New Features and Improvements
AtScale contains the following new features and improvements.
I2024.2.6
Crossjoin MDX function
AtScale now supports the Crossjoin MDX function, which returns a set that is the cross product of one or more sets. For more information, see Crossjoin.
ATSCALE-22685
Common table expressions
The AtScale engine now uses common table expressions (CTEs) to reduce redundancy in queries, thereby reducing query size.
This functionality is controlled via the new QUERY.PLANNING.ALLOWCTES engine setting, which is enabled by default. For more information, see Query Settings.
ATSCALE-15188
I2024.2.4
Semi-additive measures now support aggregation across multiple hierarchies
You can now configure semi-additive measures to execute their non-additive behavior when evaluated against several specific hierarchies, rather than being triggered by a single attribute. This functionality increases the generalizability of LVNE/FVNE measures, and saves you from having to author calculated measures with CASE statements wrapping individually created LVNE/FVNE measures.
To support this functionality, the Semi Additive Measure field in the Create and Edit a Measure dialog boxes now allows you to select multiple attributes, rather than just one.
For more information, see Add Semi-Additive Measures.
ATSCALE-21212
Distinct Sum aggregation for non-additive measures
You can now create non-additive measures that use Distinct Sum aggregation, which provides the sum of distinct values for integers.
To support this functionality, the Aggregation Type field in the Create and Edit a Measure dialog boxes contains a new option called Distinct Sum.
For more information on working with distinct sum measures, see Non-Additive Measures. For more information on creating non-additive measures, see Add Additive or Non-Additive Measures.
ATSCALE-21703
Measure support for MDX DateAdd and TimeStampAdd
The DateAdd and TimeStampAdd MDX functions can now be used in calculated measures. Additionally, they can now accept measures and calculated measures as arguments.
For more information, see DateAdd and TimeStampAdd.
ATSCALE-21883
Support for referencing calculation groups in calculated measures
Measures inside of calculated measures can now be scoped by the member range defined in a calculation group. This is typically a quantity of time like Month-to-Date or Equivalent Period in the Last Year.
To make this capability as re-usable as possible, you are no longer required to reference a specific hierarchy in your calculation group code. Additionally, for ParallelPeriods, you no longer need to reference a specific hierarchy level by name (e.g. "Year Level"), and can instead use metadata types, such as TimeYears.
For more information, see Referencing Calculation Groups in Calculated Measures.
ATSCALE-22059
In-memory dimensional aggregates is now GA
The in-memory dimensional aggregates functionality is now GA. For more information, see In-Memory Dimensional Aggregates.
In-dimensional aggregate support for security dimensions
In memory-dimensional aggregates can now be configured to join with security dimensions.
To enable this functionality, you must set the aggregates.dimensional.allowJoinsToSecondaries.enabled engine setting to TRUE. This configures the Create User Defined Aggregate dialog to include security dimension hierarchy levels.
For more information, see In-Memory Dimensional Aggregates.
ATSCALE-21651, ATSCALE-21651, ATSCALE-21965
I2024.2.3
In-memory dimensional aggregates is now GA
The in-memory dimensional aggregates functionality is now GA. For more information, see In-Memory Dimensional Aggregates.
I2024.2.2
In-memory dimensional aggregates is now GA
The in-memory dimensional aggregates functionality is now GA. For more information, see In-Memory Dimensional Aggregates.
Query Planning Optimization
AtScale now optimizes the planning stage for queries on complex calculated measures involving large numbers of CASE statements, resulting in faster processing times. For information on how the optimization works, see Optimizing Queries for Calculated Measures.
ATSCALE-21342, ATSCALE-21002
I2024.2.1
In-memory dimensional aggregates is now GA
The in-memory dimensional aggregates functionality is now GA. For more information, see In-Memory Dimensional Aggregates.
Aggregation functions for calculated measures
You can now set the specific aggregation function to use for a
calculated measure when it is referenced by the Aggregate MDX
function. This enables you to more easily reference calculated measures
from calculation groups.
To support this functionality, the dialog boxes for creating and editing calculated measures now contain an MDX Aggregation Function field, where you can select the aggregation function to use.
Note: AtScale recommends setting MDX Aggregation Function to a value other than None for calculated measures that are referenced via calculation groups.
For more information on the new field, see Add Calculated
Measures.
For more information on the Aggregate MDX function, see
Aggregate.
ATSCALE-20582
New MDX Functions
AtScale now supports the following MDX functions: NULLEXCEPT,
ALLMEMBEREXCEPT, ALLMEMBER. These enable you to control how
sensitive your server-side calculations are to the inbound query context
(i.e., the dimensions used in a query's grouping and filtering
directives).
For more information on the new functions, see MDX Reference.
ATSCALE-19554
Tableau with PostgreSQL
You can now connect to Tableau using the PostgreSQL JDBC driver. For instructions on configuring this, see Installing PostgreSQL JDBC Drivers.
ATSCALE-20346
Tableau: Improved tooltip performance
AtScale now more efficiently supports MIN/MAX queries on dimension attributes, providing improved performance for tooltips in Tableau reports.
ATSCALE-20241
Distinct Count Estimate Aggregates with Databricks SQL
AtScale can now create aggregates using the distinct count estimate function when connected to a Databricks SQL data warehouse.
ATSCALE-10988
New DAX Function
AtScale now supports the UTCNOW DAX function. For more information on using DAX Tabular with AtScale, see Using DAX Tabular.
ATSCALE-19848
Microsoft Excel: Improved Performance for Multi-Dimensional Result Set Assembly
AtScale now has improved performance for multi-dimensional result set assembly in Microsoft Excel, resulting in faster processing times.
Previously, result set assembly in Excel took a long time for queries that returned high numbers of cells. This improvement results in a 75% reduction in processing time for queries in the range of 100 thousand cells, and a 90% reduction in time for queries in the range of 1 million cells.
ATSCALE-16696
Outbound query optimization for multi-fact models
AtScale is now optimized to reduce the size of outbound queries for multi-fact models that contain calculated measures that use CASE statements to check hierarchy members, and that emit 1-of-n measures from a single fact table.
ATSCALE-20234