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Extends the columns of a fact table with values looked-up in a dimension table.
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For example, the following query results in a table that extends the `FactTable` (`$left`) with data from the `DimensionTable` (`$right`) by performing a lookup. The lookup matches each pair (`CommonColumn`, `Col1`) from `FactTable` with each pair (`CommonColumn`, `Col2`) in the `DimensionTable`. For the differences between fact and dimension tables, see [fact and dimension tables](../concepts/fact-and-dimension-tables.md).
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```kusto
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FactTable | lookup kind=leftouter (DimensionTable) on CommonColumn, $left.Col1 == $right.Col2
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```
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Here, the result is a table that extends the `FactTable` (`$left`) with data from `DimensionTable` (referenced by `$right`)
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by performing a lookup of each pair (`CommonColumn`,`Col`) from the former table
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with each pair (`CommonColumn1`,`Col2`) in the latter table.
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For the differences between fact and dimension tables, see [fact and dimension tables](../concepts/fact-and-dimension-tables.md).
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The `lookup` operator performs an operation similar to the [join operator](join-operator.md)
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with the following differences:
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* The result doesn't repeat columns from the `$right` table that are the basis
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for the join operation.
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* Only two kinds of lookup are supported, `leftouter` and `inner`,
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with `leftouter` being the default.
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* Only two kinds of lookup are supported, `leftouter` and `inner`, with `leftouter` being the default.
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* In terms of performance, the system by default assumes that the `$left` table
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is the larger (facts) table, and the `$right` table is the smaller (dimensions)
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table. This is exactly opposite to the assumption used by the `join` operator.
|*LeftTable*| `string` | :heavy_check_mark:|The table or tabular expression that is the basis for the lookup. Denoted as `$left`.|
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|*RightTable*| `string` | :heavy_check_mark:|The table or tabular expression that is used to "populate" new columns in the fact table. Denoted as `$right`.|
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|*Attributes*| `string` | :heavy_check_mark:|A comma-delimited list of one or more rules that describe how rows from *LeftTable* are matched to rows from *RightTable*. Multiple rules are evaluated using the `and` logical operator. See [Rules](#rules).|
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|`kind`| `string` ||Determines how to treat rows in *LeftTable* that have no match in *RightTable*. By default, `leftouter` is used, which means all those rows will appear in the output with null values used for the missing values of *RightTable* columns added by the operator. If `inner` is used, such rows are omitted from the output. Other kinds of join aren't supported by the `lookup` operator.|
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|`kind`| `string` ||Determines how to treat rows in *LeftTable* that have no match in *RightTable*. By default, `leftouter` is used, which means all those rows appear in the output with null values used for the missing values of *RightTable* columns added by the operator. If `inner` is used, such rows are omitted from the output. Other kinds of join aren't supported by the `lookup` operator.|
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### Rules
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@@ -73,45 +69,52 @@ with the following differences:
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A table with:
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* A column for every column in each of the two tables, including the matching keys.
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The columns of the right side will be automatically renamed if there are name conflicts.
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The columns of the right side are automatically renamed if there are name conflicts.
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* A row for every match between the input tables. A match is a row selected from one table that has the same value for all the `on` fields as a row in the other table.
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* The Attributes (lookup keys) will appear only once in the output table.
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* The *Attributes* (lookup keys) appear only once in the output table.
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* If `kind` is unspecified or `kind=leftouter`, then in addition to the inner matches, there's a row for every row on the left (and/or right), even if it has no match. In that case, the unmatched output cells contain nulls.
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* If `kind=inner`, then there's a row in the output for every combination of matching rows from left and right.
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## Examples
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The following example shows how to perform a left outer join between the `FactTable` and `DimTable`, based on matching values in the `Personal` and `Family` columns.
