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Release 04.09.2024
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* Fixes and improvements.
* Translations updated.
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DataUI VCS Robot authored and dtikhonova committed Sep 4, 2024
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2 changes: 1 addition & 1 deletion en/_includes/datalens/datalens-chart-parameters-example.md
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{% cut "Example of using parameters in a chart" %}

One chart is added three times to the **Ticket SLA statistics** dashboard:
One chart is added three times to the **SLA Ticket Statistics** dashboard:

* **Total of tickets created**: The chart is added with no parameter. Data is displayed for all tickets.
* **Closed without SLA violation**: The settings of the chart on the dashboard have the `sla_failed` parameter added with the `not_failed` value. Data is only displayed for the tickets closed with no SLA violations.
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{% note info %}

When you merge data from multiple tables, a dataset will get duplicates of the fields used to create links. You can remove them manually from the list of dataset fields. You can also [describe the dataset using an SQL query](../../datalens/operations/dataset/add-data.md) and exclude duplicate fields from the final set.

{% endnote %}
32 changes: 0 additions & 32 deletions en/_includes/datalens/datalens-data-join-wrong-example.md

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* **Hostname**. Specify the path to a master host or a {{ MY }} master host IP address. You can specify multiple hosts in a comma-separated list. If you are unable to connect to the first host, {{ datalens-short-name }} will select the next one from the list.
* **Port**. Specify the {{ MY }} connection port. The default port is 3306.
* **Path to database**. Specify the name of the database to connect to.
* **Username**. Specify the username for the {{ MY }} connection.
* **Password**. Enter the password for the user.
* **Cache TTL in seconds**. Specify the cache time-to-live 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](../../datalens/concepts/dataset/settings.md#sql-request-in-datatset).
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* **Hostname**: Specify the path to a master host or a {{ PG }} master host IP address. You can specify multiple hosts in a comma-separated list. If you are unable to connect to the first host, {{ datalens-short-name }} will select the next one from the list.
* **Hostname**: Specify the path to a [master host](https://www.postgresql.org/docs/16/runtime-config-replication.html#RUNTIME-CONFIG-REPLICATION-PRIMARY) or a {{ PG }} master host IP address. You can specify multiple hosts in a comma-separated list. If you are unable to connect to the first host, {{ datalens-short-name }} will select the next one from the list.
* **Port**: Specify the {{ PG }} connection port. In {{ datalens-short-name }}, the default port is 6432.
* **Path to database**: Specify the name of the database to connect to.
* **Username**: Specify the username for the {{ PG }} connection.
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16 changes: 8 additions & 8 deletions en/_includes/datalens/internal/datalens-yt-connection.md
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To create a {{ ytsaurus-name }} CHYT connection:

1. Go to the [connections page]({{ link-datalens-main }}/connections).
1. Click **Create connection**.
1. Select **{{ ytsaurus-name }} CHYT** as the connection type.


To create a {{ ytsaurus-name }} CHYT connection:

1. Go to the [workbook](../../../datalens/workbooks-collections/index.md) page or create a new one.
1. In the top-right corner, click **Create****Connection**.
1. Select the **{{ ytsaurus-name }} CHYT** connection.
1. Specify the connection parameters:

* **{{ ytsaurus-name }} token**: Manually set the OAuth token to use with {{ ytsaurus-name }}. For more information, see the [{{ ytsaurus-name }} documentation](https://ytsaurus.tech/docs/en/user-guide/storage/auth).
* **Hostname**: Specify the {{ ytsaurus-name }} 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-name }} token**: Manually set the OAuth token to use with {{ ytsaurus-name }}. For more information, see the [{{ ytsaurus-name }} documentation](https://ytsaurus.tech/docs/en/user-guide/storage/auth).
* **Cache TTL in seconds**: Specify the cache time-to-live or leave the default value. The recommended value is 300 seconds (5 minutes).
* **Raw SQL level**: Select the SQL query access level for the user.
* **HTTPS**: Enable the secure connection option if your server supports HTTPS.


1. Click **Create connection**.
1. (Optional) Make sure the connection works properly. To do this, click **Check connection**.
1. Click **Create connection**.
1. Enter a name for the connection and click **Create**.

{% include [datalens-check-host](../../../_includes/datalens/operations/datalens-check-host.md) %}

## Additional settings {#additional-settings}

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1. In the top-right corner, click **![image](../../../_assets/console-icons/plus.svg) Add field**.
1. Enter a name for the field.
1. Select **Formula** as the data source for the field.
1. Set the formula using [data source functions](../../../datalens/function-ref/all.md).
1. Add the formula using [data source functions](../../../datalens/function-ref/all.md).
1. Click **Create**. The field will appear in the dataset.
2 changes: 2 additions & 0 deletions 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 }}.

{{ datalens-short-name }} accesses the source directly: it sends requests to select data using the SQL dialect of the source database. The request is formed based on the fields used in charts and the functions used in those fields. So, if you understand the basic principles of aggregation in SQL, it will be easier for you to deal with aggregate functions in {{ datalens-short-name }}.

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.

