Dedicated influxql (#4976)
* Restructure Dedicated query docs (#4967) * restructure dedicated query docs for influxql, add execute influxql doc * updated code examples * Update content/influxdb/cloud-dedicated/query-data/influxql/execute-queries/influxdb-v1-api.md --------- Co-authored-by: Jason Stirnaman <stirnamanj@gmail.com> * added code-placeholder-key shortcoded, updated code placholder styles * add note about authing with user/pass * updated basic auth credential list * Dedicated InfluxQL Python instructions (#4972) * add python influxql instructions, update python sql instructions * Apply suggestions from code review Co-authored-by: Jason Stirnaman <stirnamanj@gmail.com> --------- Co-authored-by: Jason Stirnaman <stirnamanj@gmail.com> --------- Co-authored-by: Jason Stirnaman <stirnamanj@gmail.com>pull/4975/head^2
Scott Anderson
GitHub
parent
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@import "code-api-methods";
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}
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// Styles for calling out specific code in code blocks
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////////////// Styles for calling out specific code in code blocks /////////////
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///
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span.code-callout, .code-placeholder {
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font-weight:bold;
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margin:0 .15rem;
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&.orange {color: $r-curacao;}
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}
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/////////////// Styles for code placeholders that can be updated ///////////////
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padding: 0;
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color: $code-placeholder;
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font-weight: normal;
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font-style: normal;
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transition: color .2s;
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cursor: pointer;
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font-style: normal;
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margin-left: .2rem;
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background-color: $sidebar-search-bg;
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padding: 2px 20px 2px 6px;
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color: $code-placeholder-hover;
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font-weight: bold;
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font-weight: normal;
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}
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.code-placeholder-key code {color: $code-placeholder}
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////////////////////////////////////////////////////////////////////////////////
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@ -217,7 +217,7 @@ $diagram-arrow: $g6-smoke;
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$flux-water-process-img: url('/img/flux/0-x-water-process-dark.svg');
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// Code placeholder colors
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$code-placeholder: #d43587;
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$code-placeholder: #e659a2;
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$code-placeholder-hover: $br-teal;
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@import "dark/telegraf",
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@ -1,15 +0,0 @@
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---
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title: Execute queries
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seotitle: Execute queries for data stored in an InfluxDB database
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description: Use tools and libraries to query data stored in an InfluxDB database.
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weight: 103
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menu:
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influxdb_cloud_dedicated:
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name: Execute queries
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parent: Query data
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influxdb/cloud-dedicated/tags: [query]
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---
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There are multiple ways to execute queries with InfluxDB. Choose from the following options:
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{{< children >}}
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@ -1,24 +0,0 @@
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---
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title: Query with Flight SQL
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seotitle: Query InfluxDB with Arrow Flight SQL
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description: >
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Query your data using Apache Arrow Flight SQL protocol and clients.
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weight: 201
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menu:
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influxdb_cloud_dedicated:
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name: Query with Flight SQL
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parent: Execute queries
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influxdb/cloud-dedicated/tags: [query, flightsql]
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---
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Use [Apache Arrow Flight SQL](https://arrow.apache.org/) to query data
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stored in an InfluxDB database.
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> Arrow Flight SQL is a protocol for interacting with SQL databases using the [Arrow in-memory format](https://arrow.apache.org/docs/format/Columnar.html) and the [Flight RPC](https://arrow.apache.org/docs/format/Flight.html) framework.
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>
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> {{% caption %}}[Apache Arrow Flight SQL documentation](https://arrow.apache.org/docs/format/FlightSql.html){{% /caption %}}
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Data platforms and clients that support the Flight SQL protocol can query data stored in an InfluxDB database.
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Learn how to connect to InfluxDB and query your data using the following tools:
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{{< children >}}
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@ -1,302 +0,0 @@
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---
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title: Use Python and the Flight SQL library to query data
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description: >
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Use Python and the `flightsql-dbapi` Flight SQL library to query data
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stored in InfluxDB.
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weight: 101
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menu:
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influxdb_cloud_dedicated:
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parent: Query with Flight SQL
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name: Use Python
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identifier: query_with_python
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influxdb/cloud-dedicated/tags: [query, flightsql, python]
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related:
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- /influxdb/cloud-dedicated/query-data/tools/pandas/
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- /influxdb/cloud-dedicated/query-data/tools/pyarrow/
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- /influxdb/cloud-dedicated/query-data/sql/
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list_code_example: |
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```py
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from flightsql import FlightSQLClient
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client = FlightSQLClient(host='cluster-id.influxdb.io',
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token='INFLUX_READ_WRITE_TOKEN',
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metadata={'database': 'INFLUX_DATABASE'},
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features={'metadata-reflection': 'true'})
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info = client.execute("SELECT * FROM home")
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ticket = info.endpoints[0].ticket
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reader = client.do_get(ticket)
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```
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---
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Use Python and the Flight SQL library to query data stored in InfluxDB.
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- [Get started using Python to query InfluxDB](#get-started-using-python-to-query-influxdb)
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- [Create a Python virtual environment](#create-a-python-virtual-environment)
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- [Install Python](#install-python)
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- [Create a project virtual environment](#venv-install)
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- [Install Anaconda](#conda-install)
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- [Query InfluxDB using Flight SQL](#query-influxdb-using-flight-sql)
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- [Install the Flight SQL Python Library](#install-the-flight-sql-python-library)
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- [Create a query client](#create-a-query-client)
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- [Execute a query](#execute-a-query)
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- [Retrieve data for Flight SQL query results](#retrieve-data-for-flight-sql-query-results)
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## Get started using Python to query InfluxDB
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This guide follows the recommended practice of using Python _virtual environments_.
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If you don't want to use virtual environments and you have Python installed,
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continue to [Query InfluxDB using Flight SQL](#query-influxdb-using-flight-sql).
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## Create a Python virtual environment
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Python [virtual environments](https://docs.python.org/3/library/venv.html) keep
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the Python interpreter and dependencies for your project self-contained and isolated from other projects.
