based aggregates
SELECT
  DATE_BIN(INTERVAL '1 hour', time, '2022-01-01T00:00:00Z'::TIMESTAMP) as _time,
  room,
  selector_max(temp, time)['value'] AS 'max temp'
FROM
  home
GROUP BY
  _time,
  'max temp',
  room
ORDER BY room, _time

Execute an SQL query

Get started with one of the following tools for querying data stored in an InfluxDB Cloud Serverless bucket:

  • InfluxDB UI: View your schema, build queries using the query editor, and generate data visualizations.
  • InfluxDB v3 client libraries: Use language-specific (Python, Go, etc.) clients to execute queries in your terminal or custom code.
  • influx3 data CLI: Send queries from your terminal command-line.
  • Grafana: Use the FlightSQL Data Source plugin, to query, connect, and visualize data.

Avoid using /api/v2/query

Avoid using the /api/v2/query API endpoint in InfluxDB Cloud Serverless and associated tooling, such as the influx query CLI command and InfluxDB v2 client libraries. You can’t use SQL or InfluxQL with these tools.

For this example, use the following query to select all the data written to the get-started bucket between 2022-01-01T08:00:00Z and 2022-01-01T20:00:00Z.

SELECT
  *
FROM
  home
WHERE
  time >= '2022-01-01T08:00:00Z'
  AND time <= '2022-01-01T20:00:00Z'

Some examples in this getting started tutorial assume your InfluxDB credentials (URL, organization, and token) are provided by environment variables.

  1. Go to cloud2.influxdata.com in a browser to log in and access the InfluxDB UI.

  2. In the side navigation menu, click Data Explorer.

  1. In the schema browser on the left, select the get-started bucket from the bucket drop-down menu. The displayed measurements and fields are read-only and are meant to show you the schema of data stored in the selected bucket.

  2. Enter the SQL query in the text editor.

  3. Click Run.

Results are displayed under the query editor.

See Query in the Data Explorer to learn more.

Query InfluxDB v3 using SQL and the influx3 CLI.

The following steps include setting up a Python virtual environment already covered in Get started writing data. If your project’s virtual environment is already running, skip to step 3.

  1. Create a directory for your project and change into it:

    mkdir influx3-query-example && cd $_
    
  2. To create and activate a Python virtual environment, run the following command:

    python -m venv envs/virtual-env && . envs/virtual-env/bin/activate
    
  3. Install the CLI package (already installed in the Write data section).

    pip install influxdb3-python-cli
    

    Installing influxdb3-python-cli also installs the pyarrow library for working with Arrow data returned from queries.

  4. Create the config.json configuration.

    influx3 config create \
      --name="config-serverless" \
      --database="get-started" \
      --host="cloud2.influxdata.com" \
      --token="API_TOKEN" \
      --org="ORG_ID"
    

    Replace the following:

  5. Enter the influx3 sql command and your SQL query statement.

    influx3 sql "SELECT *
                  FROM home
                  WHERE time >= '2022-01-01T08:00:00Z'
                  AND time <= '2022-01-01T20:00:00Z'"
    

    influx3 displays query results in your terminal.

Use the influxdb_client_3 client library module to integrate InfluxDB Cloud Serverless with your Python code. The client library supports writing data to InfluxDB and querying data using SQL or InfluxQL.

The following steps include setting up a Python virtual environment already covered in Get started writing data. If your project’s virtual environment is already running, skip to step 3.

  1. Open a terminal in the influxdb_py_client module directory you created in the Write data section:

    1. To create and activate your Python virtual environment, enter the following command in your terminal:

      python -m venv envs/virtual-env && . ./envs/virtual-env/bin/activate
      
    2. Install the following dependencies:

      * Already installed in the Write data section

      • influxdb3-python*: Provides the InfluxDB influxdb_client_3 Python client library module and also installs the pyarrow package for working with Arrow data returned from queries.
      • pandas: Provides pandas functions, modules, and data structures for analyzing and manipulating data.
      • tabulate: Provides the tabulate function for formatting tabular data. pandas requires this module for formatting data as Markdown.

