partition operator
Applies to: ✅ Microsoft Fabric ✅ Azure Data Explorer ✅ Azure Monitor ✅ Microsoft Sentinel
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.
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.
The partition operator supports several strategies of subquery operation:
- Native - use with an implicit data source with thousands of key partition values.
- Shuffle - use with an implicit source with millions of key partition values.
- Legacy - use with an implicit or explicit source for 64 or less key partition values.
Syntax
T |
partition
[ hint.strategy=
Strategy ] [ Hints ] by
Column (
TransformationSubQuery )
T |
partition
[ hint.strategy=legacy
] [ Hints ] by
Column {
SubQueryWithSource }
Learn more about syntax conventions.
Parameters
Name | Type | Required | Description |
---|---|---|---|
T | string |
✔️ | The input tabular source. |
Strategy | string |
The value legacy , shuffle , or native . This hint defines the execution strategy of the partition operator.If no strategy is specified, the legacy strategy is used. For more information, see Strategies. |
|
Column | string |
✔️ | The name of a column in T whose values determine how to partition the input tabular source. |
TransformationSubQuery | string |
✔️ | 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. The expression must provide only one tabular result and shouldn't have other types of statements, such as let statements. |
SubQueryWithSource | string |
✔️ | A tabular expression that includes its own tabular source, such as a table reference. This syntax is only supported with the legacy strategy. The subquery can only reference the key column, Column, from T. To reference the column, use the syntax toscalar( Column) .The expression must provide only one tabular result and shouldn't have other types of statements, such as let statements. |
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 per strategy type. |
Supported hints
Hint name | Type | Strategy | Description |
---|---|---|---|
hint.shufflekey |
string |
shuffle | The partition key used to run the partition operator with the shuffle strategy. |
hint.materialized |
bool |
legacy | If set to true , will materialize the source of the partition operator. The default value is false . |
hint.concurrency |
int |
legacy | Determines how many partitions to run in parallel. The default value is 16 . |
hint.spread |
int |
legacy | Determines how to distribute the partitions among cluster nodes. The default value is 1 .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. |
Returns
The operator returns a union of the results of the individual subqueries.
Strategies
The partition operator supports several strategies of subquery operation: native, shuffle, and legacy.
Note
The distinction between the native
and shuffle
strategies allows the caller to indicate the cardinality and execution strategy of the subquery. This choice may affect how long the subquery takes to complete but doesn't change the end result.
Native strategy
This strategy should be applied when the number of distinct values of the partition key isn't large, roughly in the thousands.
The subquery must be a tabular transformation that doesn't specify a tabular source. The source is implicit and is assigned according to the subtable partitions. Only certain supported operators can be used in the subquery. There's no restriction on the number of partitions.
To use this strategy, specify hint.strategy=native
.
Shuffle strategy
This strategy should be applied when the number of distinct values of the partition key is large, in the millions.
The subquery must be a tabular transformation that doesn't specify a tabular source. The source is implicit and is assigned according to the subtable partitions. Only certain supported operators can be used in the subquery. There's no restriction on the number of partitions.
To use this strategy, specify hint.strategy=shuffle
. For more information about shuffle strategy and performance, see shuffle query.
Supported operators for the native and shuffle strategies
The following list of operators can be used in subqueries with the native or shuffle strategies:
- count
- distinct
- extend
- make-series
- mv-apply
- mv-expand
- parse
- parse-where
- project
- project-away
- project-keep
- project-rename
- project-reorder
- reduce
- sample
- sample-distinct
- scan
- search
- serialize
- sort
- summarize
- take
- top
- top-hitters
- top-nested
- where
Note
- Operators that reference a table source other than the subtable partitions aren't compatible with the
native
andshuffle
strategies. For example, join, union, externaldata, and evaluate (plugins). For such scenarios, resort to the legacy strategy. - The fork operator isn't supported for any strategy type, as the subquery must return a single tabular result.
Legacy strategy
For historical reasons, the legacy
strategy is the default strategy. However, we recommend favoring the native or shuffle strategies, as the legacy
approach is limited to 64 partitions and is less efficient.
In some scenarios, the legacy
strategy might be necessary due to its support for including a tabular source in the subquery. In such cases, the subquery can only reference the key column, Column, from the input tabular source, T. To reference the column, use the syntax toscalar(
Column)
.
If the subquery is a tabular transformation without a tabular source, the source is implicit and is based on the subtable partitions.
To use this strategy, specify hint.strategy=legacy
or omit any other strategy indication.
Note
An error will occur if the partition column, Column, contains more than 64 distinct values.
Examples
Find top values
In some cases, it's more performant and easier to write a query using the partition
operator than using the top-nested
operator. The following query runs a subquery calculating summarize
and top
for each State
starting with W
: "WYOMING", "WASHINGTON", "WEST VIRGINIA", and "WISCONSIN".
StormEvents
| where State startswith 'W'
| partition hint.strategy=native by State
(
summarize Events=count(), Injuries=sum(InjuriesDirect) by EventType, State
| top 3 by Events
)
Output
EventType | State | Events | Injuries |
---|---|---|---|
Hail | WYOMING | 108 | 0 |
High Wind | WYOMING | 81 | 5 |
Winter Storm | WYOMING | 72 | 0 |
Heavy Snow | WASHINGTON | 82 | 0 |
High Wind | WASHINGTON | 58 | 13 |
Wildfire | WASHINGTON | 29 | 0 |
Thunderstorm Wind | WEST VIRGINIA | 180 | 1 |
Hail | WEST VIRGINIA | 103 | 0 |
Winter Weather | WEST VIRGINIA | 88 | 0 |
Thunderstorm Wind | WISCONSIN | 416 | 1 |
Winter Storm | WISCONSIN | 310 | 0 |
Hail | WISCONSIN | 303 | 1 |
Native strategy
The following query returns the top 2 EventType
values by TotalInjuries
for each State
that starts with 'W':
StormEvents
| where State startswith 'W'
| partition hint.strategy = native by State
(
summarize TotalInjueries = sum(InjuriesDirect) by EventType
| top 2 by TotalInjueries
)
Output
EventType | TotalInjueries |
---|---|
Tornado | 4 |
Hail | 1 |
Thunderstorm Wind | 1 |
Excessive Heat | 0 |
High Wind | 13 |
Lightning | 5 |
High Wind | 5 |
Avalanche | 3 |
Shuffle strategy
The following query returns the top 3 DamagedProperty
values foreach EpisodeId
and the columns EpisodeId
and State
.
StormEvents
| partition hint.strategy=shuffle by EpisodeId
(
top 3 by DamageProperty
| project EpisodeId, State, DamageProperty
)
| count
Output
Count |
---|
22345 |
Legacy strategy with explicit source
The following query runs two subqueries:
- When
x == 1
, the query returns all rows fromStormEvents
that haveInjuriesIndirect == 1
. - When
x == 2
, the query returns all rows fromStormEvents
that haveInjuriesIndirect == 2
.
The final result is the union of these two subqueries.
range x from 1 to 2 step 1
| partition hint.strategy=legacy by x {StormEvents | where x == InjuriesIndirect}
| count
Output
Count |
---|
113 |
Partition reference
The following example shows how to use the as operator to give a "name" to each data partition and then reuse that name within the subquery. This approach is only relevant to the legacy
strategy.
T
| partition by Dim
(
as Partition
| extend MetricPct = Metric * 100.0 / toscalar(Partition | summarize sum(Metric))
)