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To install Python and create a virtual environment, choose one of the following options:
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- [Python venv](?t=venv#venv-install): The [`venv` module](https://docs.python.org/3/library/venv.html) comes standard in Python as of version 3.5.
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- [Anaconda® Distribution](?t=Anaconda#conda-install): A Python/R data science distribution that provides Python and the **conda** package and environment manager.
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{{< tabs-wrapper >}}
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{{% tabs "small" %}}
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[venv]()
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[Anaconda]()
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{{% /tabs %}}
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{{% tab-content %}}
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<!--------------------------------- Begin venv -------------------------------->
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### Install Python
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1. Follow the [Python installation instructions](https://wiki.python.org/moin/BeginnersGuide/Download)
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to install a recent version of the Python programming language for your system.
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2. Check that you can run `python` and `pip` commands.
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`pip` is a package manager included in most Python distributions.
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In your terminal, enter the following commands:
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```sh
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python --version
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```
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```sh
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pip --version
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```
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Depending on your system, you may need to use version-specific commands--for example.
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```sh
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python3 --version
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```
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```sh
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pip3 --version
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```
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If neither `pip` nor `pip<PYTHON_VERSION>` works, follow one of the [Pypa.io Pip installation](https://pip.pypa.io/en/stable/installation/) methods for your system.
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### Create a project virtual environment {#venv-install}
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1. Create a directory for your Python project and change to the new directory--for example:
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```sh
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mkdir ./PROJECT_DIRECTORY && cd $_
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```
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2. Use the Python `venv` module to create a virtual environment--for example:
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```sh
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python -m venv envs/virtualenv-1
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```
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`venv` creates the new virtual environment directory in your project.
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3. To activate the new virtual environment in your terminal, run the `source` command and pass the file path of the virtual environment `activate` script:
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```sh
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source envs/VIRTUAL_ENVIRONMENT_NAME/bin/activate
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```
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For example:
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```sh
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source envs/virtualenv-1/bin/activate
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```
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<!---------------------------------- End venv --------------------------------->
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{{% /tab-content %}}
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{{% tab-content %}}
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<!-------------------------------- Begin conda -------------------------------->
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### Install Anaconda {#conda-install}
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1. Follow the [Anaconda installation instructions](https://docs.continuum.io/anaconda/install/) for your system.
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2. Check that you can run the `conda` command:
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```sh
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conda
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```
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3. Use `conda` to create a virtual environment--for example:
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```sh
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conda create --prefix envs/virtualenv-1
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```
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`conda` creates a virtual environment in a directory named `./envs/virtualenv-1`.
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4. To activate the new virtual environment, use the `conda activate` command and pass the directory path of the virtual environment:
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```sh
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conda activate envs/VIRTUAL_ENVIRONMENT_NAME
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```
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For example:
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```sh
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conda activate ./envs/virtualenv-1
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```
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<!--------------------------------- END conda --------------------------------->
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{{% /tab-content %}}
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{{< /tabs-wrapper >}}
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When a virtual environment is activated, the name displays at the beginning of your terminal command line--for example:
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{{% code-callout "(virtualenv-1)"%}}
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```sh
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(virtualenv-1) $ PROJECT_DIRECTORY
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```
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{{% /code-callout %}}
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## Query InfluxDB using Flight SQL
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1. [Install the Flight SQL Python Library](#install-the-flight-sql-python-library)
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2. [Create a query client](#create-a-query-client)
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3. [Execute a query](#execute-a-query)
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### Install the Flight SQL Python Library
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The [`flightsql-dbapi`](https://github.com/influxdata/flightsql-dbapi) Flight SQL library for Python provides a
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[DB API 2](https://peps.python.org/pep-0249/) interface and
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[SQLAlchemy](https://www.sqlalchemy.org/) dialect for
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[Flight SQL](https://arrow.apache.org/docs/format/FlightSql.html).
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Installing `flightsql-dbapi` also installs the [`pyarrow`](https://arrow.apache.org/docs/python/index.html) library that you'll use for working with Arrow data.
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In your terminal, use `pip` to install `flightsql-dbapi`:
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```sh
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pip install flightsql-dbapi
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```
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With `flightsql-dbapi` and `pyarrow` installed, you're ready to query and analyze data stored in an InfluxDB database.
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### Create a query client
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The following example shows how to use Python with `flightsql-dbapi`
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and the _DB API 2_ interface to instantiate a Flight SQL client configured for an InfluxDB database.
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1. In your editor, copy and paste the following sample code to a new file--for example, `query-example.py`:
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```py
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# query-example.py
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from flightsql import FlightSQLClient
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# Instantiate a FlightSQLClient configured for your database
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client = FlightSQLClient(host='cluster-id.influxdb.io',
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token='INFLUX_READ_WRITE_TOKEN',
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metadata={'database': 'INFLUX_DATABASE'},
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features={'metadata-reflection': 'true'})
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```
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2. Replace the following configuration values:
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- **`INFLUX_READ_WRITE_TOKEN`**: Your InfluxDB token with read permissions on the databases you want to query.
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- **`INFLUX_DATABASE`**: The name of your InfluxDB database.
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### Execute a query
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To execute an SQL query, call the query client's `execute(query)` method and pass the query as a string.
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#### Syntax {#execute-query-syntax}
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```py
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execute(query: str, call_options: Optional[FlightSQLCallOptions] = None)
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```
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#### Example {#execute-query-example}
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```py
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# query-example.py
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from flightsql import FlightSQLClient
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client = FlightSQLClient(host='cluster-id.influxdb.io',
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token='INFLUX_READ_WRITE_TOKEN',
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metadata={'database': 'INFLUX_DATABASE'},
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features={'metadata-reflection': 'true'})
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# Execute the query
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info = client.execute("SELECT * FROM home")
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```
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The response contains a `flight.FlightInfo` object that contains metadata and an `endpoints: [...]` list. Each endpoint contains the following:
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- A list of addresses where you can retrieve the data.
