Broken link fixed

Author: pritamso

articles/azure-monitor/logs/query-optimization.md

@@ -463,7 +463,7 @@ To efficiently execute a query, it's partitioned and distributed to compute node
 
 Query behaviors that can reduce parallelism include:
 
-- Use of serialization and window functions, such as the [serialize operator](/azure/kusto/query/serializeoperator), [next()](/azure/kusto/query/nextfunction), [prev()](/azure/kusto/query/prevfunction), and the [row](/azure/kusto/query/rowcumsumfunction) functions. Time series and user analytics functions can be used in some of these cases. Inefficient serialization might also happen if the following operators aren't used at the end of the query: [range](/azure/kusto/query/rangeoperator), [sort](/azure/kusto/query/sortoperator), [order](/azure/kusto/query/orderoperator), [top](/azure/kusto/query/topoperator), [top-hitters](/azure/kusto/query/tophittersoperator), and [getschema](/azure/kusto/query/getschemaoperator).
+- Use of serialization and window functions, such as the [serialize operator](/azure/kusto/query/serializeoperator), [next()](/azure/kusto/query/nextfunction), [prev()](/azure/kusto/query/prevfunction), and the [row](/azure/kusto/query/rowcumsumfunction) functions. Time series and user analytics functions can be used in some of these cases. Inefficient serialization might also happen if the following operators aren't used at the end of the query: [range](/azure/kusto/query/rangeoperator), [sort](/azure/data-explorer/kusto/query/sort-operator), [order](/azure/kusto/query/orderoperator), [top](/azure/kusto/query/topoperator), [top-hitters](/azure/kusto/query/tophittersoperator), and [getschema](/azure/kusto/query/getschemaoperator).
 - Use of the [dcount()](/azure/kusto/query/dcount-aggfunction) aggregation function forces the system to have a central copy of the distinct values. When the scale of data is high, consider using the `dcount` function optional parameters to reduce accuracy.
 - In many cases, the [join](/azure/kusto/query/joinoperator?pivots=azuremonitor) operator lowers overall parallelism. Examine `shuffle join` as an alternative when performance is problematic.
 - In resource-scope queries, the pre-execution Kubernetes role-based access control (RBAC) or Azure RBAC checks might linger in situations where there's a large number of Azure role assignments. This situation might lead to longer checks that would result in lower parallelism. For example, a query might be executed on a subscription where there are thousands of resources and each resource has many role assignments on the resource level, not on the subscription or resource group.