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DataUI VCS Robotdtikhonova
DataUI VCS Robot
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Release 08.05.2024
* Added information on filtering charts by charts. * Fixes and improvements. * Translations updated.
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en/_assets/console-icons/xmark.svg

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When creating a link between widgets on a dashboard, you may encounter a situation when the link does not work. This usually happens when you create a link between a selector and a chart built from different datasets. The cause is a link between widgets based on a field not used to pick values in the selector:
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When creating a link between widgets on a dashboard, you may encounter a situation when the link does not work. This usually happens when you create a link between a selector and a chart built from different datasets. Such widgets end up being linked based on a field that is not used in the selector.
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Let's consider this case as an example:
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1\. There is a chart on the dashboard named `Sample: Sales trends` built from a dataset called `Sample CH Sales`.
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4\. We will create a link between the selector and the `Sample: Sales trends` chart using an alias. It is not possible to create a link based on the store name since it is not included in the `Sample CH Sales` dataset used to build the chart.
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![image](../../_assets/datalens/concepts/SampleSelectorShopName.png)
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![image](../../_assets/datalens/concepts/SampleSelectorShopName-int.png)
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Therefore, we will create the link using the `ShopID` field.
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![image](../../_assets/datalens/concepts/SampleSelectorShopID-int.png)
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As a result, the values picked by the selector do not have any effect on chart visualization because the widgets are linked through the `ShopID` field, and the selector picks its values from the `ShopName` field.
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{% note warning %}
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Therefore, we will create the link using the `ShopID` field.
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At the same time, the values picked by the selector don't have any effect on chart visualization.
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![image](../../_assets/datalens/concepts/SampleSelectorShopID.png)
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{% endnote %}
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As a result, the values you choose in the selector do not have any effect on chart visualization because the widgets are linked through the `ShopID` field, and the the selector picks its values from the `ShopName` field.
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The link is illegal because you cannot use one field to pick values for a dataset-based selector and a different field as the target of a link between datasets. This link mechanism is not supported.

en/_includes/datalens/datalens-limits.md

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| Type of limit | Value |
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| ----- | ----- |
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----- | -----
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| Maximum number of tables in a single dataset | 32 |
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| Maximum number of fields in a single dataset | 1,200 |
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#### Chart data limits {#datalens-chart-data-limits}
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Charts in {{ datalens-short-name }} can only display a limited amount of data. If the number of rows (columns and cells for pivot tables) in a dataset exceeds the established limit, the chart will not be built. Therefore, to build a chart from data in a large dataset, select a part of the data to display based on the limits below using [filters](../../datalens/concepts/dataset/settings.md#default-setting):
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Charts in {{ datalens-short-name }} can only display a limited amount of data. If the number of rows (columns and cells for pivot tables) in a dataset exceeds the established limit, the chart will not be built. Therefore, to build a chart from data in a large dataset, select a part of the data to display based on the limits below using the [filters](../../datalens/concepts/dataset/settings.md#default-setting):
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| Chart type | Limit |
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----- | -----
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{% cut "Query example for a {{ CH }} database" %}
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{% cut "Example database query {{ CH }}" %}
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```sql
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SELECT Category, Month, ROUND(SUM(Sales))
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FROM samples.SampleLite
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WHERE Category in not_var{{category}} -- a variable used in the selector
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GROUP BY Category, Month -- grouping by category and month
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ORDER BY Category, Month -- sorting by category and month
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WHERE Category in not_var{{category}}: A variable used in the selector
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GROUP BY Category, Month: Grouping by category and month
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ORDER BY Category, Month: Sorting by category and month
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```
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{% endcut %}
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{% endcut %}

en/_includes/datalens/internal/datalens-yt-connection.md

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To create a {{ ytsaurus-name }} CHYT connection:
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1. Go to the [connections page](https://datalens.yandex.ru/connections).
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1. Click **Create connection**.
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1. Go to the [connections page]({{ link-datalens-main }}/connections).
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1. Click **Create connection**.
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1. Select **{{ ytsaurus-name }} CHYT** as the connection type.
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* **HTTPS**: Enable the secure connection option if your server supports HTTPS.
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1. Click **Create connection**.
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1. Click **Create connection**.
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1. Enter a name for the connection and click **Create**.
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{% include [datalens-check-host](../../../_includes/datalens/operations/datalens-check-host.md) %}
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{% note warning %}
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If you use a new {{ datalens-short-name }} object model with [workbooks and collections](../../../datalens/workbooks-collections/index.md):
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1. Go to the {{ datalens-short-name }} [home page]({{ link-datalens-main }}). In the left-hand panel, select ![collections](../../../_assets/console-icons/rectangles-4.svg) **Collections and workbooks**.
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1. Open the workbook, click **Create** in the top-right corner, and select the appropriate object.
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Follow the guide from step 4.
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{% endnote %}

en/datalens/concepts/aggregation-tutorial.md

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This section describes how data aggregation and grouping work in {{ datalens-short-name }}, how to correctly formulate expressions with aggregations, and also gives examples of SQL queries with aggregations for {{ CH }}.
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The [Selling.csv](https://storage.yandexcloud.net/doc-files/Selling.csv) file will be used as the source of data on sales in cities.
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As source data, we will use the [Selling.csv](https://storage.yandexcloud.net/doc-files/Selling.csv) file with the data on sales in cities.
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## SQL basic concepts {#basic-sql}
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In this case, aggregate functions calculate and return a single resulting value for all rows that are combined into a single group.
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For example, to get the sum of values in the `Sales` column from the table `Selling`, you need to run a query:
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For example, to get the sum of values in the `Sales` column from the table `Selling`, you need to run the following query:
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```sql
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SELECT

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