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- A `ticket` value that identifies the data to retrieve.
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Next, use the ticket to [retrieve data for Flight SQL query results](#retrieve-data-for-flight-sql-query-results)
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### Retrieve data for Flight SQL query results
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To retrieve Arrow data for a query result, call the client's `do_get(ticket)` method.
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#### Syntax {#retrieve-data-syntax}
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```py
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do_get(ticket, call_options: Optional[FlightSQLCallOptions] = None)
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```
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#### Example {#retrieve-data-example}
|
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The following sample shows how to use Python with `flightsql-dbapi` and `pyarrow` to query InfluxDB and retrieve data.
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```py
|
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# query-example.py
|
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|
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from flightsql import FlightSQLClient
|
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|
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# Instantiate a FlightSQLClient configured for a database
|
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client = FlightSQLClient(host='cluster-id.influxdb.io',
|
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token='INFLUX_READ_WRITE_TOKEN',
|
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metadata={'database': 'INFLUX_DATABASE'},
|
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features={'metadata-reflection': 'true'})
|
||||
|
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# Execute the query to retrieve FlightInfo
|
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info = client.execute("SELECT * FROM home")
|
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|
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# Extract the token for retrieving data
|
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ticket = info.endpoints[0].ticket
|
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|
||||
# Use the ticket to request the Arrow data stream.
|
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# Return a FlightStreamReader for streaming the results.
|
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reader = client.do_get(ticket)
|
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|
||||
# Read all data to a pyarrow.Table
|
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table = reader.read_all()
|
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```
|
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|
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`do_get(ticket)` returns a [`pyarrow.flight.FlightStreamReader`](https://arrow.apache.org/docs/python/generated/pyarrow.flight.FlightStreamReader.html) for streaming Arrow [record batches](https://arrow.apache.org/docs/python/data.html#record-batches).
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|
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To read data from the stream, call one of the following `FlightStreamReader` methods:
|
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|
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- `read_all()`: Read all record batches as a [`pyarrow.Table`](https://arrow.apache.org/docs/python/generated/pyarrow.Table.html).
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- `read_chunk()`: Read the next RecordBatch and metadata.
|
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- `read_pandas()`: Read all record batches and convert them to a [`pandas.DataFrame`](https://pandas.pydata.org/docs/reference/frame.html).
|
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|
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Next, learn how to use Python tools to work with time series data:
|
||||
|
||||
- [Use PyArrow](/influxdb/cloud-dedicated/query-data/tools/pyarrow/)
|
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- [Use pandas](/influxdb/cloud-dedicated/query-data/tools/pandas/)
|
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|
|
@ -0,0 +1,19 @@
|
|||
---
|
||||
title: Query data with InfluxQL
|
||||
description: >
|
||||
Learn to use InfluxQL to query data stored in InfluxDB Cloud Dedicated.
|
||||
menu:
|
||||
influxdb_cloud_dedicated:
|
||||
name: Query with InfluxQL
|
||||
parent: Query data
|
||||
weight: 102
|
||||
influxdb/cloud-dedicated/tags: [query, influxql]
|
||||
---
|
||||
|
||||
Learn to use InfluxQL to query data stored in InfluxDB Cloud Dedicated.
|
||||
|
||||
{{< children type="anchored-list" >}}
|
||||
|
||||
---
|
||||
|
||||
{{< children readmore=true hr=true >}}
|
||||
|
|
@ -0,0 +1,17 @@
|
|||
---
|
||||
title: Execute InfluxQL queries
|
||||
description: >
|
||||
Use tools and libraries to query data with InfluxQL stored in InfluxDB Cloud Dedicated.
|
||||
weight: 201
|
||||
menu:
|
||||
influxdb_cloud_dedicated:
|
||||
name: Execute InfluxQL queries
|
||||
parent: Query with InfluxQL
|
||||
identifier: influxql-execute-queries
|
||||
influxdb/cloud-dedicated/tags: [query, influxql]
|
||||
---
|
||||
|
||||
There are multiple ways to execute InfluxQL queries with {{< cloud-name >}}.
|
||||
Choose from the following options:
|
||||
|
||||
{{< children readmore=true hr=true >}}
|
||||
|
|
@ -0,0 +1,126 @@
|
|||
---
|
||||
title: Use the InfluxDB v1 HTTP query API to query with InfluxQL
|
||||
seotitle: Use InfluxQL and InfluxDB v1 HTTP query API
|
||||
description: >
|
||||
Use the InfluxDB v1 HTTP query API to query data in InfluxDB Cloud Dedicated
|
||||
with InfluxQL.
|
||||
weight: 401
|
||||
menu:
|
||||
influxdb_cloud_dedicated:
|
||||
parent: influxql-execute-queries
|
||||
name: Use the v1 query API
|
||||
influxdb/cloud-dedicated/tags: [query, influxql, python]
|
||||
list_code_example: |
|
||||
```sh
|
||||
curl --get https://cluster-id.influxdb.io/query \
|
||||
--header "Authorization: Token DATABASE_TOKEN" \
|
||||
--data-urlencode "db=DATABASE_NAME" \
|
||||
--data-urlencode "q=SELECT * FROM home"
|
||||
```
|
||||
---
|
||||
|
||||
Use the InfluxDB v1 HTTP query API to query data in {{< cloud-name >}}
|
||||
with InfluxQL.
|
||||
|
||||
The examples below use **cURL** to send HTTP requests to the InfluxDB v1 HTTP API,
|
||||
but you can use any HTTP client.
|
||||
|
||||
{{% warn %}}
|
||||
#### InfluxQL feature support
|
||||
|
||||
InfluxQL is being rearchitected to work with the InfluxDB IOx storage engine.
|
||||
This process is ongoing and some InfluxQL features are still being implemented.
|
||||
For information about the current implementation status of InfluxQL features,
|
||||
see [InfluxQL feature support](/influxdb/cloud-dedicated/reference/influxql/feature-support/).