## SQL basic concepts {#basic-sql}
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53 changes: 26 additions & 27 deletions en/datalens/concepts/calculations/index.md
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# Calculable fields
# Calculated fields

A calculable field is an additional [data field](../dataset/index.md#field) with values calculated using a formula.
You can use calculable fields to create new dimensions and measures.
The data source remains unchanged.
A calculated field is an additional [data field](../dataset/index.md#field) with values calculated using a formula.
You can use calculated fields to create new dimensions and measures. The data source remains unchanged.

To write formulas, you can use the existing dataset fields, [parameters](../parameters.md), constants, and [functions](#functions).

You can [create](#how-to-create-calculated-field) calculable fields in the dataset or wizard interface:
You can [create](#how-to-create-calculated-field) calculated fields in the dataset or wizard interface:

* Calculable fields from a dataset are available in all charts above this dataset.
* Calculable fields from the wizard are only available for saved charts.
* Calculated fields from a dataset are available in all charts above this dataset.
* Calculated fields from the wizard are only available for saved charts.

## Calculable fields in datasets {#dataset}
Calculated fields are marked with ![image](../../../_assets/console-icons/function.svg).

## Calculated fields in datasets {#dataset}

You can add new fields to a dataset field list.

When creating a formula, you can use any dataset field, including the calculable fields you previously created.
When creating a formula, you can use any dataset field, including the calculated fields you previously created. In a formula, you can also use parameters created at the dataset level.

After creating a calculable field and saving the dataset, the field becomes available to all charts and dashboard [selectors](../../dashboard/selector.md) based on that dataset.
To hide fields in the wizard, enable the **Don't display** option when creating them.
After creating a calculated field and saving the dataset, the field becomes available to all charts and dashboard [selectors](../../dashboard/selector.md) based on that dataset.

Calculable fields are marked with ![image](../../../_assets/console-icons/function.svg).
To hide fields in the wizard, enable the **Do not display in wizard** option when creating them.

## Calculable fields in charts {#chart}
## Calculated fields in charts {#chart}

You can add new fields when creating and editing charts in the wizard:

* In the list of fields from a dataset.
* In the visualization section.

When creating a formula, you can use any dataset field, including the calculable fields you previously created.
When creating a formula, you can use any dataset field, including the calculated fields you previously created. In a formula, you can also use the parameters of the chart or dataset based on which the chart is created.

If a field is created in a chart, it will not be available to dashboard selectors and other charts.

Calculable fields are marked with ![image](../../../_assets/console-icons/function.svg).

{% note warning %}

In [multi-dataset charts](../chart/index.md#multi-dataset-charts), calculable fields are not applicable to fields from multiple datasets.
In [multi-dataset charts](../chart/index.md#multi-dataset-charts), calculated fields are not applicable to fields from multiple datasets.

{% endnote %}

Expand All @@ -53,27 +51,26 @@ Avoid calculation loops: in a formula, you cannot use a field that uses the same

{% endnote %}


### Notation format {#entry-format}

Write formulas that meet the following requirements:
Write formulas according to the following requirements:

1. Specify function arguments in parentheses, e.g., `YEAR([DATE1])`. Separate multiple arguments with commas.
1. Specify field names in square brackets, such as `[CustomerID]`.
1. Make sure to enter the values of fields and constants in a valid [format](../dataset/index.md#data-types). For example, use a period as a decimal separator: `0.123`.
1. Make sure to enter the values of fields and constants in a valid [format](../data-types.md). For example, use a period as a decimal separator: `0.123`.

{% note info %}

* Field name syntax is case-sensitive. For example, if a formula uses `[NAME]`, and a dataset contains only `[Name]`, the formula field will be highlighted in red.
* Function syntax is not case-sensitive. For instance, `count` and `COUNT` will perform the same operation.
* Function syntax is not case-sensitive. For example, `count` and `COUNT` will perform the same operation.

{% endnote %}

For more information on format, types of accepted arguments, and returned function values, use the **Reference** button when adding a field in the formula editor interface.

## How to create a calculable field {#how-to-create-calculated-field}
## How to create a calculated field {#how-to-create-calculated-field}

You can create calculable fields in the dataset or wizard interface.
You can create calculated fields in the dataset or wizard interface.

{% list tabs %}

Expand All @@ -83,13 +80,15 @@ You can create calculable fields in the dataset or wizard interface.

- Wizard

1. Open the [wizard]({{ link-datalens-main }}/wizard).
1. Select the dataset to create a chart in.
1. In the left part of the screen, click **![image](../../../_assets/console-icons/plus.svg)** above the list of dataset fields.

1. In the left-hand panel, click ![image](../../../_assets/console-icons/chart-column.svg) **Charts** and select the chart created in the [wizard]({{ link-datalens-wizard }}).
1. On the left side of the screen above the list of dataset fields, click ![image](../../../_assets/console-icons/plus.svg) and select **Field**.
1. Enter a name for the field.
1. Enter the required formula.
1. Click **Create**. The field will appear in the list of fields. You can use it as your chart data source.
1. Click **Create**. The field will appear in the list on the left. You can use it in a chart.

{% endlist %}

#### See also {#see-also}

- [{#T}](../../operations/dataset/create-field.md)
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Charts are created in a wizard based on the data from a dataset.