      In your terminal, enter the following command:

      pip install influxdb3-python pandas tabulate
      
    3. In your terminal or editor, create a new file for your code–for example: query.py.

  2. In query.py, enter the following sample code:

    from influxdb_client_3 import InfluxDBClient3
    
    client = InfluxDBClient3(
        host=f"cloud2.influxdata.com",
        token=f"API_TOKEN",
        database=f"get-started")
    
    sql = '''
      SELECT
        *
      FROM
        home
      WHERE
        time >= '2022-01-01T08:00:00Z'
        AND time <= '2022-01-01T20:00:00Z'
    '''
    
    table = client.query(query=sql)
    assert table['room'], "Expect table to have room column."
    print(table.to_pandas().to_markdown())
    

Important: If using Windows, specify the Windows certificate path

The sample code does the following:

  1. Imports the InfluxDBClient3 constructor from the influxdb_client_3 module.

  2. Calls the InfluxDBClient3() constructor method with credentials to instantiate an InfluxDB client with the following credentials:

    • host: InfluxDB Cloud Serverless region hostname (URL without protocol or trailing slash)
    • database: the name of the InfluxDB Cloud Serverless bucket to query
    • token: an API token with read access to the specified bucket. Store this in a secret store or environment variable to avoid exposing the raw token string.
  3. Defines the SQL query to execute and assigns it to a query variable.

  4. Calls the client.query() method with the SQL query. query() sends a Flight request to InfluxDB, queries the database (bucket), retrieves result data from the endpoint, and then returns a pyarrow.Table assigned to the table variable.

  5. Calls the to_pandas() method to convert the Arrow table to a pandas.DataFrame.

  6. Calls the pandas.DataFrame.to_markdown() method to convert the DataFrame to a markdown table.

  7. Calls the print() method to print the markdown table to stdout.

  8. In your terminal, enter the following command to run the program and query InfluxDB Cloud Serverless:

    python query.py
    

View returned markdown table

  1. In the influxdb_go_client directory you created in the Write data section, create a new file named query.go.

  2. In query.go, enter the following sample code:

    package main
    
    import (
      "context"
      "fmt"
      "io"
      "os"
      "time"
      "text/tabwriter"
    
      "github.com/apache/arrow/go/v13/arrow"
      "github.com/InfluxCommunity/influxdb3-go/influxdb3"
    )
    
    func Query() error {
    
       // INFLUX_TOKEN is an environment variable you created
       // for your API read token.
      token := os.Getenv("INFLUX_TOKEN")
    
      // Instantiate the client.
      client, err := influxdb3.New(influxdb3.ClientConfig{
        Host:     "https://cloud2.influxdata.com",
        Token:    token,
        Database: "get-started",
      })
    
      // Close the client when the function returns.
      defer func(client *influxdb3.Client) {
        err := client.Close()
        if err != nil {
          panic(err)
        }
      }(client)
    
      // Define the query.
      query := `SELECT *
        FROM home
        WHERE time >= '2022-01-01T08:00:00Z'
        AND time <= '2022-01-01T20:00:00Z'`
    
      // Execute the query.
      iterator, err := client.Query(context.Background(), query)
    
      if err != nil {
        panic(err)
      }
    
      w := tabwriter.NewWriter(io.Discard, 4, 4, 1, ' ', 0)
      w.Init(os.Stdout, 0, 8, 0, '\t', 0)
      fmt.Fprintln(w, "time\troom\ttemp\thum\tco")
    
      // Iterate over rows and prints column values in table format.
      for iterator.Next() {
        row := iterator.Value()
        // Use Go arrow and time packages to format unix timestamp
        // as a time with timezone layout (RFC3339).
        time := (row["time"].(arrow.Timestamp)).
          ToTime(arrow.TimeUnit(arrow.Nanosecond)).
          Format(time.RFC3339)
        fmt.Fprintf(w, "%s\t%s\t%d\t%.1f\t%.1f\n",
          time, row["room"], row["co"], row["hum"], row["temp"])
      }
    
      w.Flush()
      return nil
    }
    

    The sample code does the following:

    1. Imports the following packages:

      • context
      • fmt
      • io
      • os
      • text/tabwriter
      • github.com/apache/arrow/go/v13/arrow
      • github.com/InfluxCommunity/influxdb3-go/influxdb3
    2. Defines a Query() function that does the following:

      1. Instantiates influx.Client with InfluxDB credentials.

        • Host: your InfluxDB Cloud Serverless region URL
        • Database: The name of your InfluxDB Cloud Serverless bucket
        • Token: an API token with read permission on the specified bucket. Store this in a secret store or environment variable to avoid exposing the raw token string.
      2. Defines a deferred function to close the client after execution.

