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Copy file name to clipboardExpand all lines: data-explorer/kusto/management/callout-policy.md
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| sandbox_artifacts | Controls sandboxed plugins ([python](../query/python-plugin.md) and [R](../query/r-plugin.md)). |
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| external_data | Controls access to external data through [external tables](../query/schema-entities/external-tables.md) or [externaldata](../query/externaldata-operator.md) operator. |
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| webapi | Controls access to http endpoints. |
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|ai_embed_text| Controls the [ai_embed_text plugin)](../query/ai-embed-text-plugin.md). |
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|azure_openai| Controls calls to Azure OpenAI plugins such as the embedding plugin [ai_embed_text plugin](../query/ai-embed-text-plugin.md). |
Copy file name to clipboardExpand all lines: data-explorer/kusto/query/parse-kv-operator.md
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@@ -3,7 +3,7 @@ title: parse-kv operator
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description: Learn how to use the parse-kv operator to represent structured information extracted from a string expression in a key/value form.
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ms.reviewer: alexans
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ms.topic: reference
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ms.date: 08/11/2024
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ms.date: 02/06/2025
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---
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# parse-kv operator
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The following extraction modes are supported:
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*[**Specified delimeter**](#specified-delimeter): Extraction based on specified delimiters that dictate how keys/values and pairs are separated from each other.
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*[**Non-specified delimeter**](#nonspecified-delimiter): Extraction with no need to specify delimiters. Any nonalphanumeric character is considered a delimiter.
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*[**Specified delimiter**](#specified-delimiter): Extraction based on specified delimiters that dictate how keys/values and pairs are separated from each other.
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*[**Non-specified delimiter**](#nonspecified-delimiter): Extraction with no need to specify delimiters. Any nonalphanumeric character is considered a delimiter.
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*[**Regex**](#regex): Extraction based on [regular expressions](regex.md).
The `parse` operator provides a streamlined way to `extend` a table by using multiple `extract` applications on the same `string` expression. This result is useful, when the table has a `string` column that contains several values that you want to break into individual columns. For example, a column that's produced by a developer trace ("`printf`"/"`Console.WriteLine`") statement.
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### Parse and extend results
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In the following example, the column `EventText` of table `Traces` contains
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strings of the form `Event: NotifySliceRelease (resourceName={0}, totalSlices={1}, sliceNumber={2}, lockTime={3}, releaseTime={4}, previousLockTime={5})`.
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The operation extends the table with six columns: `resourceName`, `totalSlices`, `sliceNumber`, `lockTime`, `releaseTime`, and `previousLockTime`.
The `parse-where` operator provides a streamlined way to `extend` a table by using multiple `extract` applications on the same `string` expression. This is most useful when the table has a `string` column that contains several values that you want to break into individual columns. For example, you can break up a column that was produced by a developer trace ("`printf`"/"`Console.WriteLine`") statement.
The partition operator partitions the records of its input table into multiple subtables according to values in a key column. The operator runs a subquery on each subtable, and produces a single output table that is the union of the results of all subqueries.
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This operator is useful when you need to perform a subquery only on a subset of rows that belongs to the same partition key, and not query the whole dataset. These subqueries could include aggregate functions, window functions, top *N* and others.
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The partition operator is useful when you need to perform a subquery only on a subset of rows that belong to the same partition key, and not a query of the whole dataset. These subqueries could include aggregate functions, window functions, top *N* and others.
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The partition operator supports several strategies of subquery operation:
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|*Column*|`string`|:heavy_check_mark:| The name of a column in *T* whose values determine how to partition the input tabular source.|
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|*TransformationSubQuery*|`string`|:heavy_check_mark:| A tabular transformation expression. The source is implicitly the subtables produced by partitioning the records of *T*. Each subtable is homogenous on the value of *Column*.</br></br> The expression must provide only one tabular result and shouldn't have other types of statements, such as `let` statements.|
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|*SubQueryWithSource*|`string`|:heavy_check_mark:| A tabular expression that includes its own tabular source, such as a table reference. This syntax is only supported with the [legacy strategy](#legacy-strategy). The subquery can only reference the key column, *Column*, from *T*. To reference the column, use the syntax `toscalar(`*Column*`)`.</br></br> The expression must provide only one tabular result and shouldn't have other types of statements, such as `let` statements.|
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| *Hints*| `string` | | Zero or more space-separated parameters in the form of: *HintName*`=`*Value* that control the behavior of the operator. See the [supported hints](#supported-hints) per strategy type.
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|*Hints*|`string`|| Zero or more space-separated parameters in the form of: *HintName*`=`*Value* that control the behavior of the operator. See the [supported hints](#supported-hints) per strategy type.|
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### Supported hints
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|Hint name|Type|Strategy|Description|
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|--|--|--|--|
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|`hint.shufflekey`|`string`|[shuffle](#shuffle-strategy)| The partition key used to run the partition operator with the `shuffle` strategy. |
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|`hint.materialized`|`bool`|[legacy](#legacy-strategy)| If set to `true`, will materialize the source of the `partition` operator. The default value is `false`. |
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|`hint.materialized`|`bool`|[legacy](#legacy-strategy)| If set to `true`, materializes the source of the `partition` operator. The default value is `false`. |
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|`hint.concurrency`|`int`|[legacy](#legacy-strategy)| Determines how many partitions to run in parallel. The default value is `16`.|
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|`hint.spread`|`int`|[legacy](#legacy-strategy)| Determines how to distribute the partitions among cluster nodes. The default value is `1`.</br></br> For example, if there are *N* partitions and the spread hint is set to *P*, then the *N* partitions will be processed by *P* different cluster nodes equally in parallel/sequentially depending on the concurrency hint.|
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|`hint.spread`|`int`|[legacy](#legacy-strategy)| Determines how to distribute the partitions among cluster nodes. The default value is `1`.</br></br> For example, if there are *N* partitions and the spread hint is set to *P*, then the *N* partitions are processed by *P* different cluster nodes equally, in parallel/sequentially depending on the concurrency hint.|
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## Returns
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To use this strategy, specify `hint.strategy=legacy` or omit any other strategy indication.