|
||||
{{% /warn %}}
|
||||
|
||||
Use the v1 `/query` endpoint and the `GET` request method to query data with InfluxQL:
|
||||
|
||||
{{< api-endpoint endpoint="https://cluster-id.influxdb.io/query" method="get" api-ref="/influxdb/cloud-dedicated/api/#tag/Query" >}}
|
||||
|
||||
Provide the following with your request:
|
||||
|
||||
- **Headers:**
|
||||
- **Authorization:** `Bearer DATABASE_TOKEN`
|
||||
- **Query parameters:**
|
||||
- **db**: Database to query
|
||||
- **rp**: _(Optional)_ Retention policy to query
|
||||
- **q**: URL-encoded InfluxQL query
|
||||
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```sh
|
||||
curl --get https://cluster-id.influxdb.io/query \
|
||||
--header "Authorization: Token DATABASE_TOKEN" \
|
||||
--data-urlencode "db=DATABASE_NAME" \
|
||||
--data-urlencode "q=SELECT * FROM home"
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
|
||||
Replace the following:
|
||||
|
||||
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
|
||||
Name of the database to query
|
||||
- {{% code-placeholder-key %}}`DATABASE_TOKEN`{{% /code-placeholder-key %}}:
|
||||
|
||||
|
||||
{{% note %}}
|
||||
#### Authenticate with username and password
|
||||
|
||||
If using basic authentication or query string authentication (username and password)
|
||||
to interact with the v1 HTTP query API, provide the following credentials:
|
||||
|
||||
- **username**: Arbitrary string _({{< cloud-name >}} ignores the username)_
|
||||
- **password**: [Database token](/influxdb/cloud-dedicated/admin/tokens/) with read permission
|
||||
on the database you want to query
|
||||
|
||||
{{< code-tabs-wrapper >}}
|
||||
{{% code-tabs %}}
|
||||
[Basic Auth](#)
|
||||
[Query String Auth](#)
|
||||
{{% /code-tabs %}}
|
||||
|
||||
{{% code-tab-content %}}
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```sh
|
||||
curl --get https://cluster-id.influxdb.io/query \
|
||||
--header "Authorization: Basic ignored:DATABASE_TOKEN" \
|
||||
--data-urlencode "db=DATABASE_NAME" \
|
||||
--data-urlencode "q=SELECT * FROM home"
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
{{% /code-tab-content %}}
|
||||
|
||||
{{% code-tab-content %}}
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```sh
|
||||
curl --get https://cluster-id.influxdb.io/query \
|
||||
--data-urlencode "u=ignored" \
|
||||
--data-urlencode "p=DATABASE_TOKEN" \
|
||||
--data-urlencode "db=DATABASE_NAME" \
|
||||
--data-urlencode "q=SELECT * FROM home"
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
{{% /code-tab-content %}}
|
||||
|
||||
{{< /code-tabs-wrapper >}}
|
||||
{{% /note %}}
|
||||
|
||||
## Return results as JSON or CSV
|
||||
|
||||
By default, the `/query` endpoint returns results in **JSON**, but it can also
|
||||
return results in **CSV**. To return results as CSV, include the `Accept` header
|
||||
with the `application/csv` or `text/csv` MIME type:
|
||||
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```sh
|
||||
curl --get https://cluster-id.influxdb.io/query \
|
||||
--header "Authorization: Token DATABASE_TOKEN" \
|
||||
--header "Accept: application/csv" \
|
||||
--data-urlencode "db=DATABASE_NAME" \
|
||||
--data-urlencode "q=SELECT * FROM home"
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
|
||||
<!--
|
||||
TO-DO: Explain how DBRP mappings work with bucket names
|
||||
-->
|
||||
|
|
@ -0,0 +1,285 @@
|
|||
---
|
||||
title: Use Python to query data with InfluxQL
|
||||
description: >
|
||||
Use Python and the `influxdb3-python` library to query data stored in InfluxDB
|
||||
with InfluxQL.
|
||||
weight: 401
|
||||
menu:
|
||||
influxdb_cloud_dedicated:
|
||||
parent: influxql-execute-queries
|
||||
name: Use Python
|
||||
identifier: query-with-python-influxql
|
||||
influxdb/cloud-dedicated/tags: [query, influxql, python]
|
||||
related:
|
||||
- /influxdb/cloud-dedicated/query-data/tools/pandas/
|
||||
- /influxdb/cloud-dedicated/query-data/tools/pyarrow/
|
||||
- /influxdb/cloud-dedicated/reference/influxql/
|
||||
list_code_example: |
|
||||
```py
|
||||
from influxdb_client_3 import InfluxDBClient3
|
||||
|
||||
# Instantiate an InfluxDB client
|
||||
client = InfluxDBClient3(
|
||||
host='cluster-id.influxdb.io',
|
||||
token='DATABASE_TOKEN',
|
||||
database='DATABASE_NAME'
|
||||
)
|
||||
|
||||
# Execute the query and return an Arrow table
|
||||
table = client.query(
|
||||
query="SELECT * FROM home",
|
||||
language="influxql"
|
||||
)
|
||||
|
||||
# Return query results as a markdown table
|
||||
print(table.to_pandas().to_markdown())
|
||||
```
|
||||
---
|
||||
|
||||
Use the `influxdb3-python` client library to query data stored in InfluxDB with InfluxQL.
|
||||
The `influxdb3-client` uses Flight SQL to query data from InfluxDB and return
|
||||
results in Apache Arrow format.
|
||||
|
||||
- [Get started using Python to query InfluxDB](#get-started-using-python-to-query-influxdb)
|
||||
- [Create a Python virtual environment](#create-a-python-virtual-environment)
|
||||
- [Install Python](#install-python)
|
||||
- [Create a project virtual environment](#venv-install)
|
||||
- [Install Anaconda](?t=Anaconda#conda-install)
|
||||
- [Query InfluxDB](#query-influxdb)
|
||||
- [Install the influxdb3-python library](#install-the-influxdb3-python-library)
|
||||
- [Create an InfluxDB client](#create-an-influxdb-client)
|
||||
- [Execute a query](#execute-a-query)
|
||||
|
||||
{{% warn %}}
|
||||
#### InfluxQL feature support
|
||||
|
||||
InfluxQL is being rearchitected to work with the InfluxDB IOx storage engine.