You can create an unlimited number of charts based on a single dataset.

The workspace in the wizard interface is divided into three main panels:
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4 changes: 4 additions & 0 deletions en/datalens/concepts/chart/index.md
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Expand Up @@ -17,7 +17,11 @@ For more information about charts, see the following sections:

* [{#T}](../../operations/chart/create-chart.md)
* [{#T}](../../operations/chart/create-sql-chart.md)
* [{#T}](../../operations/chart/replace-dataset.md)
* [{#T}](../../operations/chart/add-hierarchy.md)
* [{#T}](../../operations/chart/config-chart-navigator.md)
* [{#T}](../../operations/chart/chart-null-settings.md)
* [{#T}](../../operations/chart/create-palette.md)
* [{#T}](../../operations/chart/add-parameters.md)
* [{#T}](../../operations/chart/add-guid.md)
* [{#T}](../../operations/chart/add-parameter-chart.md)
6 changes: 5 additions & 1 deletion en/datalens/concepts/connection.md
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Expand Up @@ -6,10 +6,14 @@ You can create [_datasets_](dataset/index.md) based on connections.

The following connection types are available in {{ datalens-short-name }}:



* [{{ CH }}](../operations/connection/create-clickhouse.md)
* [{{ PG }}](../operations/connection/create-postgresql.md)
* [{{ MY }}](../operations/connection/create-mysql.md)
* [{{ ytsaurus-name }} CHYT](../operations/connection/chyt/create-chyt.md)
* [{{ GP }}](../operations/connection/create-greenplum.md)



{% include [clickhouse-disclaimer](../../_includes/clickhouse-disclaimer.md) %}
{% include [clickhouse-disclaimer](../../_includes/clickhouse-disclaimer.md) %}
3 changes: 3 additions & 0 deletions en/datalens/concepts/dashboard.md
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Expand Up @@ -14,7 +14,9 @@ For more information about dashboards, see the following sections:
* [{#T}](../dashboard/widget.md)
* [{#T}](../dashboard/link.md)
* [{#T}](../dashboard/selector.md)
* [{#T}](../dashboard/chart-chart-filtration.md)
* [{#T}](../dashboard/dashboard_parameters.md)
* [{#T}](../dashboard/markdown.md)
* Step-by-step guides:

* [{#T}](../operations/dashboard/create.md)
Expand All @@ -26,4 +28,5 @@ For more information about dashboards, see the following sections:
* [Creating an alias](../operations/dashboard/create-alias.md)
* [{#T}](../operations/dashboard/edit-alias.md)
* [{#T}](../operations/dashboard/add-parameters.md)
* [{#T}](../operations/dashboard/add-filtration.md)

6 changes: 6 additions & 0 deletions en/datalens/concepts/data-join.md
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Expand Up @@ -35,6 +35,8 @@ You cannot join data from different sources at a single dataset level.

You can [join data](../operations/dataset/join-data.md) through the dataset creation interface by dragging tables to the workspace and configuring links between them using the [JOIN operator](dataset/data-model.md#source).

{% include [data-join-duplicate-fields-note](../../_includes/datalens/datalens-data-join-duplicate-fields-note.md) %}

#### SQL query {#sql-join}

In a dataset, you can add an [ad-hoc SQL query](dataset/settings.md#sql-request-in-datatset) to the data source. When accessing a data source, the query code is run as a subquery. You can use the output of the query as final dataset data or combine it with other source tables via the interface.
Expand All @@ -45,6 +47,10 @@ In a dataset, you can add an [ad-hoc SQL query](dataset/settings.md#sql-request-
To combine data at the chart level, you can use a [QL chart](#sql-chart).


#### QL chart {#sql-chart}

[QL charts](chart/index.md#sql-charts) are charts created from a connection if there is a database at the other end of the connection. Running a SQL query does not create a separate dataset object; instead, it generates one on the fly and displays it in the preview panel. For more information, see [{#T}](../operations/chart/create-sql-chart.md).


### Selector link level {#selector-join}

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6 changes: 1 addition & 5 deletions en/datalens/concepts/data-types.md
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Expand Up @@ -186,11 +186,7 @@ An array is a structure made up of a series of elements of the same type.
* `Floating-point number`
* `String`

{% note warning %}

You cannot define an array inside {{ datalens-short-name }}.

{% endnote %}
You can define an array in {{ datalens-short-name }} using the [ARRAY](../../datalens/function-ref/ARRAY.md) function.

#### Example notation {#array-example}

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1 change: 1 addition & 0 deletions en/datalens/concepts/dataset/index.md
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Expand Up @@ -23,6 +23,7 @@ To learn more about datasets and dataset operations, see:
* [{#T}](../../operations/dataset/create-field.md)
* [{#T}](../../operations/dataset/create-calculated-field.md)
* [{#T}](../../operations/dataset/create-filter.md)
* [{#T}](../../operations/dataset/replace-connection.md)
* [{#T}](../../operations/dataset/update-field.md)
* [{#T}](../../operations/dataset/add-data.md)
* [{#T}](../../operations/dataset/add-parameter-dataset.md)
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