Visualizing data from CHYT

This section explains how to connect CHYT using a public clique as a data source for DataLens.

Getting startedGetting started

To use a YTsaurus table as a data source, select the CHYT clique you will be working with.

When working with CHYT, you can use the public *ch_public clique.

Prepare a data table on YTsaurusPrepare a data table on YTsaurus

Before creating a connector in CHYT, prepare your table on YTsaurus:

• The table must be static. Learn more about static tables in YTsaurus.

• The table must be schematized. DataLens queries the table and gets its schema to create a dataset. Learn more about schemas in YTsaurus.

Create a chartCreate a chart

To create a chart in DataLens, you need to create a connection and dataset over it.

Create a connectionCreate a connection

To work with CHYT, create a CHYT connection.

To create a YTsaurus CHYT connection:

1. Open the page for creating a new connection.

2. Under Databases, select the YTsaurus CHYT connection.

3. Configure the connection as follows:

   • Host name: Specify the YTsaurus proxy server address.
   • Port: Specify the CHYT connection port.
   • Clique alias: Specify the alias of a running clique. By default, the *ch_public public clique is used.
   • YTsaurus token: Manually set the OAuth token to use with YTsaurus. For more information, see this YTsaurus guide.
   • Cache TTL in seconds: Specify the cache TTL or leave the default value. The recommended value is 300 seconds (5 minutes).

   • Raw SQL level: Enables you to use an ad-hoc SQL query to generate a dataset. This option is disabled by default. When enabling it, you will need to select the raw SQL level:

     • Allow subqueries in datasets: Describe dataset sources using SQL queries.
     • Allow subqueries in datasets and source parameterization: Describe dataset sources using SQL queries and use source parameterization.
     • Allow subqueries in datasets, source parameterization, and QL charts: Describe dataset sources using SQL queries, use source parameterization, and create QL charts.
   • HTTPS. Enable the secure connection option if your server supports HTTPS.

   

4. Optionally, test the connection by clicking Check connection.

5. Click Create connection.

6. Select a workbook to save your connection to or create a new one. If using legacy folder navigation, select a folder to save the connection to. Click Create.

7. Enter a name for the connection and click Create.

Additional settingsAdditional settings

You can limit data export from charts by enabling the Disable data export option under Advanced connection settings. Thus, for charts based on the respective connection, the export data option will not be available in their menu. However, you will still be able to copy chart data and take screenshots.

You can go straight to creating a dataset from the connection creation interface. To do this, in the top-right corner, click Create dataset.

Create a datasetCreate a dataset

After creating a connection, you can create a dataset over it.

1. In the left-hand navigation menu, click and then click Create dataset in the top-right corner.

2. In the window that opens, in the Connections section, click + Add. Select the CHYT connection you created earlier.

3. Select the source indication method:

   • Table: One table on YTsaurus. URL from the browser or a full path to a table.

   • List: Multiple tables on YTsaurus. URL from the browser or a full path to a table. Use a new row for each table.

   • Range: Range of tables on YTsaurus. You can set your own table range using the Start with and Finish at fields. DataLens will add all the tables specified in the range to the dataset in alphabetical order. If the limit values are left blank, DataLens will use all the tables in the specified folder. You can also set only one limit value.

     Note

     Let's assume a folder contains twenty tables named table_1, table_2, table_3, ... . If you set the limits as 1 and 5, DataLens will use only five tables from the folder.

   • SQL: Selecting data for a dataset via an SQL query. We recommend copying a query from Query in ClickHouse® syntax and then pasting it into the field.

     Warning

     First, process the query you got from Query: delete all semicolon characters (;). An entire Query query from DataLens is run as a subquery.

4. Click Save. Make sure the data is displayed in the dataset preview.

5. Click Save in the top-right corner. Enter a name for the dataset and click Create. The dataset will appear in the list of datasets available to you.

On top of the created dataset, you can create various charts and place them on dashboards.

Frequently asked questionsFrequently asked questions

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