|
||||
This process is ongoing and some InfluxQL features are still being implemented.
|
||||
For information about the current implementation status of InfluxQL features,
|
||||
see [InfluxQL feature support](/influxdb/cloud-dedicated/reference/influxql/feature-support/).
|
||||
{{% /warn %}}
|
||||
|
||||
## Get started using Python to query InfluxDB
|
||||
|
||||
This guide follows the recommended practice of using Python _virtual environments_.
|
||||
If you don't want to use virtual environments and you have Python installed,
|
||||
continue to [Query InfluxDB](#query-influxdb).
|
||||
|
||||
## Create a Python virtual environment
|
||||
|
||||
Python [virtual environments](https://docs.python.org/3/library/venv.html) keep
|
||||
the Python interpreter and dependencies for your project self-contained and isolated from other projects.
|
||||
|
||||
To install Python and create a virtual environment, choose one of the following options:
|
||||
|
||||
- [Python venv](?t=venv#venv-install): The [`venv` module](https://docs.python.org/3/library/venv.html) comes standard in Python as of version 3.5.
|
||||
- [Anaconda® Distribution](?t=Anaconda#conda-install): A Python/R data science distribution that provides Python and the **conda** package and environment manager.
|
||||
|
||||
{{< tabs-wrapper >}}
|
||||
{{% tabs "small" %}}
|
||||
[venv]()
|
||||
[Anaconda]()
|
||||
{{% /tabs %}}
|
||||
{{% tab-content %}}
|
||||
<!--------------------------------- Begin venv -------------------------------->
|
||||
|
||||
### Install Python
|
||||
|
||||
1. Follow the [Python installation instructions](https://wiki.python.org/moin/BeginnersGuide/Download)
|
||||
to install a recent version of the Python programming language for your system.
|
||||
2. Check that you can run `python` and `pip` commands.
|
||||
`pip` is a package manager included in most Python distributions.
|
||||
|
||||
In your terminal, enter the following commands:
|
||||
|
||||
```sh
|
||||
python --version
|
||||
```
|
||||
|
||||
```sh
|
||||
pip --version
|
||||
```
|
||||
|
||||
Depending on your system, you may need to use version-specific commands--for example.
|
||||
|
||||
```sh
|
||||
python3 --version
|
||||
```
|
||||
|
||||
```sh
|
||||
pip3 --version
|
||||
```
|
||||
|
||||
If neither `pip` nor `pip<PYTHON_VERSION>` works, follow one of the [Pypa.io Pip installation](https://pip.pypa.io/en/stable/installation/) methods for your system.
|
||||
|
||||
### Create a project virtual environment {#venv-install}
|
||||
|
||||
1. Create a directory for your Python project and change to the new directory--for example:
|
||||
|
||||
```sh
|
||||
mkdir ./PROJECT_DIRECTORY && cd $_
|
||||
```
|
||||
|
||||
2. Use the Python `venv` module to create a virtual environment--for example:
|
||||
|
||||
```sh
|
||||
python -m venv envs/virtualenv-1
|
||||
```
|
||||
|
||||
`venv` creates the new virtual environment directory in your project.
|
||||
|
||||
3. To activate the new virtual environment in your terminal, run the `source` command and pass the file path of the virtual environment `activate` script:
|
||||
|
||||
```sh
|
||||
source envs/VIRTUAL_ENVIRONMENT_NAME/bin/activate
|
||||
```
|
||||
|
||||
For example:
|
||||
|
||||
```sh
|
||||
source envs/virtualenv-1/bin/activate
|
||||
```
|
||||
<!---------------------------------- End venv --------------------------------->
|
||||
{{% /tab-content %}}
|
||||
{{% tab-content %}}
|
||||
<!-------------------------------- Begin conda -------------------------------->
|
||||
|
||||
### Install Anaconda {#conda-install}
|
||||
|
||||
1. Follow the [Anaconda installation instructions](https://docs.continuum.io/anaconda/install/) for your system.
|
||||
2. Check that you can run the `conda` command:
|
||||
|
||||
```sh
|
||||
conda
|
||||
```
|
||||
|
||||
3. Use `conda` to create a virtual environment--for example:
|
||||
|
||||
```sh
|
||||
conda create --prefix envs/virtualenv-1
|
||||
```
|
||||
|
||||
`conda` creates a virtual environment in a directory named `./envs/virtualenv-1`.
|
||||
|
||||
4. To activate the new virtual environment, use the `conda activate` command and pass the directory path of the virtual environment:
|
||||
|
||||
```sh
|
||||
conda activate envs/VIRTUAL_ENVIRONMENT_NAME
|
||||
```
|
||||
|
||||
For example:
|
||||
|
||||
```sh
|
||||
conda activate ./envs/virtualenv-1
|
||||
```
|
||||
|
||||
<!--------------------------------- END conda --------------------------------->
|
||||
{{% /tab-content %}}
|
||||
{{< /tabs-wrapper >}}
|
||||
|
||||
When a virtual environment is activated, the name displays at the beginning of your terminal command line--for example:
|
||||
|
||||
{{% code-callout "(virtualenv-1)"%}}
|
||||
```sh
|
||||
(virtualenv-1) $ PROJECT_DIRECTORY
|
||||
```
|
||||
{{% /code-callout %}}
|
||||
|
||||
## Query InfluxDB
|
||||
|
||||
1. [Install the influxdb3-python library](#install-the-influxdb3-python-library)
|
||||
2. [Create an InfluxDB client](#create-an-influxdb-client)
|
||||
3. [Execute a query](#execute-a-query)
|
||||
|
||||
### Install the influxdb3-python library
|
||||
|
||||
The `influxdb_client_3` module provides a simple and convenient way to interact
|
||||
with {{< cloud-name >}} using Python. This module supports both writing data to
|
||||
InfluxDB and querying data using SQL or InfluxQL queries.