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:::moniker range="azure-data-explorer"
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> [!div class="nextstepaction"]
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> <a href="https://dataexplorer.azure.com/clusters/help/databases/Samples?query=H4sIAAAAAAAAA32RsW4CMQyG93sKKxOVslDahYoBqOhatWwVQ+4wyMJJqotpVakP3wQ3h2BAGRL7k+X/UxgFVq6TtWsZZ1sn+eTX6C1+T5P0FPb2FfsUg+Nar5wn/vmv7uCjATBjY8EsiDnfuXxxgsnYQu4vyZIpSAzKJjfYQ2Hvgl9YoFk4Zo+9ssfC1uRPY3kuxoNpNk8NZ5ln8tcuNwXsnMmlS5saqXqUJW3u7XX9gIfAijvFNfQ5M5hUeq3yGlxzq4KQ704Kw180v8CZHz/hQGE7Y9xJPAr2gyDEANXMgjr9AbRCGP7OAQAA" target="_blank">Run the query</a>
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> <a href="https://dataexplorer.azure.com/clusters/help/databases/Samples?query=H4sIAAAAAAAAA32RPWsDMQxA94P7D8JTA176tSRkKG2zBdqSrXTQJU5rTravPptykB8fuedzQobgRdKzJT1MKsAKt2GDDanlDgMfjm4%2B3N%2B8D17bb%2FmmfO8s0pSv0GgacjaDz7oCELdCguBHaDngfB199zMI%2BQ%2FvEnwl0v0IN9Fb5TO8vwYfElzjgIlx%2F0Zb3iXDxwTfo7bjTBDPaLpGEYm6%2BlrUFbHbizaXald95BNp7C%2FkilfRStN8qpq8SxEo%2B4NQqRbyhSxx5gDCcG0yPXmcNEar30S22an8VV0dgJxrYwettrslqX1wMShflMFZmFwljJZHtRbAkO8BAAA%3D" target="_blank">Run the query</a>
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::: moniker-end
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```kusto
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let FactTable=datatable(Row:string,Personal:string,Family:string) [
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"1", "Bill", "Gates",
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"2", "Bill", "Clinton",
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"3", "Bill", "Clinton",
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"4", "Steve", "Ballmer",
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"5", "Tim", "Cook"
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"1", "Rowan", "Murphy",
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"2", "Ellis", "Turner",
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"3", "Ellis", "Turner",
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"4", "Maya", "Robinson",
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"5", "Quinn", "Campbell"
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];
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let DimTable=datatable(Personal:string,Family:string,Alias:string) [
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"Bill", "Gates", "billg",
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"Bill", "Clinton", "billc",
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"Steve", "Ballmer", "steveb",
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"Tim", "Cook", "timc"
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"Rowan", "Murphy", "rowanm",
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"Ellis", "Turner", "ellist",
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"Maya", "Robinson", "mayar",
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"Quinn", "Campbell", "quinnc"
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];
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FactTable
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| lookup kind=leftouter DimTable on Personal, Family
Copy file name to clipboardExpand all lines: data-explorer/web-ui-query-keyboard-shortcuts.md
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@@ -3,56 +3,56 @@ title: Azure Data Explorer web UI query keyboard shortcuts
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description: This article describes Azure Data Explorer query keyboard shortcuts (hot keys) in Azure Data Explorer web UI.
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ms.reviewer: mibar
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ms.topic: reference
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ms.date: 05/28/2023
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ms.date: 12/04/2024
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---
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# Azure Data Explorer web UI keyboard shortcuts
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Keyboard shortcuts provide a quick way to navigate websites, and allow users to work more efficiently. Instead of using a pointing device, you use keys, or combinations of keys, to run tasks. This article lists Windows keyboard shortcuts that work in the Azure Data Explorer web UI query editor window and results grid.
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The letters that appear below represent letter keys on your keyboard. For example, to use <kbd>G</kbd>+<kbd>N</kbd>, hold down the <kbd>G</kbd> key and then press <kbd>N</kbd>. If the command is <kbd>Ctrl</kbd>+<kbd>K</kbd> <kbd>Ctrl</kbd>+<kbd>X</kbd>, keep pressing <kbd>Ctrl</kbd>, and simultaneously press <kbd>K</kbd> and then <kbd>X</kbd>.
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The following letters represent letter keys on your keyboard. For example, to use <kbd>G</kbd>+<kbd>N</kbd>, hold down the <kbd>G</kbd> key and then press <kbd>N</kbd>. If the command is <kbd>Ctrl</kbd>+<kbd>K</kbd> <kbd>Ctrl</kbd>+<kbd>X</kbd>, keep pressing <kbd>Ctrl</kbd>, and simultaneously press <kbd>K</kbd> and then <kbd>X</kbd>.
| Insert data cell selections as filters into the query | <kbd>Ctrl</kbd>+<kbd>Shift</kbd>+<kbd>Space</kbd> |
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|[Column header] Toggle the sorting state | <kbd>Enter</kbd> |
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|[Column header] Open the menu for the focused header | <kbd>Shift</kbd>+<kbd>Enter</kbd> |
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| To do this action | Windows shortcuts | Mac shortcuts|
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|--|--|--|
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| Insert data cell selections as filters into the query | <kbd>Ctrl</kbd>+<kbd>Shift</kbd>+<kbd>Space</kbd> | <kbd>⌘</kbd>+<kbd>Shift</kbd>+<kbd>Space</kbd> |
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|[Column header] Toggle the sorting state | <kbd>Enter</kbd> | <kbd>Enter</kbd>|
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|[Column header] Open the menu for the focused header | <kbd>Shift</kbd>+<kbd>Enter</kbd> | <kbd>Shift</kbd>+<kbd>Enter</kbd>|
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