      3. Defines a string variable for the SQL query.

      4. Calls the influxdb3.Client.Query(sql string) method and passes the SQL string to query InfluxDB. Query(sql string) method returns an iterator for data in the response stream.

      5. Iterates over rows, formats the timestamp as an RFC3339 timestamp, and prints the data in table format to stdout.

  3. In your editor, open the main.go file you created in the Write data section and insert code to call the Query() function–for example:

    package main
    
    func main() {	
      WriteLineProtocol()
      Query()
    }
    
  4. In your terminal, enter the following command to install the necessary packages, build the module, and run the program:

    go mod tidy && go build && go run influxdb_go_client
    

    The program executes the main() function that writes the data and prints the query results to the console.

This tutorial assumes you installed Node.js and npm, and created an influxdb_js_client npm project as described in the Write data section.

  1. In your terminal or editor, change to the influxdb_js_client directory you created in the Write data section.

  2. If you haven’t already, install the @influxdata/influxdb3-client JavaScript client library as a dependency to your project:

    npm install --save @influxdata/influxdb3-client
    
  3. Create a file named query.mjs. The .mjs extension tells the Node.js interpreter that you’re using ES6 module syntax.

  4. Inside of query.mjs, enter the following sample code:

    // query.mjs
    import {InfluxDBClient} from '@influxdata/influxdb3-client'
    import {tableFromArrays} from 'apache-arrow';
    
    /**
    * Set InfluxDB credentials.
    */
    const host = "https://cloud2.influxdata.com";
    const database = 'get-started';
    /**
    * INFLUX_TOKEN is an environment variable you assigned to your
    * API READ token value.
    */
    const token = process.env.INFLUX_TOKEN;
    
    /**
    * Query InfluxDB with SQL using the JavaScript client library.
    */
    export async function querySQL() {
      /**
      * Instantiate an InfluxDBClient
      */
      const client = new InfluxDBClient({host, token})
      const sql = `
      SELECT *
      FROM home
      WHERE time >= '2022-01-01T08:00:00Z'
        AND time <= '2022-01-01T20:00:00Z'
      `
    
      const data = {time: [], room: [], co: [], hum: [], temp: []};
      const result = client.query(query, database);
    
      for await (const row of result) {
        data.time.push(new Date(row._time))
        data.room.push(row.room)
        data.co.push(row.co);
        data.hum.push(row.hum);
        data.temp.push(row.temp);
      }
    
      console.table([...tableFromArrays(data)])
    
      client.close()
    }
    

    The sample code does the following:

    1. Imports the following:

      • InfluxDBClient class
      • tableFromArrays function
    2. Calls new InfluxDBClient() and passes a ClientOptions object to instantiate a client configured with InfluxDB credentials.

      • host: your InfluxDB Cloud Serverless region URL
      • token: an API token with read access to the specified bucket. Store this in a secret store or environment variable to avoid exposing the raw token string.
    3. Defines a string variable (sql) for the SQL query.

    4. Defines an object (data) with column names for keys and array values for storing row data.

    5. Calls the InfluxDBClient.query() method with the following arguments:

      • sql: the query to execute
      • database: the name of the InfluxDB Cloud Serverless bucket to query

      query() returns a stream of row vectors.

    6. Iterates over rows and adds the column data to the arrays in data.

    7. Passes data to the Arrow tableFromArrays() function to format the arrays as a table, and then passes the result to the console.table() method to output a highlighted table in the terminal.