|
||||
|
||||
Installing `inflxudb3-python` also installs the
|
||||
[`pyarrow`](https://arrow.apache.org/docs/python/index.html) library that you'll
|
||||
use for working with Arrow data returned from queries.
|
||||
|
||||
In your terminal, use `pip` to install `influxdb3-python`:
|
||||
|
||||
```sh
|
||||
pip install influxdb3-python
|
||||
```
|
||||
|
||||
With `influxdb3-python` and `pyarrow` installed, you're ready to query and
|
||||
analyze data stored in an InfluxDB database.
|
||||
|
||||
### Create an InfluxDB client
|
||||
|
||||
The following example shows how to use Python with `influxdb3-python`
|
||||
and to instantiate a client configured for an InfluxDB database.
|
||||
|
||||
In your editor, copy and paste the following sample code to a new file--for
|
||||
example, `query-example.py`:
|
||||
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```py
|
||||
# query-example.py
|
||||
|
||||
from influxdb_client_3 import InfluxDBClient3
|
||||
|
||||
# Instantiate an InfluxDBClient3 client configured for your database
|
||||
client = InfluxDBClient3(
|
||||
host='cluster-id.influxdb.io',
|
||||
token='DATABASE_TOKEN',
|
||||
database='DATABASE_NAME'
|
||||
)
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
|
||||
Replace the following configuration values:
|
||||
|
||||
- {{% code-placeholder-key %}}`DATABASE_TOKEN`{{% /code-placeholder-key %}}:
|
||||
Your InfluxDB token with read permissions on the databases you want to query.
|
||||
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
|
||||
The name of your InfluxDB database.
|
||||
|
||||
### Execute a query
|
||||
|
||||
To execute an InfluxQL query, call the client's `query(query,language)` method
|
||||
and specify the following arguments:
|
||||
|
||||
- **query**: InfluxQL query string to execute.
|
||||
- **language**: `influxql`
|
||||
|
||||
#### Syntax {#execute-query-syntax}
|
||||
|
||||
```py
|
||||
query(query: str, language: str)
|
||||
```
|
||||
|
||||
#### Example {#execute-query-example}
|
||||
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```py
|
||||
# query-example.py
|
||||
|
||||
from influxdb_client_3 import InfluxDBClient3
|
||||
|
||||
client = InfluxDBClient3(
|
||||
host='cluster-id.influxdb.io',
|
||||
token='DATABASE_TOKEN',
|
||||
database='DATABASE_NAME'
|
||||
)
|
||||
|
||||
# Execute the query and return an Arrow table
|
||||
table = client.query(
|
||||
query="SELECT * FROM home",
|
||||
language="influxql"
|
||||
)
|
||||
|
||||
# Return query results as a markdown table
|
||||
print(table.to_pandas().to_markdown())
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
|
||||
Next, learn how to use Python tools to work with time series data:
|
||||
|
||||
- [Use PyArrow](/influxdb/cloud-dedicated/query-data/tools/pyarrow/)
|
||||
- [Use pandas](/influxdb/cloud-dedicated/query-data/tools/pandas/)
|
||||
|
|
@ -0,0 +1,30 @@
|
|||
---
|
||||
title: Execute SQL queries
|
||||
description: >
|
||||
Use tools and libraries to query data with SQL stored in InfluxDB Cloud Dedicated.
|
||||
weight: 201
|
||||
menu:
|
||||
influxdb_cloud_dedicated:
|
||||
name: Execute SQL queries
|
||||
parent: Query with SQL
|
||||
identifier: sql-execute-queries
|
||||
influxdb/cloud-dedicated/tags: [query, sql]
|
||||
aliases:
|
||||
- /influxdb/cloud-dedicated/query-data/execute-queries/
|
||||
---
|
||||
|
||||
The InfluxDB SQL implementation uses [Arrow DataFusion](https://arrow.apache.org/datafusion/)
|
||||
and the [Apache Arrow Flight SQL](https://arrow.apache.org/) protocol to query
|
||||
data stored in an InfluxDB database.
|
||||
|
||||
> Arrow Flight SQL is a protocol for interacting with SQL databases using the
|
||||
> [Arrow in-memory format](https://arrow.apache.org/docs/format/Columnar.html)
|
||||
> and the [Flight RPC](https://arrow.apache.org/docs/format/Flight.html) framework.
|
||||
>
|
||||
> {{% caption %}}[Apache Arrow Flight SQL documentation](https://arrow.apache.org/docs/format/FlightSql.html){{% /caption %}}
|
||||
|
||||
Data platforms and clients that support the Flight SQL protocol can query data
|
||||
stored in an InfluxDB database.
|
||||
Learn how to connect to InfluxDB and query your data using the following tools:
|
||||
|
||||
{{< children readmore=true hr=true hlevel="h2" >}}
|
||||
|
|
@ -0,0 +1,283 @@
|
|||
---
|
||||
title: Use Python to query data with SQL
|
||||
description: >
|
||||
Use Python and the `influxdb3-python` library to query data stored in InfluxDB
|
||||
with SQL.