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> [!NOTE]
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> An error will occur if the partition column, *Column*, contains more than 64 distinct values.
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> An error occurs if the partition column, *Column*, contains more than 64 distinct values.
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## Examples
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The examples in this section show how to use the syntax to help you get started.
Copy file name to clipboardExpand all lines: data-explorer/kusto/query/pattern-statement.md
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|*PathArgType*|`string`|| The type of the *PathArgType* argument. Possible values: `string`|
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|*ArgValue*|`string`|:heavy_check_mark:| The *ArgName* and optional *PathName* tuple values to be mapped to an *expression*. |
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|*PathValue*|`string`|| The value to map for *PathName*. |
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|*expression*|`string`|:heavy_check_mark:| A tabular or lambda expression that references a function returning tabular data. For example: `Logs | where Timestamp > ago(1h)`|
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|*expression*|`string`|:heavy_check_mark:| A tabular or lambda expression that references a function returning tabular data. For example: `Logs | where Timestamp > ago(1h)`|
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## Examples
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The examples in this section show how to use the syntax to help you get started.
The following example outputs a row with two columns. One column contains the sum of a series of numbers and the other column contains the value of the variable, `x`.
Copy file name to clipboardExpand all lines: data-explorer/kusto/query/query-parameters-statement.md
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|Name|Type|Required|Description|
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|--|--|--|--|
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|*Name1*|`string`|:heavy_check_mark:|The name of a query parameter used in the query.|
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|*Type1*|`string`|:heavy_check_mark:|The corresponding type, such as `string` or `datetime`. The values provided by the user are encoded as strings. The appropriate parse method is applied to the query parameter to get a strongly-typed value.|
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|*Type1*|`string`|:heavy_check_mark:|The corresponding type, such as `string` or `datetime`. The values provided by the user are encoded as strings. The appropriate parse method is applied to the query parameter to get a stronglytyped value.|
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|*DefaultValue1*|`string`||A default value for the parameter. This value must be a literal of the appropriate scalar type.|
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> [!NOTE]
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## Example
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The examples in this section show how to use the syntax to help you get started.
This query retrieves storm events from the *StormEvents* table where the total number of direct and indirect injuries exceeds a specified threshold (default is 90). It then projects the *EpisodeId*, *EventType*, and the total number of injuries for each of these events.
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:::moniker range="azure-data-explorer"
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> [!div class="nextstepaction"]
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> <ahref="https://dataexplorer.azure.com/clusters/help/databases/Samples?query=H4sIAAAAAAAAA4WNuw7CMBAE+0j5hytBpKAFBBUpXEOPrHgFjvzifAEi8fEkQUBJO9qZNWicZtC1A/enpFl7CDjPvH6o0HYMs3YxnGlLq+V8UxYHiezrG4JkKosn3S8Y9GlqkfeW0QgtvkAF80Y7+hVHL3FsR14nm6OBMhVN1WOfUJFE0e7TGL7/9l+H314eyAAAAA=="target="_blank">Run the query</a>
Copy file name to clipboardExpand all lines: data-explorer/kusto/query/range-operator.md
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description: Learn how to use the range operator to generate a single-column table of values.
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ms.reviewer: alexans
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ms.topic: reference
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ms.date: 01/07/2025
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ms.date: 01/22/2025
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# range operator
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|--|--|--|--|
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|*columnName*|`string`|:heavy_check_mark:| The name of the single column in the output table.|
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|*start*|int, long, real, datetime, or timespan|:heavy_check_mark:| The smallest value in the output.|
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|*stop*|int, long, real, datetime, or timespan|:heavy_check_mark:| The highest value being generated in the output or a bound on the highest value if *step*steps over this value.|
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|*stop*|int, long, real, datetime, or timespan|:heavy_check_mark:| The highest value being generated in the output or a bound on the highest value if *step*is over this value.|
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|*step*|int, long, real, datetime, or timespan|:heavy_check_mark:| The difference between two consecutive values.|
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> [!NOTE]
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## Examples
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The example in this section shows how to use the syntax to help you get started.
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```kusto
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range Steps from 1 to 8 step 3
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```
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**Output**
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| Steps |
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|-------|
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| 1 |
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| 4 |
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| 7 |
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|--|
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| 1 |
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| 7 |
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### Traces over a time range
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The following example shows how the `range` operator can be used to create a dimension table that is used to introduce zeros where the source data has no values. It takes timestamps from the last four hours and counts traces for each oneminute interval. When there are no traces for a specific interval, the count is zero.
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The following example shows how the `range` operator can be used to create a dimension table that is used to introduce zeros where the source data has no values. It takes timestamps from the last four hours and counts traces for each one-minute interval. When there are no traces for a specific interval, the count is zero.
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