  5. Inside of index.mjs (created in the Write data section), enter the following sample code to import the modules and call the functions:

    // index.mjs
    import { writeLineProtocol } from "./write.mjs";
    import { querySQL } from "./query.mjs";
    
    /**
    * Execute the client functions.
    */
    async function main() {
      /** Write line protocol data to InfluxDB. */
      await writeLineProtocol();
      /** Query data from InfluxDB using SQL. */
      await querySQL();
    }
    
    main();
    
  6. In your terminal, execute index.mjs to write to and query InfluxDB Cloud Serverless:

    node index.mjs
    
  1. In the influxdb_csharp_client directory you created in the Write data section, create a new file named Query.cs.

  2. In Query.cs, enter the following sample code:

    // Query.cs
    
    using System;
    using System.Threading.Tasks;
    using InfluxDB3.Client;
    using InfluxDB3.Client.Query;
    
    namespace InfluxDBv3;
    
    public class Query
    {
      /**
        * Queries an InfluxDB database (bucket) using the C# .NET client
        * library.
        **/
      public static async Task QuerySQL()
      {
        /** INFLUX_TOKEN is an environment variable you assigned to your
          * API READ token value.
          **/
        string? token = System.Environment
            .GetEnvironmentVariable("INFLUX_TOKEN");
    
        /**
          * Instantiate the InfluxDB client with credentials.
          **/
        using var client = new InfluxDBClient(
            "https://cloud2.influxdata.com", token: token, database: database);
    
        const string sql = @"
          SELECT time, room, temp, hum, co
          FROM home
          WHERE time >= '2022-01-01T08:00:00Z'
          AND time <= '2022-01-01T20:00:00Z'
        ";
    
        Console.WriteLine("{0,-30}{1,-15}{2,-15}{3,-15}{4,-15}",
            "time", "room", "co", "hum", "temp");
    
        await foreach (var row in client.Query(query: sql))
        {
          {
            /** 
              * Iterate over rows and print column values in table format.
              * Format the timestamp as sortable UTC format.
              */
            Console.WriteLine("{0,-30:u}{1,-15}{4,-15}{3,-15}{2,-15}",
                row[0], row[1], row[2], row[3], row[4]);
          }
        }
        Console.WriteLine();
      }
    }
    

    The sample code does the following:

    1. Imports the following classes:

      • System
      • System.Threading.Tasks;
      • InfluxDB3.Client;
      • InfluxDB3.Client.Query;
    2. Defines a Query class with a QuerySQL() method that does the following:

      1. Calls the new InfluxDBClient() constructor to instantiate a client configured with InfluxDB credentials.

        • host: your InfluxDB Cloud Serverless region URL.
        • token: an API token with read permission on the specified bucket. Store this in a secret store or environment variable to avoid exposing the raw token string.
        • database: the name of the InfluxDB Cloud Serverless bucket to query
      2. Defines a string variable for the SQL query.

      3. Calls the InfluxDBClient.Query() method to send the query request with the SQL string. Query() returns batches of rows from the response stream as a two-dimensional array–an array of rows in which each row is an array of values.

      4. Iterates over rows and prints the data in table format to stdout.

  3. In your editor, open the Program.cs file you created in the Write data section and insert code to call the Query() function–for example:

    // Program.cs
    
    using System;
    using System.Threading.Tasks;
    
    namespace InfluxDBv3;
    
    public class Program
    {
      public static async Task Main()
      {
        await Write.WriteLineProtocol();
        await Query.QuerySQL();
      }
    }
    
  4. To build and execute the program and query InfluxDB Cloud Serverless, enter the following commands in your terminal:

    dotnet run
    

This tutorial assumes using Maven version 3.9, Java version >= 15, and an influxdb_java_client Maven project created in the Write data section.

  1. In your terminal or editor, change to the influxdb_java_client directory you created in the Write data section.

  2. Inside of the src/main/java/com/influxdbv3 directory, create a new file named Query.java.

  3. In Query.java, enter the following sample code:

    // Query.java
    package com.influxdbv3;
    
    import com.influxdb.v3.client.InfluxDBClient;
    import java.util.stream.Stream;
    
    /**
      * Queries an InfluxDB database (bucket) using the Java client
      * library.
      **/
    public final class Query {
    
        private Query() {
            //not called
        }
    
        /**
        * @throws Exception
        */
        public static void querySQL() throws Exception {
            /**
            * Query using SQL.
            */
    
            /** Set InfluxDB credentials. **/
            final String host = "https://cloud2.influxdata.com";
            final String database = "get-started";
    