|
||||
weight: 401
|
||||
menu:
|
||||
influxdb_cloud_dedicated:
|
||||
parent: sql-execute-queries
|
||||
name: Use Python
|
||||
identifier: query-with-python-sql
|
||||
influxdb/cloud-dedicated/tags: [query, flightsql, python]
|
||||
aliases:
|
||||
- /influxdb/cloud-dedicated/query-data/execute-queries/flight-sql/python/
|
||||
related:
|
||||
- /influxdb/cloud-dedicated/query-data/tools/pandas/
|
||||
- /influxdb/cloud-dedicated/query-data/tools/pyarrow/
|
||||
- /influxdb/cloud-dedicated/reference/sql/
|
||||
list_code_example: |
|
||||
```py
|
||||
from influxdb_client_3 import InfluxDBClient3
|
||||
|
||||
# Instantiate an InfluxDB client
|
||||
client = InfluxDBClient3(
|
||||
host='cluster-id.influxdb.io',
|
||||
token='DATABASE_TOKEN',
|
||||
database='DATABASE_NAME'
|
||||
)
|
||||
|
||||
# Execute the query and return an Arrow table
|
||||
table = client.query(
|
||||
query="SELECT * FROM home",
|
||||
language="sql"
|
||||
)
|
||||
|
||||
# Return query results as a markdown table
|
||||
print(table.to_pandas().to_markdown())
|
||||
```
|
||||
---
|
||||
|
||||
Use the `influxdb3-python` client library to query data stored in InfluxDB with SQL.
|
||||
The `influxdb3-client` uses Flight SQL to query data from InfluxDB and return
|
||||
results in Apache Arrow format.
|
||||
|
||||
- [Get started using Python to query InfluxDB](#get-started-using-python-to-query-influxdb)
|
||||
- [Create a Python virtual environment](#create-a-python-virtual-environment)
|
||||
- [Install Python](#install-python)
|
||||
- [Create a project virtual environment](#venv-install)
|
||||
- [Install Anaconda](?t=Anaconda#conda-install)
|
||||
- [Query InfluxDB](#query-influxdb)
|
||||
- [Install the influxdb3-python library](#install-the-influxdb3-python-library)
|
||||
- [Create an InfluxDB client](#create-an-influxdb-client)
|
||||
- [Execute a query](#execute-a-query)
|
||||
|
||||
## Get started using Python to query InfluxDB
|
||||
|
||||
This guide follows the recommended practice of using Python _virtual environments_.
|
||||
If you don't want to use virtual environments and you have Python installed,
|
||||
continue to [Query InfluxDB](#query-influxdb).
|
||||
|
||||
## Create a Python virtual environment
|
||||
|
||||
Python [virtual environments](https://docs.python.org/3/library/venv.html) keep
|
||||
the Python interpreter and dependencies for your project self-contained and isolated from other projects.
|
||||
|
||||
To install Python and create a virtual environment, choose one of the following options:
|
||||
|
||||
- [Python venv](?t=venv#venv-install): The [`venv` module](https://docs.python.org/3/library/venv.html) comes standard in Python as of version 3.5.
|
||||
- [Anaconda® Distribution](?t=Anaconda#conda-install): A Python/R data science distribution that provides Python and the **conda** package and environment manager.
|
||||
|
||||
{{< tabs-wrapper >}}
|
||||
{{% tabs "small" %}}
|
||||
[venv]()
|
||||
[Anaconda]()
|
||||
{{% /tabs %}}
|
||||
{{% tab-content %}}
|
||||
<!--------------------------------- Begin venv -------------------------------->
|
||||
|
||||
### Install Python
|
||||
|
||||
1. Follow the [Python installation instructions](https://wiki.python.org/moin/BeginnersGuide/Download)
|
||||
to install a recent version of the Python programming language for your system.
|
||||
2. Check that you can run `python` and `pip` commands.
|
||||
`pip` is a package manager included in most Python distributions.
|
||||
|
||||
In your terminal, enter the following commands:
|
||||
|
||||
```sh
|
||||
python --version
|
||||
```
|
||||
|
||||
```sh
|
||||
pip --version
|
||||
```
|
||||
|
||||
Depending on your system, you may need to use version-specific commands--for example.
|
||||
|
||||
```sh
|
||||
python3 --version
|
||||
```
|
||||
|
||||
```sh
|
||||
pip3 --version
|
||||
```
|
||||
|
||||
If neither `pip` nor `pip<PYTHON_VERSION>` works, follow one of the [Pypa.io Pip installation](https://pip.pypa.io/en/stable/installation/) methods for your system.
|
||||
|
||||
### Create a project virtual environment {#venv-install}
|
||||
|
||||
1. Create a directory for your Python project and change to the new directory--for example:
|
||||
|
||||
```sh
|
||||
mkdir ./PROJECT_DIRECTORY && cd $_
|
||||
```
|
||||
|
||||
2. Use the Python `venv` module to create a virtual environment--for example:
|
||||
|
||||
```sh
|
||||
python -m venv envs/virtualenv-1
|
||||
```
|
||||
|
||||
`venv` creates the new virtual environment directory in your project.
|
||||
|
||||
3. To activate the new virtual environment in your terminal, run the `source` command and pass the file path of the virtual environment `activate` script:
|
||||
|
||||
```sh
|
||||
source envs/VIRTUAL_ENVIRONMENT_NAME/bin/activate
|
||||
```
|
||||
|
||||
For example:
|
||||
|
||||
```sh
|
||||
source envs/virtualenv-1/bin/activate
|
||||
```
|
||||
<!---------------------------------- End venv --------------------------------->
|
||||
{{% /tab-content %}}
|
||||
{{% tab-content %}}
|
||||
<!-------------------------------- Begin conda -------------------------------->
|
||||
|
||||
### Install Anaconda {#conda-install}
|
||||
|
||||
1. Follow the [Anaconda installation instructions](https://docs.continuum.io/anaconda/install/) for your system.
|
||||
2. Check that you can run the `conda` command:
|
||||
|
||||
```sh
|
||||
conda
|
||||
```
|
||||
|
||||
3. Use `conda` to create a virtual environment--for example:
|
||||
|
||||
```sh
|
||||
conda create --prefix envs/virtualenv-1
|
||||
```
|
||||
|
||||
`conda` creates a virtual environment in a directory named `./envs/virtualenv-1`.
|
||||
|
||||
4. To activate the new virtual environment, use the `conda activate` command and pass the directory path of the virtual environment:
|
||||
|
||||
```sh
|
||||
conda activate envs/VIRTUAL_ENVIRONMENT_NAME
|
||||
```
|
||||
|
||||
For example:
|
||||
|
||||
```sh
|
||||
conda activate ./envs/virtualenv-1
|
||||
```
|
||||
|
||||
<!--------------------------------- END conda --------------------------------->
|
||||
{{% /tab-content %}}
|
||||
{{< /tabs-wrapper >}}
|
||||
|
||||
When a virtual environment is activated, the name displays at the beginning of your terminal command line--for example:
|
||||
|
||||
{{% code-callout "(virtualenv-1)"%}}
|
||||
```sh
|
||||
(virtualenv-1) $ PROJECT_DIRECTORY
|
||||
```
|
||||
{{% /code-callout %}}
|
||||
|
||||
## Query InfluxDB
|
||||
|
||||
1. [Install the influxdb3-python library](#install-the-influxdb3-python-library)
|
||||
2. [Create an InfluxDB client](#create-an-influxdb-client)
|
||||
3. [Execute a query](#execute-a-query)
|
||||
|
||||
### Install the influxdb3-python library
|
||||
|
||||
The `influxdb_client_3` module provides a simple and convenient way to interact
|
||||
with {{< cloud-name >}} using Python. This module supports both writing data to
|
||||
InfluxDB and querying data using SQL or InfluxQL queries.
|
||||
|
||||
{{% note %}}
|
||||
_To query data with **InfluxQL** and Python, see
|
||||
[Use InfluxQL with Python](/influxdb/cloud-dedicated/query-data/influxql/execute-queries/python/)._
|
||||
{{% /note %}}
|
||||
|
||||
Installing `inflxudb3-python` also installs the
|
||||
[`pyarrow`](https://arrow.apache.org/docs/python/index.html) library that you'll
|
||||
use for working with Arrow data returned from queries.
|
||||
|
||||
In your terminal, use `pip` to install `influxdb3-python`:
|
||||
|
||||
```sh
|
||||
pip install influxdb3-python
|
||||
```
|
||||
|
||||
With `influxdb3-python` and `pyarrow` installed, you're ready to query and
|
||||
analyze data stored in an InfluxDB database.
|
||||
|
||||
### Create an InfluxDB client
|
||||
|
||||
The following example shows how to use Python with `influxdb3-python`
|
||||
and to instantiate a client configured for an InfluxDB database.
|
||||
|
||||
In your editor, copy and paste the following sample code to a new file--for
|
||||
example, `query-example.py`:
|
||||
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```py
|
||||
# query-example.py
|
||||
|
||||
from influxdb_client_3 import InfluxDBClient3
|
||||
|
||||
# Instantiate an InfluxDBClient3 client configured for your database
|
||||
client = InfluxDBClient3(
|
||||
host='b0c7cce5-8dbc-428e-98c6-7f996fb96467.a.influxdb.io',
|
||||
token='DATABASE_TOKEN',
|
||||
database='DATABASE_NAME'
|
||||
)
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
|
||||
Replace the following configuration values:
|
||||
|
||||
- {{% code-placeholder-key %}}`DATABASE_TOKEN`{{% /code-placeholder-key %}}:
|
||||
Your InfluxDB token with read permissions on the databases you want to query.
|
||||
- {{% code-placeholder-key %}}`DATABASE_NAME`{{% /code-placeholder-key %}}:
|
||||
The name of your InfluxDB database.
|
||||
|
||||
### Execute a query
|
||||
|
||||
To execute an SQL query, call the client's `query(query,language)` method and
|
||||
specify the following arguments:
|
||||
|
||||
- **query**: SQL query string to execute.
|
||||
- **language**: `sql`
|
||||
|
||||
#### Syntax {#execute-query-syntax}
|
||||
|
||||
```py
|
||||
query(query: str, language: str)
|
||||
```
|
||||
|
||||
#### Example {#execute-query-example}
|
||||
|
||||
{{% code-placeholders "DATABASE_(NAME|TOKEN)" %}}
|
||||
```py
|
||||
# query-example.py
|
||||
|
||||
from influxdb_client_3 import InfluxDBClient3
|
||||
|
||||
client = InfluxDBClient3(
|
||||
host='cluster-id.influxdb.io',
|
||||
token='DATABASE_TOKEN',
|
||||
database='DATABASE_NAME'
|
||||
)
|
||||
|
||||
# Execute the query and return an Arrow table
|
||||
table = client.query(
|
||||
query="SELECT * FROM home",
|
||||
language="sql"
|
||||
)
|
||||
|
||||
# Return query results as a markdown table
|
||||
print(table.to_pandas().to_markdown())
|
||||
```
|
||||
{{% /code-placeholders %}}
|
||||
|
||||
Next, learn how to use Python tools to work with time series data:
|
||||
|
||||
- [Use PyArrow](/influxdb/cloud-dedicated/query-data/tools/pyarrow/)
|
||||
- [Use pandas](/influxdb/cloud-dedicated/query-data/tools/pandas/)
|
||||
|
|
@ -4,13 +4,15 @@ seotitle: Use Apache Superset to query data stored in InfluxDB Cloud Dedicated
|
|||
description: >
|
||||
Install and run [Apache Superset](https://superset.apache.org/)
|
||||
to query data stored in InfluxDB.
|
||||
weight: 101
|
||||
weight: 401
|
||||
menu:
|
||||
influxdb_cloud_dedicated:
|
||||
parent: Query with Flight SQL
|
||||
parent: sql-execute-queries
|
||||
name: Use Superset
|
||||
identifier: query_with_superset
|
||||
identifier: query-with-superset
|
||||
influxdb/cloud-dedicated/tags: [query, flightsql, superset]
|
||||
aliases:
|
||||
- /influxdb/cloud-dedicated/query-data/execute-queries/flight-sql/superset/
|
||||
related:
|
||||
- /influxdb/cloud-dedicated/visualize-data/superset/
|
||||
---
|
||||
|
|
@ -0,0 +1 @@
|
|||
<span class="code-placeholder-key">{{.Inner}}</span>
|
||||
Loading…
Reference in New Issue