            /** INFLUX_TOKEN is an environment variable you assigned to your
              * API READ token value.
              **/
            final char[] token = (System.getenv("INFLUX_TOKEN")).
            toCharArray();
    
            try (InfluxDBClient client = InfluxDBClient.getInstance(host,
            token, database)) {
                String sql =
                    """
                    SELECT time, room, temp, hum, co
                    FROM home
                    WHERE time >= '2022-01-01T08:00:00Z'
                    AND time <= '2022-01-01T20:00:00Z'""";
    
                String layoutHead = "| %-16s | %-12s | %-6s | %-6s | %-6s |%n";
                System.out.printf(
                "--------------------------------------------------------%n");
                System.out.printf(layoutHead,
                "time", "room", "co", "hum", "temp");
                System.out.printf(
                "--------------------------------------------------------%n");
                String layout = "| %-16s | %-12s | %-6s | %.1f | %.1f |%n";
    
                try (Stream<Object[]> stream = client.query(sql)) {
                    stream.forEach(row -> 
                      System.out.printf(layout,
                      row[0], row[1], row[4], row[3], row[2])
                    );
                }
            }
        }
    }
    

    The sample code does the following:

    1. Assigns the com.influxdbv3 package name (the Maven groupId).

    2. Imports the following classes:

      • com.influxdb.v3.client.InfluxDBClient
      • java.util.stream.Stream
    3. Defines a Query class with a querySQL() method that does the following:

      1. Calls InfluxDBClient.getInstance() to instantiate a client configured with InfluxDB credentials.

        • host: your InfluxDB Cloud Serverless region URL
        • database: the name of the InfluxDB Cloud Serverless bucket to write to
        • token: an API token with read access to the specified bucket. Store this in a secret store or environment variable to avoid exposing the raw token string.
      2. Defines a string variable (sql) for the SQL query.

      3. Defines a Markdown table format layout for headings and data rows.

      4. Calls the InfluxDBClient.query() method to send the query request with the SQL string. query() returns a stream of rows.

      5. Iterates over rows and prints the data in the specified layout to stdout.

  4. In your editor, open the src/main/java/com/influxdbv3/App.java file and replace its contents with the following sample code:

    // App.java
    
    package com.influxdbv3;
    
    /**
    * Execute the client functions.
    *
    */
    public class App {
    
        /**
        * @param args
        * @throws Exception
        */
        public static void main(final String[] args) throws Exception {
            // Write data to InfluxDB v3.
            Write.writeLineProtocol();
            // Run the SQL query.
            Query.querySQL();
        }
    }
    
    • The App, Write, and Query classes belong to the com.influxdbv3 package (your project groupId).
    • App defines a main() function that calls Write.writeLineProtocol() and Query.querySQL().
  5. In your terminal or editor, use Maven to to install dependencies and compile the project code–for example:

    mvn compile
    
  6. Set the --add-opens=java.base/java.nio=ALL-UNNAMED Java option for your environment. The Apache Arrow Flight library requires this setting for access to the java.nio API package.

    For example, enter the following command in your terminal:

    Linux/MacOS

    export MAVEN_OPTS="--add-opens=java.base/java.nio=ALL-UNNAMED"
    

    Windows PowerShell

    $env:MAVEN_OPTS="--add-opens=java.base/java.nio=ALL-UNNAMED"
    
  7. To run the app to write to and query InfluxDB Cloud Serverless, execute App.main()–for example, using Maven:

    mvn exec:java -Dexec.mainClass="com.influxdbv3.App"
    

Query results

View query results

Congratulations! You’ve learned the basics of querying data in InfluxDB with SQL. For a deep dive into all the ways you can query InfluxDB Cloud Serverless, see the Query data in InfluxDB section of documentation.


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Introducing InfluxDB Clustered

A highly available InfluxDB 3.0 cluster on your own infrastructure.

InfluxDB Clustered is a highly available InfluxDB 3.0 cluster built for high write and query workloads on your own infrastructure.

InfluxDB Clustered is currently in limited availability and is only available to a limited group of InfluxData customers. If interested in being part of the limited access group, please contact the InfluxData Sales team.

Learn more
Contact InfluxData Sales

The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following:

InfluxDB Cloud Serverless